Performance Evaluation of SNPs Machine-Learning Workload on Intel® Pentium® Hyper-Threading Architectures

S. Ge, J. Song, C. Lai, E. Li, W. Hu (PRC), and X. Tian (USA)


Thread-level parallelism, OpenMP, hyper-threading, machine learning, performance evaluation, optimization.


This paper analyzes a Pentium 4 hyper-threading processor and a Pentium 4 hyper-threading processor on 90nm technology with a machine learning workload parallelized with OpenMP* and Intel compiler. The focus is to understand SNPs performance and the underlying reasons behind that performance. The particular attention is paid to micro-architecture metrics and comparison to examine and evaluate, where appropriate, how those two types of processors perform relative to expectation on SNP machine learning workloads. Results include parallel speedup, micro-architecture metrics comparison.

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