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iLORE: Discovering a Lineage of Microprocessors

Researchers, benchmarking organizations, and hardware manufacturers maintain repositories of computer component and performance information. However, this data is split across many isolated sources and is stored in a form that is not conducive to analysis. A centralized repository of said data would arm stakeholders across industry and academia with a tool to more quantitatively understand the history of computing. We propose iLORE, a data model designed to represent intricate relationships between computer system benchmarks and computer components. We detail the methods we used to implement and populate the iLORE data model using data harvested from publicly available sources. Finally, we demonstrate the validity and utility of our iLORE implementation through an analysis of the characteristics and lineage of commercial microprocessors. We encourage the research community to interact with our data and visualizations at csgenome.org. / Master of Science / Researchers, benchmarking organizations, and hardware manufacturers maintain repositories of computer component and performance information. However, this data is split across many isolated sources and is stored in a form that is not conducive to analysis. A centralized repository of said data would arm stakeholders across industry and academia with a tool to more quantitatively understand the history of computing. We propose iLORE, a data model designed to represent intricate relationships between computer system benchmarks and computer components. We detail the methods we used to implement and populate the iLORE data model using data harvested from publicly available sources. Finally, we demonstrate the validity and utility of our iLORE implementation through an analysis of the characteristics and lineage of commercial microprocessors. We encourage the research community to interact with our data and visualizations at csgenome.org.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/104071
Date29 June 2021
CreatorsFurman, Samuel Lewis
ContributorsComputer Science, Cameron, Kirk W., Back, Godmar V., Ellis, Margaret O.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeThesis
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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