JOURNAL ARTICLE

Evolutionary Benchmark Subsetting

Zhanpeng JinAllen C. Cheng

Year: 2008 Journal:   IEEE Micro Vol: 28 (6)Pages: 20-36   Publisher: Institute of Electrical and Electronics Engineers

Abstract

To improve simulation efficiency and relieve burdened benchmarking efforts, this research proposes a survival-of-the-fittest evolutionary methodology. The goal is to subset any given benchmark suite based on its inherent workload characteristics, desired workload space coverage, and total execution time. Given a user-specified workload space coverage threshold, the proposed technique can systematically yield the "fittest" time-efficient benchmark subset.

Keywords:
Computer science Benchmark (surveying)

Metrics

3
Cited By
0.24
FWCI (Field Weighted Citation Impact)
36
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Parallel Computing and Optimization Techniques
Physical Sciences →  Computer Science →  Hardware and Architecture
Simulation Techniques and Applications
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Distributed and Parallel Computing Systems
Physical Sciences →  Computer Science →  Computer Networks and Communications
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