Performance characteristics of openMP constructs, and application benchmarks on a large symmetric multiprocessor
Bibliographic record
Abstract
With the increasing popularity of small to large-scale symmetric multiprocessor (SMP) systems, there has been a dire need to have sophisticated, and flexible development and runtime environments for efficient and rapid development of parallel applications. To this end, OpenMP has emerged as the standard for parallel programming on shared-memory systems. It is very important to evaluate the performance of OpenMP constructs, kernels, and application benchmarks on large-scale SMP systems. We present the performance of the basic OpenMP constructs, class B of NAS OpenMP 3.0 benchmarks, and the SPEC OMPL2001 application benchmarks (large data set) on a contemporary 72-node Sun Fire 15K SMP node. We report the basic timings, scalability, and runtime profiles of different parallel regions within each benchmark in the NAS OpenMP 3.0, and the SPEC OMPL-2001 suites. We elaborate on the performance differences between the medium and large classes of the SPEC OMP2001 suites on our system, as well as a comparison among a number of large-scale symmetric multiprocessors for the SPEC OMPL2001.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".