Glue opcodes report
This is a snapshot of the latest archived evm-gasfit run. All numerical tables and regression summaries are retained. Plots are omitted. Runtime estimates do not depend on the gas anchor. See the supporting report for the source details and gas estimates at 75 Mgas/s.
This report uses nonnegative least squares (NNLS) to estimate auxiliary opcode runtimes for each client. Cycle tier opcodes share one joint regression per client. Pure tier and mixed tier opcodes each use a fit with one feature.
Mixed tier fits first subtract the estimated time spent on upstream partner opcodes. For mixed_a, these partners come from the pure and cycle tiers. For mixed_b, they also include the mixed_a tier.
Contents: besu, erigon, ethrex, geth, nethermind, reth
besu
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
1067 |
6.097e-06 |
1.00e-03 |
0.9869 |
JUMPDEST |
1067 |
1.205e-06 |
1.00e-03 |
0.8849 |
SWAP |
17072 |
3.562e-06 |
1.00e-03 |
0.9695 |
CALLDATASIZE |
63173 |
5.045e-06 |
1.00e-03 |
0.9875 |
DUP |
63173 |
2.342e-06 |
1.00e-03 |
0.9875 |
GAS |
63173 |
4.155e-06 |
1.00e-03 |
0.9875 |
MLOAD |
63173 |
1.328e-05 |
1.00e-03 |
0.9875 |
PUSH |
63173 |
3.123e-06 |
1.00e-03 |
0.9875 |
PUSH0 |
63173 |
2.242e-06 |
1.00e-03 |
0.9875 |
STATICCALL |
63173 |
0.0008686 |
1.00e-03 |
0.9875 |
ADD |
1067 |
1.629e-05 |
1.00e-03 |
0.9788 |
AND |
1067 |
1.05e-05 |
1.00e-03 |
0.9462 |
CALLDATACOPY |
25608 |
2.36e-05 |
1.00e-03 |
0.7204 |
CALLDATALOAD |
4268 |
3.431e-05 |
1.00e-03 |
0.03926 |
DIV |
1067 |
2.324e-05 |
1.00e-03 |
0.981 |
EXP |
1067 |
0.00229 |
1.00e-03 |
0.9693 |
GT |
1067 |
4.46e-05 |
1.00e-03 |
0.9835 |
JUMPI |
1067 |
9.852e-06 |
1.00e-03 |
0.9715 |
LT |
1067 |
3.649e-05 |
1.00e-03 |
0.3061 |
MSTORE |
5335 |
2.707e-05 |
1.00e-03 |
0.9774 |
MSTORE8 |
5335 |
1.553e-05 |
1.00e-03 |
0.9703 |
MUL |
1067 |
1.39e-05 |
1.00e-03 |
0.8203 |
PC |
1067 |
5.074e-06 |
1.00e-03 |
0.9801 |
RETURNDATASIZE |
4268 |
7.389e-06 |
1.00e-03 |
0.9842 |
SELFBALANCE |
1067 |
2.344e-05 |
1.00e-03 |
0.9871 |
SUB |
1067 |
1.727e-05 |
1.00e-03 |
0.9882 |
JUMP |
1067 |
3.687e-05 |
1.00e-03 |
0.987 |
KECCAK256 |
17072 |
4.594e-05 |
1.00e-03 |
0.1016 |
Cycle glue: joint fit, besu
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.987
Model: NNLS Adj. R-squared: 0.987
No. Observations: 63173 RMSE: 17.11
Df Residuals: 63165 MAE: 9.86
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 34.9023 0.2429 0.001 34.4202 35.3485
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0009 0.0000 0.001 0.0009 0.0009
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=63173, runtime_ms=5.045e-06, p=1.00e-03, R²=0.9875
DUP, nobs=63173, runtime_ms=2.342e-06, p=1.00e-03, R²=0.9875
GAS, nobs=63173, runtime_ms=4.155e-06, p=1.00e-03, R²=0.9875
MLOAD, nobs=63173, runtime_ms=1.328e-05, p=1.00e-03, R²=0.9875
PUSH, nobs=63173, runtime_ms=3.123e-06, p=1.00e-03, R²=0.9875
PUSH0, nobs=63173, runtime_ms=2.242e-06, p=1.00e-03, R²=0.9875
STATICCALL, nobs=63173, runtime_ms=0.0008686, p=1.00e-03, R²=0.9875
Pure glue, besu
ISZERO, nobs=1067, runtime_ms=6.097e-06, p=1.00e-03, R²=0.9869
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.987
Model: NNLS Adj. R-squared: 0.987
No. Observations: 1067 RMSE: 14.79
Df Residuals: 1065 MAE: 10.93
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 34.2684 1.5632 0.001 31.1505 37.3538
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=1067, runtime_ms=1.205e-06, p=1.00e-03, R²=0.8849
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.885
Model: NNLS Adj. R-squared: 0.885
No. Observations: 1067 RMSE: 27.45
Df Residuals: 1065 MAE: 13.82
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 27.5062 2.5349 0.001 22.5978 32.4065
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=17072, runtime_ms=3.562e-06, p=1.00e-03, R²=0.9695
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.969
Model: NNLS Adj. R-squared: 0.969
No. Observations: 17072 RMSE: 13.32
Df Residuals: 17070 MAE: 9.73
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 31.5310 0.3124 0.001 30.9261 32.1369
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), besu
ADD, nobs=1067, runtime_ms=1.629e-05, p=1.00e-03, R²=0.9788
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.979
Model: NNLS Adj. R-squared: 0.979
No. Observations: 1067 RMSE: 25.24
Df Residuals: 1065 MAE: 20.05
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 74.6889 2.8580 0.001 69.0477 80.0287
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=1067, runtime_ms=1.05e-05, p=1.00e-03, R²=0.9462
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.946
Model: NNLS Adj. R-squared: 0.946
No. Observations: 1067 RMSE: 26.37
Df Residuals: 1065 MAE: 11.01
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 39.8178 2.3094 0.001 35.1187 43.8601
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=25608, runtime_ms=2.36e-05, p=1.00e-03, R²=0.7204
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.720
Model: NNLS Adj. R-squared: 0.720
No. Observations: 25608 RMSE: 110.60
Df Residuals: 25606 MAE: 85.88
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 138.2697 0.7261 0.001 136.8788 139.7283
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=4268, runtime_ms=3.431e-05, p=1.00e-03, R²=0.03926
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.039
Model: NNLS Adj. R-squared: 0.039
No. Observations: 4268 RMSE: 0.65
Df Residuals: 4266 MAE: 0.42
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 2.9211 0.0383 0.001 2.8448 2.9950
CALLDATALOAD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=1067, runtime_ms=2.324e-05, p=1.00e-03, R²=0.981
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.981
Model: NNLS Adj. R-squared: 0.981
No. Observations: 1067 RMSE: 25.51
Df Residuals: 1065 MAE: 18.58
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 89.1046 2.1357 0.001 84.4769 93.0821
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=1067, runtime_ms=0.00229, p=1.00e-03, R²=0.9693
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.969
Model: NNLS Adj. R-squared: 0.969
No. Observations: 1067 RMSE: 15.96
Df Residuals: 1065 MAE: 11.51
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 66.7214 2.3857 0.001 62.0108 71.4222
EXP 0.0023 0.0000 0.001 0.0023 0.0023
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=1067, runtime_ms=4.46e-05, p=1.00e-03, R²=0.9835
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.983
Model: NNLS Adj. R-squared: 0.983
No. Observations: 1067 RMSE: 60.84
Df Residuals: 1065 MAE: 48.72
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 118.1598 6.8655 0.001 105.0555 131.8340
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=1067, runtime_ms=9.852e-06, p=1.00e-03, R²=0.9715
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.971
Model: NNLS Adj. R-squared: 0.971
No. Observations: 1067 RMSE: 7.62
Df Residuals: 1065 MAE: 5.43
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 19.6079 0.7037 0.001 18.1048 20.9084
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=1067, runtime_ms=3.649e-05, p=1.00e-03, R²=0.3061
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.306
Model: NNLS Adj. R-squared: 0.305
No. Observations: 1067 RMSE: 578.52
Df Residuals: 1065 MAE: 537.00
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 109.1524 50.0815 0.017 8.0092 208.2890
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=5335, runtime_ms=2.707e-05, p=1.00e-03, R²=0.9774
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.977
Model: NNLS Adj. R-squared: 0.977
No. Observations: 5335 RMSE: 28.90
Df Residuals: 5333 MAE: 23.20
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 48.1290 1.2876 0.001 45.7086 50.5695
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=5335, runtime_ms=1.553e-05, p=1.00e-03, R²=0.9703
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.970
Model: NNLS Adj. R-squared: 0.970
No. Observations: 5335 RMSE: 19.06
Df Residuals: 5333 MAE: 13.96
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 25.3590 0.7848 0.001 23.8614 26.8685
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=1067, runtime_ms=1.39e-05, p=1.00e-03, R²=0.8203
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.820
Model: NNLS Adj. R-squared: 0.820
No. Observations: 1067 RMSE: 51.39
Df Residuals: 1065 MAE: 32.91
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 47.1055 4.5740 0.001 37.9001 55.9982
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=1067, runtime_ms=5.074e-06, p=1.00e-03, R²=0.9801
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.980
Model: NNLS Adj. R-squared: 0.980
No. Observations: 1067 RMSE: 21.61
Df Residuals: 1065 MAE: 16.40
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 27.9476 2.1954 0.001 23.4155 32.2691
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=4268, runtime_ms=7.389e-06, p=1.00e-03, R²=0.9842
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.984
Model: NNLS Adj. R-squared: 0.984
No. Observations: 4268 RMSE: 14.80
Df Residuals: 4266 MAE: 10.18
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 36.7557 0.7639 0.001 35.3253 38.2218
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=1067, runtime_ms=2.344e-05, p=1.00e-03, R²=0.9871
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.987
Model: NNLS Adj. R-squared: 0.987
No. Observations: 1067 RMSE: 33.09
Df Residuals: 1065 MAE: 25.94
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 49.0053 3.7973 0.001 41.7580 57.0884
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=1067, runtime_ms=1.727e-05, p=1.00e-03, R²=0.9882
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.988
Model: NNLS Adj. R-squared: 0.988
No. Observations: 1067 RMSE: 19.91
Df Residuals: 1065 MAE: 13.52
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 47.5521 1.7805 0.001 43.8725 50.9199
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), besu
JUMP, nobs=1067, runtime_ms=3.687e-05, p=1.00e-03, R²=0.987
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.987
Model: NNLS Adj. R-squared: 0.987
No. Observations: 1067 RMSE: 15.74
Df Residuals: 1065 MAE: 11.54
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 43.3092 1.6103 0.001 40.2416 46.4411
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=17072, runtime_ms=4.594e-05, p=1.00e-03, R²=0.1016
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.102
Model: NNLS Adj. R-squared: 0.102
No. Observations: 17072 RMSE: 271.61
Df Residuals: 17070 MAE: 217.92
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 763.2790 4.5617 0.001 754.6101 771.9629
KECCAK256 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
erigon
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
1089 |
1.575e-06 |
1.00e-03 |
0.5326 |
JUMPDEST |
1089 |
1.207e-06 |
1.00e-03 |
0.4256 |
SWAP |
17424 |
1.937e-06 |
1.00e-03 |
0.8104 |
CALLDATASIZE |
64482 |
1.63e-06 |
1.00e-03 |
0.7937 |
DUP |
64482 |
1.901e-06 |
1.00e-03 |
0.7937 |
GAS |
64482 |
1.655e-06 |
1.00e-03 |
0.7937 |
MLOAD |
64482 |
4.443e-06 |
1.00e-03 |
0.7937 |
PUSH |
64482 |
2.966e-06 |
1.00e-03 |
0.7937 |
PUSH0 |
64482 |
1.633e-06 |
1.00e-03 |
0.7937 |
STATICCALL |
64482 |
5.864e-05 |
1.00e-03 |
0.7937 |
ADD |
1089 |
3.378e-06 |
1.00e-03 |
0.4558 |
AND |
1089 |
3.398e-06 |
1.00e-03 |
0.4912 |
CALLDATACOPY |
26136 |
1.032e-05 |
1.00e-03 |
0.9594 |
CALLDATALOAD |
4356 |
5.138e-05 |
1.00e-03 |
0.1927 |
DIV |
1089 |
1.413e-05 |
1.00e-03 |
0.9243 |
EXP |
1089 |
0.0006888 |
1.00e-03 |
0.981 |
GT |
1089 |
3.455e-06 |
1.00e-03 |
0.505 |
JUMPI |
1089 |
4.681e-06 |
1.00e-03 |
0.8555 |
LT |
1089 |
3.465e-06 |
1.00e-03 |
0.5108 |
MSTORE |
5445 |
6.85e-06 |
1.00e-03 |
0.4373 |
MSTORE8 |
5445 |
7.129e-06 |
1.00e-03 |
0.7473 |
MUL |
1089 |
5.275e-06 |
1.00e-03 |
0.5413 |
PC |
1089 |
1.751e-06 |
1.00e-03 |
0.9798 |
RETURNDATASIZE |
4356 |
2.9e-06 |
1.00e-03 |
0.8139 |
SELFBALANCE |
1089 |
1.928e-06 |
1.00e-03 |
0.9613 |
SUB |
1089 |
3.417e-06 |
1.00e-03 |
0.4848 |
JUMP |
1089 |
8.02e-06 |
1.00e-03 |
0.5586 |
KECCAK256 |
17424 |
5.972e-06 |
1.00e-03 |
0.002552 |
Cycle glue: joint fit, erigon
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.794
Model: NNLS Adj. R-squared: 0.794
No. Observations: 64482 RMSE: 31.55
Df Residuals: 64474 MAE: 18.87
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 16.8406 0.3474 0.001 16.1746 17.5400
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0001 0.0000 0.001 0.0001 0.0001
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=64482, runtime_ms=1.63e-06, p=1.00e-03, R²=0.7937
DUP, nobs=64482, runtime_ms=1.901e-06, p=1.00e-03, R²=0.7937
GAS, nobs=64482, runtime_ms=1.655e-06, p=1.00e-03, R²=0.7937
MLOAD, nobs=64482, runtime_ms=4.443e-06, p=1.00e-03, R²=0.7937
PUSH, nobs=64482, runtime_ms=2.966e-06, p=1.00e-03, R²=0.7937
PUSH0, nobs=64482, runtime_ms=1.633e-06, p=1.00e-03, R²=0.7937
STATICCALL, nobs=64482, runtime_ms=5.864e-05, p=1.00e-03, R²=0.7937
Pure glue, erigon
ISZERO, nobs=1089, runtime_ms=1.575e-06, p=1.00e-03, R²=0.5326
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.533
Model: NNLS Adj. R-squared: 0.532
No. Observations: 1089 RMSE: 31.08
Df Residuals: 1087 MAE: 24.57
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.8921 2.7546 0.001 3.4568 14.1441
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=1089, runtime_ms=1.207e-06, p=1.00e-03, R²=0.4256
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.426
Model: NNLS Adj. R-squared: 0.425
No. Observations: 1089 RMSE: 88.58
Df Residuals: 1087 MAE: 70.79
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.6525 7.7588 0.037 0.0000 30.1437
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=17424, runtime_ms=1.937e-06, p=1.00e-03, R²=0.8104
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.810
Model: NNLS Adj. R-squared: 0.810
No. Observations: 17424 RMSE: 19.73
Df Residuals: 17422 MAE: 10.43
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 17.2551 0.4865 0.001 16.2337 18.1739
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), erigon
ADD, nobs=1089, runtime_ms=3.378e-06, p=1.00e-03, R²=0.4558
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.456
Model: NNLS Adj. R-squared: 0.455
No. Observations: 1089 RMSE: 38.87
Df Residuals: 1087 MAE: 30.52
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 14.2725 3.5162 0.001 7.2908 21.0937
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=1089, runtime_ms=3.398e-06, p=1.00e-03, R²=0.4912
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.491
Model: NNLS Adj. R-squared: 0.491
No. Observations: 1089 RMSE: 36.41
Df Residuals: 1087 MAE: 28.73
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.1921 3.2759 0.001 6.0315 19.1270
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=26136, runtime_ms=1.032e-05, p=1.00e-03, R²=0.9594
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.959
Model: NNLS Adj. R-squared: 0.959
No. Observations: 26136 RMSE: 15.97
Df Residuals: 26134 MAE: 10.66
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 14.3940 0.1183 0.001 14.1707 14.6302
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=4356, runtime_ms=5.138e-05, p=1.00e-03, R²=0.1927
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.193
Model: NNLS Adj. R-squared: 0.192
No. Observations: 4356 RMSE: 0.40
Df Residuals: 4354 MAE: 0.19
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.2291 0.0173 0.001 4.1945 4.2631
CALLDATALOAD 0.0001 0.0000 0.001 0.0000 0.0001
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=1089, runtime_ms=1.413e-05, p=1.00e-03, R²=0.9243
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.924
Model: NNLS Adj. R-squared: 0.924
No. Observations: 1089 RMSE: 31.94
Df Residuals: 1087 MAE: 25.14
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 29.8056 3.1696 0.001 23.5041 35.7120
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=1089, runtime_ms=0.0006888, p=1.00e-03, R²=0.981
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.981
Model: NNLS Adj. R-squared: 0.981
No. Observations: 1089 RMSE: 3.76
Df Residuals: 1087 MAE: 2.99
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.2110 0.4431 0.001 8.3873 10.0979
EXP 0.0007 0.0000 0.001 0.0007 0.0007
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=1089, runtime_ms=3.455e-06, p=1.00e-03, R²=0.505
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.505
Model: NNLS Adj. R-squared: 0.505
No. Observations: 1089 RMSE: 36.02
Df Residuals: 1087 MAE: 27.64
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.3184 3.4392 0.001 6.5011 20.0403
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=1089, runtime_ms=4.681e-06, p=1.00e-03, R²=0.8555
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.855
Model: NNLS Adj. R-squared: 0.855
No. Observations: 1089 RMSE: 8.68
Df Residuals: 1087 MAE: 6.40
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.6278 0.8484 0.001 8.0301 11.3332
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=1089, runtime_ms=3.465e-06, p=1.00e-03, R²=0.5108
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.511
Model: NNLS Adj. R-squared: 0.510
No. Observations: 1089 RMSE: 35.71
Df Residuals: 1087 MAE: 27.53
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.5595 3.2161 0.001 6.8622 19.8708
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=5445, runtime_ms=6.85e-06, p=1.00e-03, R²=0.4373
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.437
Model: NNLS Adj. R-squared: 0.437
No. Observations: 5445 RMSE: 54.55
Df Residuals: 5443 MAE: 43.54
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 15.9383 2.0440 0.001 11.7785 20.2300
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=5445, runtime_ms=7.129e-06, p=1.00e-03, R²=0.7473
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.747
Model: NNLS Adj. R-squared: 0.747
No. Observations: 5445 RMSE: 29.10
Df Residuals: 5443 MAE: 22.81
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 15.5302 1.1195 0.001 13.4172 17.7377
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=1089, runtime_ms=5.275e-06, p=1.00e-03, R²=0.5413
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.541
Model: NNLS Adj. R-squared: 0.541
No. Observations: 1089 RMSE: 38.35
Df Residuals: 1087 MAE: 29.66
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.0172 3.2450 0.003 1.6978 14.6537
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=1089, runtime_ms=1.751e-06, p=1.00e-03, R²=0.9798
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.980
Model: NNLS Adj. R-squared: 0.980
No. Observations: 1089 RMSE: 7.52
Df Residuals: 1087 MAE: 6.23
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.9412 0.8754 0.001 11.2925 14.7194
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=4356, runtime_ms=2.9e-06, p=1.00e-03, R²=0.8139
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.814
Model: NNLS Adj. R-squared: 0.814
No. Observations: 4356 RMSE: 21.91
Df Residuals: 4354 MAE: 16.24
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.1639 0.9718 0.001 10.2260 14.0062
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=1089, runtime_ms=1.928e-06, p=1.00e-03, R²=0.9613
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.961
Model: NNLS Adj. R-squared: 0.961
No. Observations: 1089 RMSE: 4.78
Df Residuals: 1087 MAE: 3.76
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.3918 0.4488 0.001 6.4887 8.2413
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=1089, runtime_ms=3.417e-06, p=1.00e-03, R²=0.4848
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.485
Model: NNLS Adj. R-squared: 0.484
No. Observations: 1089 RMSE: 37.09
Df Residuals: 1087 MAE: 29.03
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.2945 3.4508 0.001 6.9475 20.1371
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), erigon
JUMP, nobs=1089, runtime_ms=8.02e-06, p=1.00e-03, R²=0.5586
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.559
Model: NNLS Adj. R-squared: 0.558
No. Observations: 1089 RMSE: 26.50
Df Residuals: 1087 MAE: 20.87
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 10.2817 2.4346 0.001 5.6044 14.8511
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=17424, runtime_ms=5.972e-06, p=1.00e-03, R²=0.002552
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.003
Model: NNLS Adj. R-squared: 0.002
No. Observations: 17424 RMSE: 234.72
Df Residuals: 17422 MAE: 186.56
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 573.2789 3.3761 0.001 566.5371 579.8039
KECCAK256 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
ethrex
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
110 |
7.251e-07 |
1.00e-03 |
0.8973 |
JUMPDEST |
110 |
5.06e-07 |
1.00e-03 |
0.8625 |
SWAP |
1760 |
8.804e-07 |
1.00e-03 |
0.8673 |
CALLDATASIZE |
6655 |
6.443e-07 |
1.00e-03 |
0.9571 |
DUP |
6655 |
6.648e-07 |
1.00e-03 |
0.9571 |
GAS |
6655 |
6.681e-07 |
1.00e-03 |
0.9571 |
MLOAD |
6655 |
1.705e-06 |
1.00e-03 |
0.9571 |
PUSH |
6655 |
8.316e-07 |
1.00e-03 |
0.9571 |
PUSH0 |
6655 |
5.945e-07 |
1.00e-03 |
0.9571 |
STATICCALL |
6655 |
0.000132 |
1.00e-03 |
0.9571 |
ADD |
110 |
1.734e-06 |
1.00e-03 |
0.931 |
AND |
110 |
1.297e-06 |
1.00e-03 |
0.9075 |
CALLDATACOPY |
2640 |
3.997e-06 |
1.00e-03 |
0.9228 |
CALLDATALOAD |
440 |
2.655e-05 |
1.00e-03 |
0.1755 |
DIV |
110 |
1.365e-05 |
1.00e-03 |
0.9453 |
EXP |
110 |
0.001842 |
1.00e-03 |
0.963 |
GT |
110 |
1.75e-06 |
1.00e-03 |
0.9602 |
JUMPI |
110 |
2.236e-06 |
1.00e-03 |
0.8041 |
LT |
110 |
1.722e-06 |
1.00e-03 |
0.9513 |
MSTORE |
550 |
2.483e-06 |
1.00e-03 |
0.9367 |
MSTORE8 |
550 |
2.556e-06 |
1.00e-03 |
0.9476 |
MUL |
110 |
3.245e-06 |
1.00e-03 |
0.6291 |
PC |
110 |
7.961e-07 |
1.00e-03 |
0.9233 |
RETURNDATASIZE |
440 |
1.2e-06 |
1.00e-03 |
0.864 |
SELFBALANCE |
110 |
1.032e-05 |
1.00e-03 |
0.9602 |
SUB |
110 |
1.697e-06 |
1.00e-03 |
0.9043 |
JUMP |
110 |
4.197e-06 |
1.00e-03 |
0.945 |
KECCAK256 |
1760 |
0 |
1.00e+00 |
0 |
Cycle glue: joint fit, ethrex
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.957
Model: NNLS Adj. R-squared: 0.957
No. Observations: 6655 RMSE: 7.32
Df Residuals: 6647 MAE: 5.35
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.4778 0.2809 0.001 7.9347 9.0178
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0001 0.0000 0.001 0.0001 0.0001
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=6655, runtime_ms=6.443e-07, p=1.00e-03, R²=0.9571
DUP, nobs=6655, runtime_ms=6.648e-07, p=1.00e-03, R²=0.9571
GAS, nobs=6655, runtime_ms=6.681e-07, p=1.00e-03, R²=0.9571
MLOAD, nobs=6655, runtime_ms=1.705e-06, p=1.00e-03, R²=0.9571
PUSH, nobs=6655, runtime_ms=8.316e-07, p=1.00e-03, R²=0.9571
PUSH0, nobs=6655, runtime_ms=5.945e-07, p=1.00e-03, R²=0.9571
STATICCALL, nobs=6655, runtime_ms=0.000132, p=1.00e-03, R²=0.9571
Pure glue, ethrex
ISZERO, nobs=110, runtime_ms=7.251e-07, p=1.00e-03, R²=0.8973
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.897
Model: NNLS Adj. R-squared: 0.896
No. Observations: 110 RMSE: 5.17
Df Residuals: 108 MAE: 4.13
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.1731 1.4782 0.001 5.2025 10.9581
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=110, runtime_ms=5.06e-07, p=1.00e-03, R²=0.8625
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.863
Model: NNLS Adj. R-squared: 0.861
No. Observations: 110 RMSE: 12.76
Df Residuals: 108 MAE: 9.51
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.1752 3.6465 0.001 6.1061 20.3064
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=1760, runtime_ms=8.804e-07, p=1.00e-03, R²=0.8673
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.867
Model: NNLS Adj. R-squared: 0.867
No. Observations: 1760 RMSE: 7.25
Df Residuals: 1758 MAE: 5.83
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 10.5845 0.5006 0.001 9.6258 11.5920
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), ethrex
ADD, nobs=110, runtime_ms=1.734e-06, p=1.00e-03, R²=0.931
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.931
Model: NNLS Adj. R-squared: 0.930
No. Observations: 110 RMSE: 4.97
Df Residuals: 108 MAE: 3.85
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.4616 1.6100 0.001 5.2198 11.3837
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=110, runtime_ms=1.297e-06, p=1.00e-03, R²=0.9075
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.907
Model: NNLS Adj. R-squared: 0.907
No. Observations: 110 RMSE: 4.36
Df Residuals: 108 MAE: 3.51
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.8059 1.4072 0.001 6.0058 11.6268
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=2640, runtime_ms=3.997e-06, p=1.00e-03, R²=0.9228
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.923
Model: NNLS Adj. R-squared: 0.923
No. Observations: 2640 RMSE: 8.70
Df Residuals: 2638 MAE: 6.44
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.4017 0.2012 0.001 13.0123 13.8145
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=440, runtime_ms=2.655e-05, p=1.00e-03, R²=0.1755
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.175
Model: NNLS Adj. R-squared: 0.174
No. Observations: 440 RMSE: 0.22
Df Residuals: 438 MAE: 0.17
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 2.3635 0.0361 0.001 2.2962 2.4320
CALLDATALOAD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=110, runtime_ms=1.365e-05, p=1.00e-03, R²=0.9453
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.945
Model: NNLS Adj. R-squared: 0.945
No. Observations: 110 RMSE: 25.93
Df Residuals: 108 MAE: 19.53
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 47.3308 8.6819 0.001 30.3407 63.6586
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=110, runtime_ms=0.001842, p=1.00e-03, R²=0.963
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.963
Model: NNLS Adj. R-squared: 0.963
No. Observations: 110 RMSE: 14.15
Df Residuals: 108 MAE: 11.50
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 18.2296 4.4047 0.001 9.1229 26.1515
EXP 0.0018 0.0000 0.001 0.0018 0.0019
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=110, runtime_ms=1.75e-06, p=1.00e-03, R²=0.9602
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.960
Model: NNLS Adj. R-squared: 0.960
No. Observations: 110 RMSE: 3.75
Df Residuals: 108 MAE: 3.03
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.8371 1.2548 0.001 4.1737 9.2638
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=110, runtime_ms=2.236e-06, p=1.00e-03, R²=0.8041
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.804
Model: NNLS Adj. R-squared: 0.802
No. Observations: 110 RMSE: 4.98
Df Residuals: 108 MAE: 3.36
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.6657 1.4722 0.004 1.6392 7.4188
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=110, runtime_ms=1.722e-06, p=1.00e-03, R²=0.9513
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.951
Model: NNLS Adj. R-squared: 0.951
No. Observations: 110 RMSE: 4.10
Df Residuals: 108 MAE: 3.13
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.8851 1.5648 0.001 5.9922 12.0822
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=550, runtime_ms=2.483e-06, p=1.00e-03, R²=0.9367
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.937
Model: NNLS Adj. R-squared: 0.937
No. Observations: 550 RMSE: 4.53
Df Residuals: 548 MAE: 3.54
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.0189 0.6129 0.001 6.8584 9.1575
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=550, runtime_ms=2.556e-06, p=1.00e-03, R²=0.9476
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.948
Model: NNLS Adj. R-squared: 0.948
No. Observations: 550 RMSE: 4.22
Df Residuals: 548 MAE: 3.22
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.6734 0.6258 0.001 6.4355 8.8800
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=110, runtime_ms=3.245e-06, p=1.00e-03, R²=0.6291
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.629
Model: NNLS Adj. R-squared: 0.626
No. Observations: 110 RMSE: 19.68
Df Residuals: 108 MAE: 15.74
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 27.5993 5.9692 0.001 15.9174 39.3799
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=110, runtime_ms=7.961e-07, p=1.00e-03, R²=0.9233
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.923
Model: NNLS Adj. R-squared: 0.923
No. Observations: 110 RMSE: 6.86
Df Residuals: 108 MAE: 5.23
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.0822 2.0363 0.001 9.0777 17.1945
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=440, runtime_ms=1.2e-06, p=1.00e-03, R²=0.864
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.864
Model: NNLS Adj. R-squared: 0.864
No. Observations: 440 RMSE: 7.52
Df Residuals: 438 MAE: 5.82
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.5133 1.0621 0.001 7.4689 11.6429
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=110, runtime_ms=1.032e-05, p=1.00e-03, R²=0.9602
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.960
Model: NNLS Adj. R-squared: 0.960
No. Observations: 110 RMSE: 25.96
Df Residuals: 108 MAE: 19.93
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 33.6183 8.4528 0.001 15.9669 49.8346
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=110, runtime_ms=1.697e-06, p=1.00e-03, R²=0.9043
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.904
Model: NNLS Adj. R-squared: 0.903
No. Observations: 110 RMSE: 5.81
Df Residuals: 108 MAE: 4.55
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.1569 1.8988 0.001 5.2369 12.8686
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), ethrex
JUMP, nobs=110, runtime_ms=4.197e-06, p=1.00e-03, R²=0.945
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.945
Model: NNLS Adj. R-squared: 0.945
No. Observations: 110 RMSE: 3.76
Df Residuals: 108 MAE: 2.92
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.1731 1.1693 0.001 6.9337 11.4902
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=1760, runtime_ms=0, p=1.00e+00, R²=0
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.000
Model: NNLS Adj. R-squared: -0.001
No. Observations: 1760 RMSE: 271.45
Df Residuals: 1758 MAE: 225.92
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 406.9619 6.2290 0.001 394.1295 418.3335
KECCAK256 0.0000 0.0000 1.000 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
geth
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
1595 |
1.887e-06 |
1.00e-03 |
0.9354 |
JUMPDEST |
1595 |
1.292e-06 |
1.00e-03 |
0.8414 |
SWAP |
25520 |
2.268e-06 |
1.00e-03 |
0.9496 |
CALLDATASIZE |
94391 |
1.796e-06 |
1.00e-03 |
0.9151 |
DUP |
94391 |
1.997e-06 |
1.00e-03 |
0.9151 |
GAS |
94391 |
1.784e-06 |
1.00e-03 |
0.9151 |
MLOAD |
94391 |
5.65e-06 |
1.00e-03 |
0.9151 |
PUSH |
94391 |
3.155e-06 |
1.00e-03 |
0.9151 |
PUSH0 |
94391 |
1.669e-06 |
1.00e-03 |
0.9151 |
STATICCALL |
94391 |
0.0002389 |
1.00e-03 |
0.9151 |
ADD |
1595 |
4.503e-06 |
1.00e-03 |
0.9124 |
AND |
1595 |
4.417e-06 |
1.00e-03 |
0.9084 |
CALLDATACOPY |
38280 |
1.153e-05 |
1.00e-03 |
0.977 |
CALLDATALOAD |
6380 |
2.461e-05 |
1.00e-03 |
0.07049 |
DIV |
1595 |
1.439e-05 |
1.00e-03 |
0.9789 |
EXP |
1595 |
0.0007158 |
1.00e-03 |
0.9822 |
GT |
1595 |
3.969e-06 |
1.00e-03 |
0.8474 |
JUMPI |
1595 |
5.576e-06 |
1.00e-03 |
0.837 |
LT |
1595 |
4.358e-06 |
1.00e-03 |
0.9362 |
MSTORE |
7975 |
8.479e-06 |
1.00e-03 |
0.9406 |
MSTORE8 |
7975 |
7.851e-06 |
1.00e-03 |
0.9251 |
MUL |
1595 |
5.359e-06 |
1.00e-03 |
0.9461 |
PC |
1595 |
1.98e-06 |
1.00e-03 |
0.9472 |
RETURNDATASIZE |
6380 |
5.368e-06 |
1.00e-03 |
0.8652 |
SELFBALANCE |
1595 |
1.233e-05 |
1.00e-03 |
0.9702 |
SUB |
1595 |
4.347e-06 |
1.00e-03 |
0.9147 |
JUMP |
1595 |
9.644e-06 |
1.00e-03 |
0.8032 |
KECCAK256 |
25520 |
3.778e-05 |
1.00e-03 |
0.1168 |
Cycle glue: joint fit, geth
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.915
Model: NNLS Adj. R-squared: 0.915
No. Observations: 94391 RMSE: 21.61
Df Residuals: 94383 MAE: 13.24
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 16.1525 0.2117 0.001 15.7469 16.5535
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0002 0.0000 0.001 0.0002 0.0002
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=94391, runtime_ms=1.796e-06, p=1.00e-03, R²=0.9151
DUP, nobs=94391, runtime_ms=1.997e-06, p=1.00e-03, R²=0.9151
GAS, nobs=94391, runtime_ms=1.784e-06, p=1.00e-03, R²=0.9151
MLOAD, nobs=94391, runtime_ms=5.65e-06, p=1.00e-03, R²=0.9151
PUSH, nobs=94391, runtime_ms=3.155e-06, p=1.00e-03, R²=0.9151
PUSH0, nobs=94391, runtime_ms=1.669e-06, p=1.00e-03, R²=0.9151
STATICCALL, nobs=94391, runtime_ms=0.0002389, p=1.00e-03, R²=0.9151
Pure glue, geth
ISZERO, nobs=1595, runtime_ms=1.887e-06, p=1.00e-03, R²=0.9354
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.935
Model: NNLS Adj. R-squared: 0.935
No. Observations: 1595 RMSE: 10.45
Df Residuals: 1593 MAE: 5.62
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.7116 1.0064 0.001 6.8767 10.8339
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=1595, runtime_ms=1.292e-06, p=1.00e-03, R²=0.8414
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.841
Model: NNLS Adj. R-squared: 0.841
No. Observations: 1595 RMSE: 35.45
Df Residuals: 1593 MAE: 13.63
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 18.8843 2.4901 0.001 14.1043 23.6523
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=25520, runtime_ms=2.268e-06, p=1.00e-03, R²=0.9496
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.950
Model: NNLS Adj. R-squared: 0.950
No. Observations: 25520 RMSE: 11.01
Df Residuals: 25518 MAE: 6.77
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.4632 0.2431 0.001 11.9832 12.9303
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), geth
ADD, nobs=1595, runtime_ms=4.503e-06, p=1.00e-03, R²=0.9124
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.912
Model: NNLS Adj. R-squared: 0.912
No. Observations: 1595 RMSE: 14.69
Df Residuals: 1593 MAE: 7.84
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.5262 1.1394 0.001 2.2816 6.6021
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=1595, runtime_ms=4.417e-06, p=1.00e-03, R²=0.9084
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.908
Model: NNLS Adj. R-squared: 0.908
No. Observations: 1595 RMSE: 14.77
Df Residuals: 1593 MAE: 8.14
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.4078 1.1454 0.001 4.0359 8.5204
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=38280, runtime_ms=1.153e-05, p=1.00e-03, R²=0.977
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.977
Model: NNLS Adj. R-squared: 0.977
No. Observations: 38280 RMSE: 13.30
Df Residuals: 38278 MAE: 8.49
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.7332 0.0847 0.001 13.5668 13.9037
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=6380, runtime_ms=2.461e-05, p=1.00e-03, R²=0.07049
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.070
Model: NNLS Adj. R-squared: 0.070
No. Observations: 6380 RMSE: 0.34
Df Residuals: 6378 MAE: 0.15
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 1.7837 0.0152 0.001 1.7555 1.8147
CALLDATALOAD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=1595, runtime_ms=1.439e-05, p=1.00e-03, R²=0.9789
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.979
Model: NNLS Adj. R-squared: 0.979
No. Observations: 1595 RMSE: 16.67
Df Residuals: 1593 MAE: 13.40
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 26.4239 1.4395 0.001 23.4731 29.3463
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=1595, runtime_ms=0.0007158, p=1.00e-03, R²=0.9822
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.982
Model: NNLS Adj. R-squared: 0.982
No. Observations: 1595 RMSE: 3.78
Df Residuals: 1593 MAE: 3.06
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 3.2335 0.2853 0.001 2.7018 3.8147
EXP 0.0007 0.0000 0.001 0.0007 0.0007
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=1595, runtime_ms=3.969e-06, p=1.00e-03, R²=0.8474
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.847
Model: NNLS Adj. R-squared: 0.847
No. Observations: 1595 RMSE: 17.74
Df Residuals: 1593 MAE: 11.01
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 24.9365 1.9617 0.001 21.2616 28.7457
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=1595, runtime_ms=5.576e-06, p=1.00e-03, R²=0.837
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.837
Model: NNLS Adj. R-squared: 0.837
No. Observations: 1595 RMSE: 11.11
Df Residuals: 1593 MAE: 5.61
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.8169 0.9486 0.001 2.9980 6.8364
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=1595, runtime_ms=4.358e-06, p=1.00e-03, R²=0.9362
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.936
Model: NNLS Adj. R-squared: 0.936
No. Observations: 1595 RMSE: 11.98
Df Residuals: 1593 MAE: 7.22
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.2216 1.0629 0.001 5.2012 9.3340
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=7975, runtime_ms=8.479e-06, p=1.00e-03, R²=0.9406
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.941
Model: NNLS Adj. R-squared: 0.941
No. Observations: 7975 RMSE: 14.96
Df Residuals: 7973 MAE: 9.24
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 13.1446 0.5511 0.001 12.0517 14.1743
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=7975, runtime_ms=7.851e-06, p=1.00e-03, R²=0.9251
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.925
Model: NNLS Adj. R-squared: 0.925
No. Observations: 7975 RMSE: 15.69
Df Residuals: 7973 MAE: 9.31
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 14.8031 0.5920 0.001 13.6721 15.9935
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=1595, runtime_ms=5.359e-06, p=1.00e-03, R²=0.9461
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.946
Model: NNLS Adj. R-squared: 0.946
No. Observations: 1595 RMSE: 10.11
Df Residuals: 1593 MAE: 6.36
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 10.1673 0.8118 0.001 8.5899 11.6815
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=1595, runtime_ms=1.98e-06, p=1.00e-03, R²=0.9472
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.947
Model: NNLS Adj. R-squared: 0.947
No. Observations: 1595 RMSE: 13.98
Df Residuals: 1593 MAE: 9.88
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 14.2903 1.2269 0.001 12.0160 16.6217
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=6380, runtime_ms=5.368e-06, p=1.00e-03, R²=0.8652
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.865
Model: NNLS Adj. R-squared: 0.865
No. Observations: 6380 RMSE: 33.46
Df Residuals: 6378 MAE: 25.81
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 57.4778 1.5006 0.001 54.6717 60.4306
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=1595, runtime_ms=1.233e-05, p=1.00e-03, R²=0.9702
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.970
Model: NNLS Adj. R-squared: 0.970
No. Observations: 1595 RMSE: 26.70
Df Residuals: 1593 MAE: 21.90
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 48.1645 2.5311 0.001 43.2829 53.4037
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=1595, runtime_ms=4.347e-06, p=1.00e-03, R²=0.9147
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.915
Model: NNLS Adj. R-squared: 0.915
No. Observations: 1595 RMSE: 13.98
Df Residuals: 1593 MAE: 7.33
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.9023 1.1188 0.001 6.8541 11.0750
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), geth
JUMP, nobs=1595, runtime_ms=9.644e-06, p=1.00e-03, R²=0.8032
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.803
Model: NNLS Adj. R-squared: 0.803
No. Observations: 1595 RMSE: 17.74
Df Residuals: 1593 MAE: 9.96
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 18.7051 2.0850 0.001 14.8379 22.9761
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=25520, runtime_ms=3.778e-05, p=1.00e-03, R²=0.1168
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.117
Model: NNLS Adj. R-squared: 0.117
No. Observations: 25520 RMSE: 206.57
Df Residuals: 25518 MAE: 166.27
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 567.3920 2.7701 0.001 561.9039 572.7694
KECCAK256 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
nethermind
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
1661 |
5.57e-07 |
1.00e-03 |
0.4845 |
JUMPDEST |
1661 |
3.782e-07 |
1.00e-03 |
0.7618 |
SWAP |
26576 |
6.042e-07 |
1.00e-03 |
0.6358 |
CALLDATASIZE |
98208 |
4.521e-07 |
1.00e-03 |
0.8723 |
DUP |
98208 |
3.413e-07 |
1.00e-03 |
0.8723 |
GAS |
98208 |
3.689e-07 |
1.00e-03 |
0.8723 |
MLOAD |
98208 |
1.923e-06 |
1.00e-03 |
0.8723 |
PUSH |
98208 |
5.851e-07 |
1.00e-03 |
0.8723 |
PUSH0 |
98208 |
2.964e-07 |
1.00e-03 |
0.8723 |
STATICCALL |
98208 |
0.0002937 |
1.00e-03 |
0.8723 |
ADD |
1661 |
1.462e-06 |
1.00e-03 |
0.8833 |
AND |
1661 |
1.192e-06 |
1.00e-03 |
0.8966 |
CALLDATACOPY |
39864 |
4.034e-06 |
1.00e-03 |
0.7819 |
CALLDATALOAD |
6644 |
1.757e-05 |
1.00e-03 |
0.09259 |
DIV |
1661 |
5.535e-06 |
1.00e-03 |
0.5437 |
EXP |
1661 |
0 |
1.00e+00 |
0 |
GT |
1661 |
1.467e-06 |
1.00e-03 |
0.9421 |
JUMPI |
1661 |
2.292e-06 |
1.00e-03 |
0.8969 |
LT |
1661 |
1.437e-06 |
1.00e-03 |
0.9415 |
MSTORE |
8305 |
2.749e-06 |
1.00e-03 |
0.9276 |
MSTORE8 |
8305 |
2.757e-06 |
1.00e-03 |
0.9166 |
MUL |
1661 |
4.259e-06 |
1.00e-03 |
0.9519 |
PC |
1661 |
6.116e-07 |
1.00e-03 |
0.8791 |
RETURNDATASIZE |
6644 |
9.423e-07 |
1.00e-03 |
0.8028 |
SELFBALANCE |
1661 |
3.767e-06 |
1.00e-03 |
0.9394 |
SUB |
1661 |
2.023e-06 |
1.00e-03 |
0.8617 |
JUMP |
1661 |
2.931e-06 |
1.00e-03 |
0.7711 |
KECCAK256 |
26576 |
0 |
1.00e+00 |
0 |
Cycle glue: joint fit, nethermind
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.872
Model: NNLS Adj. R-squared: 0.872
No. Observations: 98208 RMSE: 10.90
Df Residuals: 98200 MAE: 7.45
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.7698 0.1030 0.001 6.5626 6.9623
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0003 0.0000 0.001 0.0003 0.0003
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=98208, runtime_ms=4.521e-07, p=1.00e-03, R²=0.8723
DUP, nobs=98208, runtime_ms=3.413e-07, p=1.00e-03, R²=0.8723
GAS, nobs=98208, runtime_ms=3.689e-07, p=1.00e-03, R²=0.8723
MLOAD, nobs=98208, runtime_ms=1.923e-06, p=1.00e-03, R²=0.8723
PUSH, nobs=98208, runtime_ms=5.851e-07, p=1.00e-03, R²=0.8723
PUSH0, nobs=98208, runtime_ms=2.964e-07, p=1.00e-03, R²=0.8723
STATICCALL, nobs=98208, runtime_ms=0.0002937, p=1.00e-03, R²=0.8723
Pure glue, nethermind
ISZERO, nobs=1661, runtime_ms=5.57e-07, p=1.00e-03, R²=0.4845
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.484
Model: NNLS Adj. R-squared: 0.484
No. Observations: 1661 RMSE: 12.10
Df Residuals: 1659 MAE: 4.97
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.5041 1.0807 0.001 4.7022 8.9889
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=1661, runtime_ms=3.782e-07, p=1.00e-03, R²=0.7618
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.762
Model: NNLS Adj. R-squared: 0.762
No. Observations: 1661 RMSE: 13.36
Df Residuals: 1659 MAE: 10.20
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.5646 0.9430 0.001 5.7334 9.2993
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=26576, runtime_ms=6.042e-07, p=1.00e-03, R²=0.6358
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.636
Model: NNLS Adj. R-squared: 0.636
No. Observations: 26576 RMSE: 9.63
Df Residuals: 26574 MAE: 5.48
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.1578 0.1992 0.001 11.7938 12.5554
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), nethermind
ADD, nobs=1661, runtime_ms=1.462e-06, p=1.00e-03, R²=0.8833
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.883
Model: NNLS Adj. R-squared: 0.883
No. Observations: 1661 RMSE: 5.60
Df Residuals: 1659 MAE: 4.20
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.0229 0.4134 0.001 6.1935 7.8324
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=1661, runtime_ms=1.192e-06, p=1.00e-03, R²=0.8966
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.897
Model: NNLS Adj. R-squared: 0.896
No. Observations: 1661 RMSE: 4.26
Df Residuals: 1659 MAE: 3.15
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 5.3164 0.3130 0.001 4.6903 5.9278
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=39864, runtime_ms=4.034e-06, p=1.00e-03, R²=0.7819
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.782
Model: NNLS Adj. R-squared: 0.782
No. Observations: 39864 RMSE: 16.03
Df Residuals: 39862 MAE: 12.58
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 20.4063 0.0841 0.001 20.2474 20.5684
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=6644, runtime_ms=1.757e-05, p=1.00e-03, R²=0.09259
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.093
Model: NNLS Adj. R-squared: 0.092
No. Observations: 6644 RMSE: 0.21
Df Residuals: 6642 MAE: 0.14
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 1.7934 0.0087 0.001 1.7748 1.8095
CALLDATALOAD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=1661, runtime_ms=5.535e-06, p=1.00e-03, R²=0.5437
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.544
Model: NNLS Adj. R-squared: 0.543
No. Observations: 1661 RMSE: 40.04
Df Residuals: 1659 MAE: 29.88
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 113.4877 5.0126 0.001 103.7268 123.0339
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=1661, runtime_ms=0, p=1.00e+00, R²=0
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.000
Model: NNLS Adj. R-squared: -0.001
No. Observations: 1661 RMSE: 1.19
Df Residuals: 1659 MAE: 0.87
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 3.3793 0.0286 0.001 3.3266 3.4388
EXP 0.0000 0.0000 1.000 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=1661, runtime_ms=1.467e-06, p=1.00e-03, R²=0.9421
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.942
Model: NNLS Adj. R-squared: 0.942
No. Observations: 1661 RMSE: 3.83
Df Residuals: 1659 MAE: 2.82
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.7215 0.3203 0.001 6.1109 7.3437
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=1661, runtime_ms=2.292e-06, p=1.00e-03, R²=0.8969
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.897
Model: NNLS Adj. R-squared: 0.897
No. Observations: 1661 RMSE: 3.51
Df Residuals: 1659 MAE: 1.93
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.7335 0.3051 0.001 4.1499 5.3825
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=1661, runtime_ms=1.437e-06, p=1.00e-03, R²=0.9415
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.941
Model: NNLS Adj. R-squared: 0.941
No. Observations: 1661 RMSE: 3.77
Df Residuals: 1659 MAE: 2.84
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.6964 0.3319 0.001 7.0960 8.3617
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=8305, runtime_ms=2.749e-06, p=1.00e-03, R²=0.9276
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.928
Model: NNLS Adj. R-squared: 0.928
No. Observations: 8305 RMSE: 5.39
Df Residuals: 8303 MAE: 3.69
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.4334 0.1758 0.001 7.0911 7.7852
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=8305, runtime_ms=2.757e-06, p=1.00e-03, R²=0.9166
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.917
Model: NNLS Adj. R-squared: 0.917
No. Observations: 8305 RMSE: 5.84
Df Residuals: 8303 MAE: 3.95
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.9334 0.2147 0.001 6.5251 7.3527
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=1661, runtime_ms=4.259e-06, p=1.00e-03, R²=0.9519
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.952
Model: NNLS Adj. R-squared: 0.952
No. Observations: 1661 RMSE: 7.56
Df Residuals: 1659 MAE: 5.67
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 11.5409 0.5140 0.001 10.5155 12.5107
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=1661, runtime_ms=6.116e-07, p=1.00e-03, R²=0.8791
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.879
Model: NNLS Adj. R-squared: 0.879
No. Observations: 1661 RMSE: 6.78
Df Residuals: 1659 MAE: 5.35
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.9987 0.4947 0.001 6.0606 7.9056
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=6644, runtime_ms=9.423e-07, p=1.00e-03, R²=0.8028
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.803
Model: NNLS Adj. R-squared: 0.803
No. Observations: 6644 RMSE: 7.38
Df Residuals: 6642 MAE: 3.83
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.2613 0.3241 0.001 5.6662 6.9088
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=1661, runtime_ms=3.767e-06, p=1.00e-03, R²=0.9394
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.939
Model: NNLS Adj. R-squared: 0.939
No. Observations: 1661 RMSE: 11.83
Df Residuals: 1659 MAE: 8.05
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 16.5843 0.9829 0.001 14.7251 18.5877
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=1661, runtime_ms=2.023e-06, p=1.00e-03, R²=0.8617
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.862
Model: NNLS Adj. R-squared: 0.862
No. Observations: 1661 RMSE: 8.53
Df Residuals: 1659 MAE: 5.87
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.8375 0.5875 0.001 5.6454 7.9713
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), nethermind
JUMP, nobs=1661, runtime_ms=2.931e-06, p=1.00e-03, R²=0.7711
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.771
Model: NNLS Adj. R-squared: 0.771
No. Observations: 1661 RMSE: 5.94
Df Residuals: 1659 MAE: 3.07
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.2891 0.5737 0.001 6.2512 8.4384
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=26576, runtime_ms=0, p=1.00e+00, R²=0
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.000
Model: NNLS Adj. R-squared: -0.000
No. Observations: 26576 RMSE: 216.15
Df Residuals: 26574 MAE: 177.96
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 316.4548 1.2984 0.001 313.9681 319.1505
KECCAK256 0.0000 0.0000 1.000 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
reth
| glue_opcode |
nobs |
glue_runtime_ms |
p_value |
rsquared |
ISZERO |
946 |
1.733e-06 |
1.00e-03 |
0.9283 |
JUMPDEST |
946 |
5.286e-07 |
1.00e-03 |
0.9638 |
SWAP |
15136 |
6.168e-07 |
1.00e-03 |
0.6087 |
CALLDATASIZE |
56023 |
8.685e-07 |
1.00e-03 |
0.7803 |
DUP |
56023 |
5.92e-07 |
1.00e-03 |
0.7803 |
GAS |
56023 |
7.167e-07 |
1.00e-03 |
0.7803 |
MLOAD |
56023 |
2.045e-06 |
1.00e-03 |
0.7803 |
PUSH |
56023 |
6.92e-07 |
1.00e-03 |
0.7803 |
PUSH0 |
56023 |
5.795e-07 |
1.00e-03 |
0.7803 |
STATICCALL |
56023 |
8.121e-05 |
1.00e-03 |
0.7803 |
ADD |
946 |
1.476e-06 |
1.00e-03 |
0.9394 |
AND |
946 |
1.415e-06 |
1.00e-03 |
0.9245 |
CALLDATACOPY |
22704 |
4.241e-06 |
1.00e-03 |
0.9118 |
CALLDATALOAD |
3784 |
0 |
1.00e+00 |
1.11e-16 |
DIV |
946 |
1.067e-05 |
1.00e-03 |
0.9476 |
EXP |
946 |
0.0006835 |
1.00e-03 |
0.9599 |
GT |
946 |
1.557e-06 |
1.00e-03 |
0.9486 |
JUMPI |
946 |
2.255e-06 |
1.00e-03 |
0.9359 |
LT |
946 |
3.08e-06 |
1.00e-03 |
0.6899 |
MSTORE |
4730 |
3.655e-06 |
1.00e-03 |
0.3993 |
MSTORE8 |
4730 |
2.186e-06 |
1.00e-03 |
0.9256 |
MUL |
946 |
2.269e-06 |
1.00e-03 |
0.9441 |
PC |
946 |
9.372e-07 |
1.00e-03 |
0.6985 |
RETURNDATASIZE |
3784 |
1.398e-06 |
1.00e-03 |
0.9506 |
SELFBALANCE |
946 |
8.157e-06 |
1.00e-03 |
0.9606 |
SUB |
946 |
1.577e-06 |
1.00e-03 |
0.9326 |
JUMP |
946 |
4.242e-06 |
1.00e-03 |
0.9527 |
KECCAK256 |
15136 |
0 |
1.00e+00 |
0 |
Cycle glue: joint fit, reth
Joint NNLS regression summary
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.780
Model: NNLS Adj. R-squared: 0.780
No. Observations: 56023 RMSE: 11.59
Df Residuals: 56015 MAE: 5.08
Df Model: 7
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.5101 0.1636 0.001 9.1948 9.8325
CALLDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
DUP 0.0000 0.0000 0.001 0.0000 0.0000
GAS 0.0000 0.0000 0.001 0.0000 0.0000
MLOAD 0.0000 0.0000 0.001 0.0000 0.0000
PUSH 0.0000 0.0000 0.001 0.0000 0.0000
PUSH0 0.0000 0.0000 0.001 0.0000 0.0000
STATICCALL 0.0001 0.0000 0.001 0.0001 0.0001
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATASIZE, nobs=56023, runtime_ms=8.685e-07, p=1.00e-03, R²=0.7803
DUP, nobs=56023, runtime_ms=5.92e-07, p=1.00e-03, R²=0.7803
GAS, nobs=56023, runtime_ms=7.167e-07, p=1.00e-03, R²=0.7803
MLOAD, nobs=56023, runtime_ms=2.045e-06, p=1.00e-03, R²=0.7803
PUSH, nobs=56023, runtime_ms=6.92e-07, p=1.00e-03, R²=0.7803
PUSH0, nobs=56023, runtime_ms=5.795e-07, p=1.00e-03, R²=0.7803
STATICCALL, nobs=56023, runtime_ms=8.121e-05, p=1.00e-03, R²=0.7803
Pure glue, reth
ISZERO, nobs=946, runtime_ms=1.733e-06, p=1.00e-03, R²=0.9283
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.928
Model: NNLS Adj. R-squared: 0.928
No. Observations: 946 RMSE: 10.15
Df Residuals: 944 MAE: 7.93
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 17.6447 0.8059 0.001 16.0742 19.3751
ISZERO 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPDEST, nobs=946, runtime_ms=5.286e-07, p=1.00e-03, R²=0.9638
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.964
Model: NNLS Adj. R-squared: 0.964
No. Observations: 946 RMSE: 6.47
Df Residuals: 944 MAE: 5.04
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 5.0375 0.6148 0.001 3.8493 6.3263
JUMPDEST 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SWAP, nobs=15136, runtime_ms=6.168e-07, p=1.00e-03, R²=0.6087
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.609
Model: NNLS Adj. R-squared: 0.609
No. Observations: 15136 RMSE: 10.42
Df Residuals: 15134 MAE: 3.66
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 9.6704 0.3018 0.001 9.0407 10.2491
SWAP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier A), reth
ADD, nobs=946, runtime_ms=1.476e-06, p=1.00e-03, R²=0.9394
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.939
Model: NNLS Adj. R-squared: 0.939
No. Observations: 946 RMSE: 3.95
Df Residuals: 944 MAE: 3.01
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.6471 0.3467 0.001 6.9845 8.3680
ADD 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
AND, nobs=946, runtime_ms=1.415e-06, p=1.00e-03, R²=0.9245
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.925
Model: NNLS Adj. R-squared: 0.924
No. Observations: 946 RMSE: 4.26
Df Residuals: 944 MAE: 3.19
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.3728 0.3879 0.001 5.5896 7.0971
AND 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATACOPY, nobs=22704, runtime_ms=4.241e-06, p=1.00e-03, R²=0.9118
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.912
Model: NNLS Adj. R-squared: 0.912
No. Observations: 22704 RMSE: 9.93
Df Residuals: 22702 MAE: 7.57
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 15.3806 0.0750 0.001 15.2350 15.5306
CALLDATACOPY 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
CALLDATALOAD, nobs=3784, runtime_ms=0, p=1.00e+00, R²=1.11e-16
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.000
Model: NNLS Adj. R-squared: -0.000
No. Observations: 3784 RMSE: 2.89
Df Residuals: 3782 MAE: 2.71
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 4.6479 0.0546 0.001 4.5365 4.7421
CALLDATALOAD 0.0000 0.0000 1.000 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
DIV, nobs=946, runtime_ms=1.067e-05, p=1.00e-03, R²=0.9476
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.948
Model: NNLS Adj. R-squared: 0.948
No. Observations: 946 RMSE: 19.82
Df Residuals: 944 MAE: 15.26
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 32.8339 1.9656 0.001 29.0536 36.6122
DIV 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
EXP, nobs=946, runtime_ms=0.0006835, p=1.00e-03, R²=0.9599
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.960
Model: NNLS Adj. R-squared: 0.960
No. Observations: 946 RMSE: 5.47
Df Residuals: 944 MAE: 4.10
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.3537 0.5200 0.001 6.2666 8.3683
EXP 0.0007 0.0000 0.001 0.0007 0.0007
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
GT, nobs=946, runtime_ms=1.557e-06, p=1.00e-03, R²=0.9486
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.949
Model: NNLS Adj. R-squared: 0.949
No. Observations: 946 RMSE: 3.82
Df Residuals: 944 MAE: 2.89
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.3410 0.3790 0.001 7.5555 9.0444
GT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
JUMPI, nobs=946, runtime_ms=2.255e-06, p=1.00e-03, R²=0.9359
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.936
Model: NNLS Adj. R-squared: 0.936
No. Observations: 946 RMSE: 2.66
Df Residuals: 944 MAE: 2.05
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 6.3590 0.2753 0.001 5.8228 6.9040
JUMPI 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
LT, nobs=946, runtime_ms=3.08e-06, p=1.00e-03, R²=0.6899
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.690
Model: NNLS Adj. R-squared: 0.690
No. Observations: 946 RMSE: 22.41
Df Residuals: 944 MAE: 18.51
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 0.0000 0.3208 1.000 0.0000 1.0370
LT 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE, nobs=4730, runtime_ms=3.655e-06, p=1.00e-03, R²=0.3993
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.399
Model: NNLS Adj. R-squared: 0.399
No. Observations: 4730 RMSE: 31.47
Df Residuals: 4728 MAE: 28.88
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 15.2515 1.3197 0.001 12.7658 17.9468
MSTORE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MSTORE8, nobs=4730, runtime_ms=2.186e-06, p=1.00e-03, R²=0.9256
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.926
Model: NNLS Adj. R-squared: 0.926
No. Observations: 4730 RMSE: 4.35
Df Residuals: 4728 MAE: 2.43
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 8.1771 0.2186 0.001 7.7749 8.6256
MSTORE8 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
MUL, nobs=946, runtime_ms=2.269e-06, p=1.00e-03, R²=0.9441
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.944
Model: NNLS Adj. R-squared: 0.944
No. Observations: 946 RMSE: 4.36
Df Residuals: 944 MAE: 3.22
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.9356 0.4341 0.001 7.1101 8.7794
MUL 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
PC, nobs=946, runtime_ms=9.372e-07, p=1.00e-03, R²=0.6985
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.698
Model: NNLS Adj. R-squared: 0.698
No. Observations: 946 RMSE: 18.42
Df Residuals: 944 MAE: 6.44
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 12.6705 2.1697 0.001 8.9241 17.4679
PC 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
RETURNDATASIZE, nobs=3784, runtime_ms=1.398e-06, p=1.00e-03, R²=0.9506
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.951
Model: NNLS Adj. R-squared: 0.951
No. Observations: 3784 RMSE: 5.03
Df Residuals: 3782 MAE: 3.87
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.2148 0.2424 0.001 6.7305 7.7088
RETURNDATASIZE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SELFBALANCE, nobs=946, runtime_ms=8.157e-06, p=1.00e-03, R²=0.9606
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.961
Model: NNLS Adj. R-squared: 0.961
No. Observations: 946 RMSE: 20.42
Df Residuals: 944 MAE: 14.68
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 25.5432 2.0561 0.001 21.5949 29.6617
SELFBALANCE 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
SUB, nobs=946, runtime_ms=1.577e-06, p=1.00e-03, R²=0.9326
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.933
Model: NNLS Adj. R-squared: 0.932
No. Observations: 946 RMSE: 4.47
Df Residuals: 944 MAE: 3.30
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.5872 0.4474 0.001 6.7499 8.4413
SUB 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
Mixed glue (tier B), reth
JUMP, nobs=946, runtime_ms=4.242e-06, p=1.00e-03, R²=0.9527
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.953
Model: NNLS Adj. R-squared: 0.953
No. Observations: 946 RMSE: 3.51
Df Residuals: 944 MAE: 2.67
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 7.6319 0.3450 0.001 6.9064 8.2729
JUMP 0.0000 0.0000 0.001 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```
KECCAK256, nobs=15136, runtime_ms=0, p=1.00e+00, R²=0
```
==============================================================================
NNLS Regression Results
==============================================================================
Dep. Variable: test_runtime_ms R-squared: 0.000
Model: NNLS Adj. R-squared: -0.000
No. Observations: 15136 RMSE: 297.58
Df Residuals: 15134 MAE: 246.59
Df Model: 1
==============================================================================
coef std err P-value [0.025 0.975]
------------------------------------------------------------------------------
const 437.3304 2.3390 0.001 432.7476 441.9862
KECCAK256 0.0000 0.0000 1.000 0.0000 0.0000
==============================================================================
Notes: Non-negative least squares with bootstrap inference (1000 iterations)
==============================================================================
```