research-article

Heterogeneous system coherence for integrated CPU-GPU systems

Authors:

Arkaprava Basu,

Sooraj Puthoor,

Bradford M. Beckmann,

Steven K. Reinhardt,

David A. WoodAuthors Info & Claims

MICRO-46: Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture

Pages 457 - 467

https://doi.org/10.1145/2540708.2540747

Published: 07 December 2013 Publication History

Abstract

Many future heterogeneous systems will integrate CPUs and GPUs physically on a single chip and logically connect them via shared memory to avoid explicit data copying. Making this shared memory coherent facilitates programming and fine-grained sharing, but throughput-oriented GPUs can overwhelm CPUs with coherence requests not well-filtered by caches. Meanwhile, region coherence has been proposed for CPU-only systems to reduce snoop bandwidth by obtaining coherence permissions for large regions.

This paper develops Heterogeneous System Coherence (HSC) for CPU-GPU systems to mitigate the coherence bandwidth effects of GPU memory requests. HSC replaces a standard directory with a region directory and adds a region buffer to the L2 cache. These structures allow the system to move bandwidth from the coherence network to the high-bandwidth direct-access bus without sacrificing coherence.

Evaluation results with a subset of Rodinia benchmarks and the AMD APP SDK show that HSC can improve performance compared to a conventional directory protocol by an average of more than 2x and a maximum of more than 4.5x. Additionally, HSC reduces the bandwidth to the directory by an average of 94% and by more than 99% for four of the analyzed benchmarks.

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Cited By

Liu JEgawa RTakahashi KShimomura YTakizawa H(2024)Reuse distance-based shared LLC management mechanism for heterogeneous CPU-GPU systemsIEICE Electronics Express10.1587/elex.21.2023052021:4(20230520-20230520)Online publication date: 25-Feb-2024
https://doi.org/10.1587/elex.21.20230520
Ren WLiang Z(2024)Review on GPU accelerated methods for genome-wide SNP-SNP interactionsMolecular Genetics and Genomics10.1007/s00438-024-02214-6300:1Online publication date: 29-Dec-2024
https://doi.org/10.1007/s00438-024-02214-6
Fang JLin SYang HXu YSu X(2023)A perceptual and predictive batch-processing memory scheduling strategy for a CPU-GPU heterogeneous systemCPU-GPU异构系统感知和预测的批处理内存调度策略Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.220044924:7(994-1006)Online publication date: 28-Jul-2023
https://doi.org/10.1631/FITEE.2200449
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Index Terms

Heterogeneous system coherence for integrated CPU-GPU systems
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Heterogeneous (hybrid) systems
2. Hardware
  1. Integrated circuits
    1. Semiconductor memory
      1. Dynamic memory

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cover image ACM Conferences

MICRO-46: Proceedings of the 46th Annual IEEE/ACM International Symposium on Microarchitecture

December 2013

498 pages

ISBN:9781450326384

DOI:10.1145/2540708

General Chair:
Matthew Farrens
UC Davis
,
Program Chair:
Christos Kozyrakis
Stanford University

Copyright © 2013 ACM.

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Published: 07 December 2013

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MICRO-46: The 46th Annual IEEE/ACM International Symposium on Microarchitecture

December 7 - 11, 2013

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Overall Acceptance Rate 484 of 2,242 submissions, 22%

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https://doi.org/10.1587/elex.21.20230520
Ren WLiang Z(2024)Review on GPU accelerated methods for genome-wide SNP-SNP interactionsMolecular Genetics and Genomics10.1007/s00438-024-02214-6300:1Online publication date: 29-Dec-2024
https://doi.org/10.1007/s00438-024-02214-6
Fang JLin SYang HXu YSu X(2023)A perceptual and predictive batch-processing memory scheduling strategy for a CPU-GPU heterogeneous systemCPU-GPU异构系统感知和预测的批处理内存调度策略Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.220044924:7(994-1006)Online publication date: 28-Jul-2023
https://doi.org/10.1631/FITEE.2200449
Puthoor SLipasti M(2023)Turn-based Spatiotemporal Coherence for GPUsACM Transactions on Architecture and Code Optimization10.1145/359305420:3(1-27)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3593054
Muthukrishnan HLustig DVilla OWenisch TNellans D(2023)FinePack: Transparently Improving the Efficiency of Fine-Grained Transfers in Multi-GPU Systems2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)10.1109/HPCA56546.2023.10070949(516-529)Online publication date: Feb-2023
https://doi.org/10.1109/HPCA56546.2023.10070949
Li WCheng HLu ZLu YLiu W(2023)HASpMV: Heterogeneity-Aware Sparse Matrix-Vector Multiplication on Modern Asymmetric Multicore Processors2023 IEEE International Conference on Cluster Computing (CLUSTER)10.1109/CLUSTER52292.2023.00025(209-220)Online publication date: 31-Oct-2023
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Masola ACapodieci N(2023)Optimization strategies for GPUs: an overview of architectural approachesInternational Journal of Parallel, Emergent and Distributed Systems10.1080/17445760.2023.217375238:2(140-154)Online publication date: 5-Feb-2023
https://doi.org/10.1080/17445760.2023.2173752
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Nagarajan VSorin DHill MWood DNagarajan VSorin DHill MWood D(2022)Consistency and Coherence for Heterogeneous SystemsA Primer on Memory Consistency and Cache Coherence10.1007/978-3-031-01764-3_10(211-251)Online publication date: 28-Mar-2022
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Michalke AGrulich PLutz CZeuch SMarkl V(2021)An Energy-Efficient Stream Join for the Internet of ThingsProceedings of the 17th International Workshop on Data Management on New Hardware10.1145/3465998.3466005(1-6)Online publication date: 20-Jun-2021
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