research-article

Scalable analysis of multicore data reuse and sharing

Authors:

Miquel Pericas,

Satoshi MatsuokaAuthors Info & Claims

ICS '14: Proceedings of the 28th ACM international conference on Supercomputing

Pages 353 - 362

https://doi.org/10.1145/2597652.2597674

Published: 10 June 2014 Publication History

Abstract

The performance and energy efficiency of multicore systems are increasingly dominated by the costs of communication. As hardware parallelism grows, developers require more powerful tools to assess the data sharing and reuse properties of their algorithms. The reuse distance is an effective metric to study the temporal locality of programs and model private and shared caches. But the application of this method is challenging. First, generating memory traces is very expensive in storage and very intrusive on execution, possibly distorting the parallel schedule. And second, the algorithm is computationally very expensive, limiting the length, memory size and parallelism of analyzable programs.

This paper introduces a novel coarse-grained reuse distance method, called Kernel Reuse Distance (KRD), which addresses these challenges. KRD enables a quick assessment of data locality by studying the reuse characteristics of the kernels' inputs and outputs. We analyze the performance of the initial prototype implementation and show two use cases comparing different parallel implementations. On a 24-core system, analyzing a trace from a matrix multiplication representing 24 threads, 1.37 terabytes of streamed data and 800 million distinct accesses, the parallel KRD implementation is able to compute the coherence-aware kernel reuse distance histogram for one socket (six cores) in 11.1 seconds.

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Cited By

Sasongko MChabbi MMarzijarani MUnat D(2022) ReuseTracker : Fast Yet Accurate Multicore Reuse Distance Analyzer ACM Transactions on Architecture and Code Optimization10.1145/348419919:1(1-25)Online publication date: 31-Mar-2022
https://doi.org/10.1145/3484199
Sasongko MChabbi MUnat D(2022)Low-Overhead Reuse Distance Profiling Tool for MulticoreEuro-Par 2021: Parallel Processing Workshops10.1007/978-3-031-06156-1_49(555-559)Online publication date: 9-Jun-2022
https://doi.org/10.1007/978-3-031-06156-1_49
Lezos CDimitroulakos GLatifis IMasselos K(2020)A Locality Optimizer for Loop-dominated Applications Based on Reuse Distance AnalysisACM Transactions on Design Automation of Electronic Systems10.1145/339818925:6(1-26)Online publication date: 2-Sep-2020
https://dl.acm.org/doi/10.1145/3398189
Show More Cited By

Index Terms

Scalable analysis of multicore data reuse and sharing

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Published In

cover image ACM Conferences

ICS '14: Proceedings of the 28th ACM international conference on Supercomputing

June 2014

378 pages

ISBN:9781450326421

DOI:10.1145/2597652

General Chairs:
Arndt Bode
Technische Universität München and Leibniz Rechenzentrum, Germany
,
Michael Gerndt
Technische Universität München, Germany
,
Program Chairs:
Per Stenström
Chalmers University of Technology, Sweden
,
Lawrence Rauchwerger
Texas A&M University, USA
,
Barton Miller
University of Wisconsin, USA
,
Martin Schulz
Lawrence Livermore National Laboratory, USA

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 June 2014

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Japan Society for the Promotion of Science

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ICS'14

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SIGARCH

ICS'14: 2014 International Conference on Supercomputing

June 10 - 13, 2014

Munich, Germany

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ICS '14 Paper Acceptance Rate 34 of 160 submissions, 21%;

Overall Acceptance Rate 629 of 2,180 submissions, 29%

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Cited By

Sasongko MChabbi MMarzijarani MUnat D(2022) ReuseTracker : Fast Yet Accurate Multicore Reuse Distance Analyzer ACM Transactions on Architecture and Code Optimization10.1145/348419919:1(1-25)Online publication date: 31-Mar-2022
https://doi.org/10.1145/3484199
Sasongko MChabbi MUnat D(2022)Low-Overhead Reuse Distance Profiling Tool for MulticoreEuro-Par 2021: Parallel Processing Workshops10.1007/978-3-031-06156-1_49(555-559)Online publication date: 9-Jun-2022
https://doi.org/10.1007/978-3-031-06156-1_49
Lezos CDimitroulakos GLatifis IMasselos K(2020)A Locality Optimizer for Loop-dominated Applications Based on Reuse Distance AnalysisACM Transactions on Design Automation of Electronic Systems10.1145/339818925:6(1-26)Online publication date: 2-Sep-2020
https://dl.acm.org/doi/10.1145/3398189
Manivannan MPericás MPapaefstathiou VStenström P(2018)Global Dead-Block Management for Task-Parallel ProgramsACM Transactions on Architecture and Code Optimization10.1145/323433715:3(1-25)Online publication date: 4-Sep-2018
https://dl.acm.org/doi/10.1145/3234337
Pericàs M(2018)Elastic PlacesACM Transactions on Architecture and Code Optimization10.1145/318545815:2(1-26)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1145/3185458
Manivannan MPericas MPapaefstathiou VStenstrom P(2017)Runtime-Assisted Global Cache Management for Task-Based Parallel ProgramsIEEE Computer Architecture Letters10.1109/LCA.2016.260659316:2(145-148)Online publication date: 1-Jul-2017
https://doi.org/10.1109/LCA.2016.2606593
Zhong ARen SXu S(2017)CDLP: A Core Distributing Policy Based on Logic PartitioningGreen, Pervasive, and Cloud Computing10.1007/978-3-319-57186-7_33(443-459)Online publication date: 13-Apr-2017
https://doi.org/10.1007/978-3-319-57186-7_33

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