An Integrated Vector-Scalar Design on an In-Order ARM Core

Author:

Stanic Milan1,Palomar Oscar2,Hayes Timothy2,Ratkovic Ivan2,Cristal Adrian2,Unsal Osman2,Valero Mateo1

Affiliation:

1. Barcelona Supercomputing Center, Veldhoven, Netherlands

2. Barcelona Supercomputing Center

Abstract

In the low-end mobile processor market, power, energy, and area budgets are significantly lower than in the server/desktop/laptop/high-end mobile markets. It has been shown that vector processors are a highly energy-efficient way to increase performance; however, adding support for them incurs area and power overheads that would not be acceptable for low-end mobile processors. In this work, we propose an integrated vector-scalar design for the ARM architecture that mostly reuses scalar hardware to support the execution of vector instructions. The key element of the design is our proposed block-based model of execution that groups vector computational instructions together to execute them in a coordinated manner. We implemented a classic vector unit and compare its results against our integrated design. Our integrated design improves the performance (more than 6×) and energy consumption (up to 5×) of a scalar in-order core with negligible area overhead (only 4.7% when using a vector register with 32 elements). In contrast, the area overhead of the classic vector unit can be significant (around 44%) if a dedicated vector floating-point unit is incorporated. Our block-based vector execution outperforms the classic vector unit for all kernels with floating-point data and also consumes less energy. We also complement the integrated design with three energy/performance-efficient techniques that further reduce power and increase performance. The first proposal covers the design and implementation of chaining logic that is optimized to work with the cache hierarchy through vector memory instructions, the second proposal reduces the number of reads/writes from/to the vector register file, and the third idea optimizes complex memory access patterns with the memory shape instruction and unified indexed vector load.

Funder

RoMoL ERC Advanced

Royal Society Newton International Fellowship

Management of University and Research Grants

European Union

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Reference38 articles.

1. Krste Asanovic. May 1998. Vector Microprocessors. Ph.D. Dissertation. University of California Berkeley. Krste Asanovic. May 1998. Vector Microprocessors. Ph.D. Dissertation. University of California Berkeley.

2. Christopher Francis Batten. 2010. Simplified Vector-Thread Architectures for Flexible and Efficient Data-parallel Accelerators. Ph.D. Dissertation. Cambridge MA. Advisor(s) Asanovic Krste. Christopher Francis Batten. 2010. Simplified Vector-Thread Architectures for Flexible and Efficient Data-parallel Accelerators. Ph.D. Dissertation. Cambridge MA. Advisor(s) Asanovic Krste.

3. The gem5 simulator

Cited by 5 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. PUMICE: Processing-using-Memory Integration with a Scalar Pipeline for Symbiotic Execution;2023 60th ACM/IEEE Design Automation Conference (DAC);2023-07-09

2. Introduction to Control Flow;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2021

3. Supporting Irregularity in Throughput-Oriented Computing by SIMT-SIMD Integration;2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3);2020-11

4. Associations of weekday-to-weekend sleep differences with academic performance and health-related outcomes in school-age children and youths;Sleep Medicine Reviews;2019-08

5. Enabling SIMT Execution Model on Homogeneous Multi-Core System;ACM Transactions on Architecture and Code Optimization;2018-03-31

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