Supporting dynamic data structures on distributed-memory machines

Author:

Rogers Anne1,Carlisle Martin C.1,Reppy John H.2,Hendren Laurie J.3

Affiliation:

1. Princeton Univ., Princeton, NJ

2. AT&T Bell Labs, Murray Hill, NJ

3. McGill Univ., Montreal, P.Q., Canada

Abstract

Compiling for distributed-memory machines has been a very active research area in recent years. Much of this work has concentrated on programs that use arrays as their primary data structures. To date, little work has been done to address the problem of supporting programs that use pointer-based dynamic data structures. The techniques developed for supporting SPMD execution of array-based programs rely on the fact that arrays are statically defined and directly addressable. Recursive data structures do not have these properties, so new techniques must be developed. In this article, we describe an execution model for supporting programs that use pointer-based dynamic data structures. This model uses a simple mechanism for migrating a thread of control based on the layout of heap-allocated data and introduces parallelism using a technique based on futures and lazy task creation. We intend to exploit this execution model using compiler analyses and automatic parallelization techniques. We have implemented a prototype system, which we call Olden , that runs on the Intel iPSC/860 and the Thinking Machines CM-5. We discuss our implementation and report on experiments with five benchmarks.

Publisher

Association for Computing Machinery (ACM)

Subject

Software

Cited by 124 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. IDaTPA: importance degree based thread partitioning approach in thread level speculation;Discover Computing;2024-06-19

2. Rapid NVM Simulation and Analysis on Single Bit Granularity Featuring Gem5 and NVMain;2023 IEEE 12th Non-Volatile Memory Systems and Applications Symposium (NVMSA);2023-08

3. Fat Pointers for Temporal Memory Safety of C;Proceedings of the ACM on Programming Languages;2023-04-06

4. MetaSys: A Practical Open-source Metadata Management System to Implement and Evaluate Cross-layer Optimizations;ACM Transactions on Architecture and Code Optimization;2022-03-24

5. Memory access scheduling to reduce thread migrations;Proceedings of the 31st ACM SIGPLAN International Conference on Compiler Construction;2022-03-18

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