Article

Automatically characterizing large scale program behavior

Authors:

Timothy Sherwood,

Brad CalderAuthors Info & Claims

ASPLOS X: Proceedings of the 10th international conference on Architectural support for programming languages and operating systems

Pages 45 - 57

https://doi.org/10.1145/605397.605403

Published: 01 October 2002 Publication History

Abstract

Understanding program behavior is at the foundation of computer architecture and program optimization. Many programs have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ramifications for many architectural and compiler techniques, from thread scheduling, to feedback directed optimizations, to the way programs are simulated. However, in order to take advantage of time-varying behavior, we must first develop the analytical tools necessary to automatically and efficiently analyze program behavior over large sections of execution.Our goal is to develop automatic techniques that are capable of finding and exploiting the Large Scale Behavior of programs (behavior seen over billions of instructions). The first step towards this goal is the development of a hardware independent metric that can concisely summarize the behavior of an arbitrary section of execution in a program. To this end we examine the use of Basic Block Vectors. We quantify the effectiveness of Basic Block Vectors in capturing program behavior across several different architectural metrics, explore the large scale behavior of several programs, and develop a set of algorithms based on clustering capable of analyzing this behavior. We then demonstrate an application of this technology to automatically determine where to simulate for a program to help guide computer architecture research.

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Special Issue: Proceedings of the 10th annual conference on Architectural Support for Programming Languages and Operating Systems

Understanding program behavior is at the foundation of computer architecture and program optimization. Many programs have wildly different behavior on even the very largest of scales (over the complete execution of the program). This realization has ...

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cover image ACM Conferences

ASPLOS X: Proceedings of the 10th international conference on Architectural support for programming languages and operating systems

October 2002

318 pages

ISBN:1581135742

DOI:10.1145/605397

Conference Chair:
Kourosh Gharachorloo
Compaq Western Research Lab
,
Program Chair:
David A. Wood

ACM SIGARCH Computer Architecture News Volume 30, Issue 5
Special Issue: Proceedings of the 10th annual conference on Architectural Support for Programming Languages and Operating Systems
December 2002
296 pages
ISSN:0163-5964
DOI:10.1145/635506
Issue’s Table of Contents
ACM SIGOPS Operating Systems Review Volume 36, Issue 5
December 2002
296 pages
ISSN:0163-5980
DOI:10.1145/635508
Issue’s Table of Contents
ACM SIGPLAN Notices Volume 37, Issue 10
October 2002
296 pages
ISSN:0362-1340
EISSN:1558-1160
DOI:10.1145/605432
Issue’s Table of Contents

Copyright © 2002 ACM.

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Published: 01 October 2002

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ASPLOS02: Tenth International Conference on Architectural Support for Programming Languages and Operating Systems

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https://dl.acm.org/doi/10.1145/3649153.3649202
Zhang YSobotka NPark SJamilan SKhan TKasikci BPokam GLitz HDevietti JTsafrir DMusuvathi MGupta RAbu-Ghazaleh N(2024)RPG2: Robust Profile-Guided Runtime Prefetch GenerationProceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 210.1145/3620665.3640396(999-1013)Online publication date: 27-Apr-2024
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