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