Toward Well-Provenanced Computer System Benchmarking: An Update

Technical Report · Thu Sep 23 04:00:00 EDT 2021

DOI:https://doi.org/10.2172/1822697· OSTI ID:1822697

Gutierrez, Samuel Keith ^[1]; Pritchard, Jr., Howard Porter ^[1]

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1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

This report provides an update on the current design, implementation, and usage of bueno, a Python framework enabled by container technology that supports gradations of reproducibility for wellprovenanced benchmarking of sequential and parallel programs. The ultimate goal of the bueno project is to provide convenient access to mechanisms that aid in the automated generation, collection, and dissemination of data relevant for experimental reproducibility in computer system benchmarking.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE Office of Science (SC); USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: 89233218CNA000001
• OSTI ID: 1822697
• Report Number(s): LA-UR-21-29427
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING
computer science