short-paper

Evaluating GPGPU Memory Performance Through the C-AMAT Model

Authors:

Shuaiwen Leon SongAuthors Info & Claims

MCHPC'17: Proceedings of the Workshop on Memory Centric Programming for HPC

Pages 35 - 39

https://doi.org/10.1145/3145617.3158214

Published: 12 November 2017 Publication History

Abstract

General Purpose Graphics Processing Units (GPGPU) have become a popular platform to accelerate high performance applications. Although they provide exceptional computing power, GPGPU impose significant pressure on the off-chip memory system. Evaluating, understanding, and improving GPGPU data access delay has become an important research topic in high-performance computing. In this study, we utilize the newly proposed GPGPU/C-AMAT (Concurrent Average Memory Access Time) model to quantitatively evaluate GPGPU memory performance. Specifically, we extend the current C-AMAT model to include a GPGPU-specific modeling component and then provide its evaluation results.

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Cited By

Sun XLu X(2023)The Memory-Bounded Speedup Model and Its Impacts in ComputingJournal of Computer Science and Technology10.1007/s11390-022-2911-138:1(64-79)Online publication date: 31-Jan-2023
https://doi.org/10.1007/s11390-022-2911-1
Liu JEspina PSun X(2021)A Study on Modeling and Optimization of Memory SystemsJournal of Computer Science and Technology10.1007/s11390-021-0771-836:1(71-89)Online publication date: 30-Jan-2021
https://doi.org/10.1007/s11390-021-0771-8
Sun XZhang NToonen BAllcock B(2020)Performance Modeling and Evaluation of a Production Disaggregated Memory SystemProceedings of the International Symposium on Memory Systems10.1145/3422575.3422795(223-232)Online publication date: 28-Sep-2020
https://dl.acm.org/doi/10.1145/3422575.3422795
Show More Cited By

Index Terms

Evaluating GPGPU Memory Performance Through the C-AMAT Model
1. Computer systems organization
  1. Architectures
    1. Parallel architectures
      1. Single instruction, multiple data

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cover image ACM Conferences

MCHPC'17: Proceedings of the Workshop on Memory Centric Programming for HPC

November 2017

43 pages

ISBN:9781450351317

DOI:10.1145/3145617

Copyright © 2017 ACM.

© 2017 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of the United States government. As such, the United States Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Publication History

Published: 12 November 2017

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SC '17

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SIGHPC

SC '17: The International Conference for High Performance Computing, Networking, Storage and Analysis

November 12 - 17, 2017

CO, Denver, USA

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Cited By

Sun XLu X(2023)The Memory-Bounded Speedup Model and Its Impacts in ComputingJournal of Computer Science and Technology10.1007/s11390-022-2911-138:1(64-79)Online publication date: 31-Jan-2023
https://doi.org/10.1007/s11390-022-2911-1
Liu JEspina PSun X(2021)A Study on Modeling and Optimization of Memory SystemsJournal of Computer Science and Technology10.1007/s11390-021-0771-836:1(71-89)Online publication date: 30-Jan-2021
https://doi.org/10.1007/s11390-021-0771-8
Sun XZhang NToonen BAllcock B(2020)Performance Modeling and Evaluation of a Production Disaggregated Memory SystemProceedings of the International Symposium on Memory Systems10.1145/3422575.3422795(223-232)Online publication date: 28-Sep-2020
https://dl.acm.org/doi/10.1145/3422575.3422795
Yu QHuang LQian CMa JWang Z(2018)FC-AMATInnovations in Systems and Software Engineering10.1007/s11334-018-0313-x14:2(143-156)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s11334-018-0313-x

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