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Record W2158716966 · doi:10.1109/ipdps.2007.370682

A Comprehensive Analysis of OpenMP Applications on Dual-Core Intel Xeon SMPs

2007· article· en· W2158716966 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsXeonComputer scienceXeon PhiMulti-core processorBenchmark (surveying)SuiteParallel computingMultithreadingSpeedupBottleneckComputer architectureDual (grammatical number)Operating systemSoftwareShared memoryEmbedded system

Abstract

fetched live from OpenAlex

Hybrid chip multithreaded SMPs present new challenges as well as new opportunities to maximize performance. Our intention is to discover the optimal operating configuration of such systems for scientific applications and to identify the shared resources that might become a bottleneck to performance under the different hardware configurations. This knowledge will be useful to the research community in developing software techniques to improve the performance of shared memory programs on modern multi-core multiprocessors. In this paper, we study a two-way dual-core Hyper-Threaded (HT) Intel Xeon SMP server under single program and multi-program multithreaded workloads using the NAS OpenMP benchmark suite. Our performance results indicate that in the single-program case, the CMP-based SMP and CMT-based SMP configurations have the highest average speedup across all of the applications. The most efficient architecture is a single HT-enabled dual-core processor that is almost comparable to the performance of a 2-way dual-core HT-disabled system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.040
GPT teacher head0.325
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it