arrow
Return

ARS: an adaptive runtime system for locality optimization

delete2003-07-01
delete2
PRE
AI
J
Jie Tao
M
Martin Schulz
W
Wolfgang Karl
DOI:10.1016/S0167-739X(02)00183-8delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Shared memory programs running on Non-Uniform Memory Access (NUMA) machines usually face inherent performance problems stemming from excessive remote memory accesses. A solution, called the Adaptive Runtime System (ARS), is presented in this paper. ARS is designed to adjust the data distribution at runtime through automatic page migrations. It uses memory access histograms gathered by hardware monitors to find access hot spots and, based on this detection, to dynamically and transparently modify the data layout. In this way, incorrectly allocated data can be moved to the most appropriate node and hence data locality can be improved. Simulations show that this allows to achieve a performance gain of as high as 40%. (C) 2002 Elsevier Science B.V. All rights reserved.
Keywords:
page migration
data locality optimization
shared memory programming on NUMA
hardware monitor
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

F
Future Generation Computer Systems-The International Journal of eScience
IF:
6.1
Papers:
6.9K
Citations:
2.3W

Organization

No organization information available
Cited Papers

Cited Papers

Prolyl endopeptidase activity in bronchoalveolar lavage fluid: a novel diagnostic biomarker in a guinea pig model of invasive pulmonary aspergillosis
err2013-08-01
err0
errOAAI
errKalyani Jambunathan; Douglas S. Watson; Laura K. Najvar; Nathan P. Wiederhold; William R. Kirkpatrick; Thomas F. Patterson; David S. Askew; Krishna Kodukula; Amit K. Galande
errShare
errSave
Evidence for Layer-Specific Connectional Heterogeneity in the Mouse Auditory Corticocollicular System
err2021-10-20
err0
errOAAI
errGeorgiy Yudintsev; Alexander R. Asilador; Stacy Sons; Nathiya Vaithiyalingam Chandra Sekaran; Macey Coppinger; Kavya Nair; Masumi Prasad; Gang Xiao; Baher A. Ibrahim; Yoshitaka Shinagawa; Daniel A. Llano
errShare
errSave
Pan Traps for Tracking Honey Bee Activity-Density: A Case Study in Soybeans
err2020-06-12
err0
errOAAI
errAshley L. St. Clair; Adam G. Dolezal; Matthew E. O’Neal; Amy L. Toth
errShare
errSave
researcher View more