Systems-on-Chip with Strong Ordering

Author:

Puthoor Sooraj1,Lipasti Mikko H.2

Affiliation:

1. University of Wisconsin—Madison, AMD Research, Southwest Pkwy, Austin

2. University of Wisconsin—Madison, Madison, WI

Abstract

Sequential consistency (SC) is the most intuitive memory consistency model and the easiest for programmers and hardware designers to reason about. However, the strict memory ordering restrictions imposed by SC make it less attractive from a performance standpoint. Additionally, prior high-performance SC implementations required complex hardware structures to support speculation and recovery. In this article, we introduce the lockstep SC consistency model (LSC), a new memory model based on SC but carefully defined to accommodate the data parallel lockstep execution paradigm of GPUs. We also describe an efficient LSC implementation for an APU system-on-chip (SoC) and show that our implementation performs close to the baseline relaxed model. Evaluation of our implementation shows that the geometric mean performance cost for lockstep SC is just 0.76% for GPU execution and 6.11% for the entire APU SoC compared to a baseline with a weaker memory consistency model. Adoption of LSC in future APU and SoC designs will reduce the burden on programmers trying to write correct parallel programs, while also simplifying the implementation and verification of systems with heterogeneous processing elements and complex memory hierarchies. 1

Funder

AFRL

NSF

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference80 articles.

1. 2017. Inside Volta: The World’s Most Advanced Data Center GPU. Retrieved from https://devblogs.nvidia.com/inside-volta/. 2017. Inside Volta: The World’s Most Advanced Data Center GPU. Retrieved from https://devblogs.nvidia.com/inside-volta/.

2. Shared memory consistency models: a tutorial

3. Weak ordering---a new definition

4. Weak ordering---a new definition

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Turn-based Spatiotemporal Coherence for GPUs;ACM Transactions on Architecture and Code Optimization;2023-07-19

2. EdgeNN: Efficient Neural Network Inference for CPU-GPU Integrated Edge Devices;2023 IEEE 39th International Conference on Data Engineering (ICDE);2023-04

3. Arbitrarily Parallelizable Code: A Model of Computation Evaluated on a Message-Passing Many-Core System;Computers;2022-11-18

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3