Performance Measurement and Analysis of Large-Scale Parallel Applications on Leadership Computing Systems
Author(s) -
Brian J. N. Wylie,
Markus Geimer,
Felix Wolf
Publication year - 2008
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2008/632685
Subject(s) - supercomputer , computer science , benchmark (surveying) , scalability , variety (cybernetics) , parallel computing , distributed computing , solver , scale (ratio) , computational science , multigrid method , computer architecture , computer engineering , operating system , artificial intelligence , physics , geodesy , quantum mechanics , partial differential equation , programming language , geography
Developers of applications with large-scale computing requirements are currently presented with a variety of high-performance systems optimised for message-passing, however, effectively exploiting the available computing resources remains a major challenge. In addition to fundamental application scalability characteristics, application and system peculiarities often only manifest at extreme scales, requiring highly scalable performance measurement and analysis tools that are convenient to incorporate in application development and tuning activities. We present our experiences with a multigrid solver benchmark and state-of-the-art real-world applications for numerical weather prediction and computational fluid dynamics, on three quite different multi-thousand-processor supercomputer systems – Cray XT3/4, MareNostrum & Blue Gene/L – using the newly-developed SCALASCA toolset to quantify and isolate a range of significant performance issues.
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