DocumentCode
2481504
Title
Smart read/write for MPI-IO
Author
Sehrish, Saba ; Wang, Jun
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
fYear
2009
fDate
23-29 May 2009
Firstpage
1
Lastpage
8
Abstract
We present a case for automating the selection of MPI-IO performance optimizations, with an ultimate goal to relieve the application programmer from these details, thereby improving their productivity. Programmers productivity has always been overlooked as compared to the performance optimizations in high performance computing community. In this paper we present RFSA, a reduced function set abstraction based on an existing parallel programming interface (MPI-IO) for I/O. MPI-IO provides high performance I/O function calls to the scientists/engineers writing parallel programs; who are required to use the most appropriate optimization of a specific function, hence limits the programmer productivity. Therefore, we propose a set of reduced functions with an automatic selection algorithm to decide what specific MPI-IO function to use. We implement a selection algorithm for I/O functions like read, write, etc. RFSA replaces 6 different flavors of read and write functions by one read and write function. By running different parallel I/O benchmarks on both medium-scale clusters and NERSC supercomputers, we show that RFSA functions impose minimal performance penalties.
Keywords
application program interfaces; message passing; MPI-IO; NERSC supercomputers; RFSA functions; automatic selection algorithm; parallel programming interface; performance optimization; reduced function set abstraction; smart read; smart write; Application software; Clustering algorithms; Computer science; High performance computing; Optimization; Parallel programming; Productivity; Programming profession; Supercomputers; Writing;
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.2009.5160934
Filename
5160934
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