Relevance and Evolution of Benchmarking in Computer Systems: A Comprehensive Historical and Conceptual Review

Benchmarking has been central to performance evaluation for more than four decades. Reinhold P. Weicker’s 1990 survey in IEEE Computer offered an early, rigorous critique of standard benchmarks, warning about pitfalls that continue to surface in contemporary practice. This review synthesizes the evolution from classical synthetic benchmarks (Whetstone, Dhrystone) and application kernels (LINPACK) to modern suites (SPEC CPU2017), domain-specific metrics (TPC), data-intensive and graph workloads (Graph500), and Artificial Intelligence/Machine Learning (AI/ML) benchmarks (MLPerf, TPCx-AI). We emphasize energy and sustainability (Green500, SPECpower, MLPerf Power), reproducibility (artifacts, environments, rules), and domain-specific representativeness, especially in biomedical and bioinformatics contexts. Building upon Weicker’s methodological cautions, we formulate a concise checklist for fair, multidimensional, reproducible benchmarking and identify open challenges and future directions.

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Publication Details

Journal
Computers
Published
2025-11-26
DOI
https://doi.org/10.3390/computers14120516
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Relevance and Evolution of Benchmarking in Computer Systems: A Comprehensive Historical and Conceptual Review

Isaac Zablah, Antonio J. García‐Loureiro, Lilian Sosa
Computers
Cell Image Analysis Techniques
article

Relevance and Evolution of Benchmarking in Computer Systems: A Comprehensive Historical and Conceptual Review

Isaac Zablah, Antonio J. García‐Loureiro, Lilian Sosa
article en

Abstract

Benchmarking has been central to performance evaluation for more than four decades. Reinhold P. Weicker’s 1990 survey in IEEE Computer offered an early, rigorous critique of standard benchmarks, warning about pitfalls that continue to surface in contemporary practice. This review synthesizes the evolution from classical synthetic benchmarks (Whetstone, Dhrystone) and application kernels (LINPACK) to modern suites (SPEC CPU2017), domain-specific metrics (TPC), data-intensive and graph workloads (Graph500), and Artificial Intelligence/Machine Learning (AI/ML) benchmarks (MLPerf, TPCx-AI). We emphasize energy and sustainability (Green500, SPECpower, MLPerf Power), reproducibility (artifacts, environments, rules), and domain-specific representativeness, especially in biomedical and bioinformatics contexts. Building upon Weicker’s methodological cautions, we formulate a concise checklist for fair, multidimensional, reproducible benchmarking and identify open challenges and future directions.

ComputersVol. 14(12)
Universidade da Coruña (ES), Universidade de Santiago de Compostela (ES), National Autonomous University of Honduras (HN), Universidad Pedagógica Nacional Francisco Morazán (HN)
Fakultet Medicinskih Nauka, Univerziteta U Kragujevcu
Openalex Percentile: Top 75%
Cell Image Analysis Techniques
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Relevance and Evolution of Benchmarking in Computer Systems: A Comprehensive Historical and Conceptual Review — Isaac Zablah, Antonio J. García‐Loureiro, et al. · Computers (2025) | TGRS Research Map | TGRS