Paper Info
Title
Volume Driven Data Distribution for NUMA-Machines
Abstract
Highly scalable parallel computers, e.g. SCI-coupled workstation clusters, are NUMA architectures. Thus good static locality is essential for high performance and scalability of parallel programs on these machines. This paper describes novel techniques to optimize static locality at compilation time by application of data transformations and data distributions. The metric which guides the optimizations employs Ehrhart polynomials and allows to calculate the amount of static locality precisely. The effectiveness of our novel techniques has been confirmed by experiments conducted on the SCI-coupled workstation cluster of the PC2 at the University of Paderborn.
Year
DOI
Venue
2000
10.1007/3-540-44520-X_53
Euro-Par
Keywords
Field
DocType
novel technique,static locality,scalable parallel computer,volume driven data distribution,sci-coupled workstation cluster,numa architecture,ehrhart polynomial,good static locality,data transformation,data distribution,parallel program,parallel computer
Data processing,Locality,Data transformation (statistics),Polynomial,Computer science,Parallel computing,Workstation,Convex polytope,Multigrid method,Distributed computing,Scalability
Conference
Volume
ISSN
ISBN
1900
0302-9743
3-540-67956-1
Citations 
PageRank 
References 
4
0.47
7
Authors
2
Name
Order
Citations
PageRank
Felix Heine1185.24
Adrian Slowik2394.03