A comparison of HEP code with SPEC<sup>1</sup>benchmarks on multi-core worker nodes
Bibliographic record
Abstract
The SPEC[1] CINT benchmark has been used as a performance reference for computing in the HEP community for the past 20 years. The SPECint_base2000 (SI2K) unit of performance has been used by the major HEP experiments both in the Computing Technical Design Report for the LHC experiments and in the evaluation of the Computing Centres. At recent HEPiX[3] meetings several HEP sites have reported disagreements between actual machine performances and the scores reported by SPEC. Our group performed a detailed comparison of Simulation and Reconstruction code performances from the four LHC experiments in order to find a successor to the SI2K benchmark. We analyzed the new benchmarks from SPEC CPU2006 suite, both integer and floating point, in order to find the best agreement with the HEP code behaviour, with particular attention paid to reproducing the actual environment of HEP farm i.e., each job running independently on each core, and matching compiler, optimization, percentage of integer and floating point operations, and ease of use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".