DocumentCode
2484412
Title
Scaling communication-intensive applications on BlueGene/P using one-sided communication and overlap
Author
Nishtala, Rajesh ; Hargrove, Paul H. ; Bonachea, Dan O. ; Yelick, Katherine A.
Author_Institution
Comput. Sci. Div., Univ. of California at Berkeley, Berkeley, CA, USA
fYear
2009
fDate
23-29 May 2009
Firstpage
1
Lastpage
12
Abstract
In earlier work, we showed that the one-sided communication model found in PGAS languages (such as UPC) offers significant advantages in communication efficiency by decoupling data transfer from processor synchronization. We explore the use of the PGAS model on IBM BlueGene/P, an architecture that combines low-power, quad-core processors with extreme scalability. We demonstrate that the PGAS model, using a new port of the Berkeley UPC compiler and GASNet one-sided communication layer, outperforms two-sided (MPI) communication in both microbenchmarks and a case study of the communication-limited benchmark, NAS FT. We scale the benchmark up to 16, 384 cores of the BlueGene/P and demonstrate that UPC consistently outperforms MPI by as much as 66% for some processor configurations and an average of 32%. In addition, the results demonstrate the scalability of the PGAS model and the Berkeley implementation of UPC, the viability of using it on machines with multicore nodes, and the effectiveness of the BG/P communication layer for supporting one-sided communication and PGAS languages.
Keywords
high level languages; multiprocessing systems; BlueGene/P; Partitioned Global Address Space languages; communication efficiency; data transfer; one-sided communication layer; one-sided communication model; processor configuration; processor synchronization; quad-core processors; scaling communication-intensive application; Application software; Computer science; Electronics packaging; High performance computing; Large-scale systems; Parallel processing; Power system modeling; Read-write memory; Scalability; Yarn;
fLanguage
English
Publisher
ieee
Conference_Titel
Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on
Conference_Location
Rome
ISSN
1530-2075
Print_ISBN
978-1-4244-3751-1
Electronic_ISBN
1530-2075
Type
conf
DOI
10.1109/IPDPS.2009.5161076
Filename
5161076
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