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Regular Paper

A Study on Modeling and Optimization of Memory Systems

School of Computing and Information Sciences, Florida International University, Miami, FL 33199, U.S.A.
Department of Computer Science, Illinois Institute of Technology, Chicago, IL 60616, U.S.A
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Abstract

Accesses Per Cycle (APC), Concurrent Average Memory Access Time (C-AMAT), and Layered Performance Matching (LPM) are three memory performance models that consider both data locality and memory assess concurrency. The APC model measures the throughput of a memory architecture and therefore reflects the quality of service (QoS) of a memory system. The C-AMAT model provides a recursive expression for the memory access delay and therefore can be used for identifying the potential bottlenecks in a memory hierarchy. The LPM method transforms a global memory system optimization into localized optimizations at each memory layer by matching the data access demands of the applications with the underlying memory system design. These three models have been proposed separately through prior efforts. This paper reexamines the three models under one coherent mathematical framework. More specifically, we present a new memory- centric view of data accesses. We divide the memory cycles at each memory layer into four distinct categories and use them to recursively define the memory access latency and concurrency along the memory hierarchy. This new perspective offers new insights with a clear formulation of the memory performance considering both locality and concurrency. Consequently, the performance model can be easily understood and applied in engineering practices. As such, the memory-centric approach helps establish a unified mathematical foundation for model-driven performance analysis and optimization of contemporary and future memory systems.

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Journal of Computer Science and Technology
Pages 71-89

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Cite this article:
Liu J, Espina P, Sun X-H. A Study on Modeling and Optimization of Memory Systems. Journal of Computer Science and Technology, 2021, 36(1): 71-89. https://doi.org/10.1007/s11390-021-0771-8

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Received: 02 July 2020
Accepted: 19 November 2020
Published: 05 January 2021
© Institute of Computing Technology, Chinese Academy of Sciences 2021