DocumentCode :
625592
Title :
Virtual Systolic Array for QR Decomposition
Author :
Kurzak, Jakub ; Luszczek, Piotr ; Gates, Mark ; Yamazaki, Ichitaro ; Dongarra, Jack
Author_Institution :
Univ. of Tennessee, Knoxville, TN, USA
fYear :
2013
fDate :
20-24 May 2013
Firstpage :
251
Lastpage :
260
Abstract :
Systolic arrays offer a very attractive, data-centric, execution model as an alternative to the von Neumann architecture. Hardware implementations of systolic arrays turned out not to be viable solutions in the past. This article shows how the systolic design principles can be applied to a software solution to deliver an algorithm with unprecedented strong scaling capabilities. Systolic array for the QR decomposition is developed and a virtualization layer is used for mapping of the algorithm to a large distributed memory system. Strong scaling properties are discovered, superior to existing solutions.
Keywords :
data flow computing; distributed memory systems; mathematics computing; matrix decomposition; parallel algorithms; systolic arrays; QR decomposition; data-centric execution model; distributed memory system; hardware implementation; software solution; strong scaling capabilities; systolic design principles; virtual systolic array; virtualization layer; Arrays; Hardware; Kernel; Program processors; Tiles; QR decomposition; dataflow programming; message passing; multi-core; roofline model; systolic array;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on
Conference_Location :
Boston, MA
ISSN :
1530-2075
Print_ISBN :
978-1-4673-6066-1
Type :
conf
DOI :
10.1109/IPDPS.2013.119
Filename :
6569816
Link To Document :
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