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
Link To Document :
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