arrow
返回

Argobots: A Lightweight Low-Level Threading and Tasking Framework

delete2018-03-01
delete82
delete
OA
AI
S
Sangmin Seo *
A
Abdelhalim Amer
G
George Bosilca
P
Philip Carns
A
Adrián Castelló
D
Damien Genet
T
Thomas Hérault
S
Shintaro Iwasaki
P
Prateek Jindal
L
Laxmikant V. Kalé
S
Sriram Krishnamoorthy
M
Marc Snir
K
Kenjiro Taura
P
Pete Beckman
DOI:10.1109/TPDS.2017.2766062delete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
In the past few decades, a number of user-level threading and tasking models have been proposed in the literature to address the shortcomings of OS-level threads, primarily with respect to cost and flexibility. Current state-of-the-art user-level threading and tasking models, however, either are too specific to applications or architectures or are not as powerful or flexible. In this paper, we present Argobots, a lightweight, low-level threading and tasking framework that is designed as a portable and performant substrate for high-level programming models or runtime systems. Argobots offers a carefully designed execution model that balances generality of functionality with providing a rich set of controls to allow specialization by end users or high-level programming models. We describe the design, implementation, and performance characterization of Argobots and present integrations with three high-level models: OpenMP, MPI, and colocated I/O services. Evaluations show that (1) Argobots, while providing richer capabilities, is competitive with existing simpler generic threading runtimes; (2) our OpenMP runtime offers more efficient interoperability capabilities than production OpenMP runtimes do; (3) when MPI interoperates with Argobots instead of Pthreads, it enjoys reduced synchronization costs and better latency-hiding capabilities; and (4) I/O services with Argobots reduce interference with colocated applications while achieving performance competitive with that of a Pthreads approach.
Keyword:
Argobots
user-level thread
tasklet
OpenMP
MPI
I/O
interoperability
lightweight
context switch
stackable scheduler
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Parallel and Distributed Systems 封面图
IEEE Transactions on Parallel and Distributed Systems
IF:
6
论文数:
5.2K
被引数:
1.1W

机构

U
Universitat Jaume I
学者数:
4.7K
论文数: 4.8K
被引数: 6.1K
P
Pacific Northwest National Laboratory
学者数:
9.0K
论文数: 6.3K
被引数: 14
U
University of Tokyo
学者数:
7.1W
论文数: 6.5W
被引数: 2.2K
A
Argonne National Laboratory
学者数:
1.1W
论文数: 9.2K
被引数: 3.8W
U
University of Illinois Urbana-Champaign
学者数:
2.4W
论文数: 2.0W
被引数: 35
U
University of Tennessee Knoxville
学者数:
1.1W
论文数: 9.4K
被引数: 17
U
united states department of energy (doe)
学者数:
11.3W
论文数: 9.6W
被引数: 246
University of Illinois System 封面图
University of Illinois System
学者数:
6.9W
论文数: 6.2W
被引数: 644
University of Tennessee System 封面图
University of Tennessee System
学者数:
2.9W
论文数: 2.7W
被引数: 115
S
Sandia National Laboratories
学者数:
5.5K
论文数: 3.8K
被引数: 6.4K
学者 查看更多机构
引用论文

引用论文

Prédiction du réveil et détection de la conscience : intérêt des potentiels évoqués cognitifs
err2009-10-01
err0
PREAI
errB. Rohaut; F. Faugeras; T.-A. Bekinschtein; A. Wassouf; N. Chausson; S. Dehaene; L. Naccache
err分享
err收藏
err2000-01-01
err0
PREAI
errT.S. Toellner
err分享
err收藏
err分享
err收藏
err分享
err收藏
An analytical formula for ring artefact suppression in X-ray tomography
err2010-12-01
err0
PREAI
errSofya Titarenko; Philip J. Withers; Anatoly Yagola
err分享
err收藏
Identifying vulnerable brain networks associated with Alzheimer’s disease risk
err2022-11-01
err0
PREAI
errAli Mahzarnia; Jacques A Stout; Robert J Anderson; Hae Sol Moon; Zay Yar Han; Kate Beck; Jeffrey N Browndyke; David B Dunson; Kim G Johnson; Richard J O’Brien; Alexandra Badea
err分享
err收藏
学者 查看更多内容