Reducing the Impact of Intensive Dynamic Memory Allocations in Parallel Multi-Threaded Programs

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00335669" target="_blank" >RIV/68407700:21240/20:00335669 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/TPDS.2019.2960514" target="_blank" >https://doi.org/10.1109/TPDS.2019.2960514</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TPDS.2019.2960514" target="_blank" >10.1109/TPDS.2019.2960514</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Reducing the Impact of Intensive Dynamic Memory Allocations in Parallel Multi-Threaded Programs

Popis výsledku v původním jazyce

Frequent dynamic memory allocations (DyMAs) can significantly hinder the scalability of parallel multi-threaded programs. As the number of threads grows, DyMAs can even become the main performance bottleneck. We introduce modern tools and methods for evaluating the impact of DyMAs and present techniques for its reduction, which include scalable heap implementations, small buffer optimization, and memory pooling. Additionally, we provide a survey of state-of-the-art implementations of these techniques and study them experimentally by using a benchmark program, server simulator software, and a real-world high-performance computing application. As a result, we show that relatively small modifications in parallel program’s source code or a way of its execution may substantially reduce the runtime overhead associated with the use of dynamic data structures.

Název v anglickém jazyce

Reducing the Impact of Intensive Dynamic Memory Allocations in Parallel Multi-Threaded Programs

Popis výsledku anglicky

Frequent dynamic memory allocations (DyMAs) can significantly hinder the scalability of parallel multi-threaded programs. As the number of threads grows, DyMAs can even become the main performance bottleneck. We introduce modern tools and methods for evaluating the impact of DyMAs and present techniques for its reduction, which include scalable heap implementations, small buffer optimization, and memory pooling. Additionally, we provide a survey of state-of-the-art implementations of these techniques and study them experimentally by using a benchmark program, server simulator software, and a real-world high-performance computing application. As a result, we show that relatively small modifications in parallel program’s source code or a way of its execution may substantially reduce the runtime overhead associated with the use of dynamic data structures.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Výzkumné centrum informatiky</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Parallel and Distributed Systems

ISSN

1045-9219

e-ISSN

1558-2183

Svazek periodika

31

Číslo periodika v rámci svazku

5

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

13

Strana od-do

1152-1164

Kód UT WoS článku

000526526100011

EID výsledku v databázi Scopus

2-s2.0-85078422513