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Main Authors: Risco-Martín, José L., Colmenar, J. Manuel, Hidalgo, J. Ignacio, Lanchares, Juan, Díaz, Josefa
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.04414
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author Risco-Martín, José L.
Colmenar, J. Manuel
Hidalgo, J. Ignacio
Lanchares, Juan
Díaz, Josefa
author_facet Risco-Martín, José L.
Colmenar, J. Manuel
Hidalgo, J. Ignacio
Lanchares, Juan
Díaz, Josefa
contents Modern consumer devices must execute multimedia applications that exhibit high resource utilization. In order to efficiently execute these applications, the dynamic memory subsystem needs to be optimized. This complex task can be tackled in two complementary ways: optimizing the application source code or designing custom dynamic memory management mechanisms. Currently, the first approach has been well established, and several automatic methodologies have been proposed. Regarding the second approach, software engineers often write custom dynamic memory managers from scratch, which is a difficult and error-prone work. This paper presents a novel way to automatically generate custom dynamic memory managers optimizing both performance and memory usage of the target application. The design space is pruned using grammatical evolution converging to the best dynamic memory manager implementation for the target application. Our methodology achieves important improvements (62.55\% and 30.62\% better on average in performance and memory usage, respectively) when its results are compared to five different general-purpose dynamic memory managers.
format Preprint
id arxiv_https___arxiv_org_abs_2403_04414
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A methodology to automatically optimize dynamic memory managers applying grammatical evolution
Risco-Martín, José L.
Colmenar, J. Manuel
Hidalgo, J. Ignacio
Lanchares, Juan
Díaz, Josefa
Hardware Architecture
Modern consumer devices must execute multimedia applications that exhibit high resource utilization. In order to efficiently execute these applications, the dynamic memory subsystem needs to be optimized. This complex task can be tackled in two complementary ways: optimizing the application source code or designing custom dynamic memory management mechanisms. Currently, the first approach has been well established, and several automatic methodologies have been proposed. Regarding the second approach, software engineers often write custom dynamic memory managers from scratch, which is a difficult and error-prone work. This paper presents a novel way to automatically generate custom dynamic memory managers optimizing both performance and memory usage of the target application. The design space is pruned using grammatical evolution converging to the best dynamic memory manager implementation for the target application. Our methodology achieves important improvements (62.55\% and 30.62\% better on average in performance and memory usage, respectively) when its results are compared to five different general-purpose dynamic memory managers.
title A methodology to automatically optimize dynamic memory managers applying grammatical evolution
topic Hardware Architecture
url https://arxiv.org/abs/2403.04414