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Differential Evolution to Reduce Energy Consumption in Three-Level Memory Hierarchy

Authors:

A. G. Silva-Filho,

L. J. C. Nunes,

H. F. LacerdaAuthors Info & Claims

SBCCI '15: Proceedings of the 28th Symposium on Integrated Circuits and Systems Design

Article No.: 39, Pages 1 - 6

https://doi.org/10.1145/2800986.2801005

Published: 31 August 2015 Publication History

Abstract

This paper presents an improved differential evolution (DE) algorithm for multi-objective optimization in the discrete domain, applied to a cache memory hierarchy exploration problem, aiming to reduce the energy consumption and to increase the performance to process an embedded application. The architecture exploration is based on cache parameters adjustments and the memory hierarchy is composed of three levels of cache memory. A model of LPDDR2 memory (Low Power DDR2) was adopted to simulate the main memory and a recent cache memory model based on 32 nm transistor technology was used. In these experiments, the proposed algorithm was applied to nine different applications from the MiBench and the MediaBenchII suites. Furthermore, the performance of the proposed strategy was compared with those of SPEA2 and NSGAII optimization mechanisms. The metrics selected to compare the quality of the Pareto front found for each of those algorithms were the hypervolume and the generational distance. The results show that the proposed strategy based on DE optimization algorithm applied to memory hierarchy exploration problem obtained better results for both indicators, achieving improvements in 100% and 78% of cases in both metrics mentioned respectively.

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Cited By

Vivek YRavi VKrishna P(2022)Scalable feature subset selection for big data using parallel hybrid evolutionary algorithm based wrapper under apache spark environmentCluster Computing10.1007/s10586-022-03725-w26:3(1949-1983)Online publication date: 10-Sep-2022
https://doi.org/10.1007/s10586-022-03725-w
Andrade HRios MLima RLacerda HSilva-Filho ANotare MSun PCoutinho R(2018)Multi-objective Approaches to Improve QoS in Vehicular Ad-hoc NetworksProceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3272036.3272046(41-48)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3272036.3272046

Index Terms

Differential Evolution to Reduce Energy Consumption in Three-Level Memory Hierarchy
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language features

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Information & Contributors

Information

Published In

cover image ACM Conferences

SBCCI '15: Proceedings of the 28th Symposium on Integrated Circuits and Systems Design

August 2015

279 pages

ISBN:9781450337632

DOI:10.1145/2800986

General Chair:
Robson Nunes de Lima
UFBA, Brazil
,
Program Chairs:
Ana Isabela Araújo Cunha
UFBA, Brazil
,
Calvin Plett
Carleton University, Canada
,
Publications Chair:
Wagner Luiz Alves de Oliveira
UFBA, Brazil

Copyright © 2015 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]

Sponsors

SBC: Brazilian Computer Society
SIGDA: ACM Special Interest Group on Design Automation
SBMICRO: Brazilian Microelectronics Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 31 August 2015

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Research-article
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SBCCI '15

Sponsor:

SBC
SIGDA
SBMICRO

SBCCI '15: 28th Symposium on Integrated Circuits and Systems Design

August 31 - September 4, 2015

Salvador, Brazil

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SBCCI '15 Paper Acceptance Rate 43 of 98 submissions, 44%;

Overall Acceptance Rate 133 of 347 submissions, 38%

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Cited By

Vivek YRavi VKrishna P(2022)Scalable feature subset selection for big data using parallel hybrid evolutionary algorithm based wrapper under apache spark environmentCluster Computing10.1007/s10586-022-03725-w26:3(1949-1983)Online publication date: 10-Sep-2022
https://doi.org/10.1007/s10586-022-03725-w
Andrade HRios MLima RLacerda HSilva-Filho ANotare MSun PCoutinho R(2018)Multi-objective Approaches to Improve QoS in Vehicular Ad-hoc NetworksProceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications10.1145/3272036.3272046(41-48)Online publication date: 25-Oct-2018
https://dl.acm.org/doi/10.1145/3272036.3272046

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