Dissertation/Thesis Abstract

Heterogeneity and Density Aware Design of Computing Systems
by Arora, Manish, Ph.D., University of California, San Diego, 2018, 137; 10788835
Abstract (Summary)

The number of programmable cores that are available in systems continues to increase with advances in device scaling, integration, and iterative improvements. Today, systems are not just integrating more cores, but also integrating a variety of different types of processing cores, resulting in dense heterogeneous systems. However, important questions remain about the design methodology for dense heterogeneous systems. This thesis seeks to address these questions.

One typical methodology for heterogeneous system design is to comprise systems by using parts of homogeneous systems. Another commonly used technique to enable density is replication. However, these design methodologies are “heterogeneous system oblivious” and “density oblivious”. The components of the system are not aware or optimized for the heterogeneous system they would become a part of. Nor are they aware of the existence of other replicated components. This thesis shows that “heterogeneous system oblivious” and “density oblivious” design methodologies result in inefficient systems. This thesis proposes heterogeneity and density aware approaches to designing dense heterogeneous architectures.

Indexing (document details)
Advisor: Tullsen, Dean M.
Commitee: Chen, Renkun, Porter, George, Rosing, Tajana S., Swanson, Steve
School: University of California, San Diego
Department: Computer Science
School Location: United States -- California
Source: DAI-B 79/12(E), Dissertation Abstracts International
Subjects: Computer Engineering, Computer science
Keywords: CPU design, CPU-GPU design, Computer architecture, GPU design, Heterogeneity aware design, Heterogeneous systems
Publication Number: 10788835
ISBN: 9780438167650
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