MATE: toward scalable automated and dynamic performance tuning environment
PARA'10 Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume 2
An online service-oriented performance profiling tool for cloud computing systems
Frontiers of Computer Science: Selected Publications from Chinese Universities
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High-performance computing systems continue to employ more and more processor cores. Current typical high-end machines in industry, university, and government research laboratory computing centers feature thousands of computing cores. While these machines promise ever more compute power and memory capacity to tackle today's complex simulation problems, they force application developers to greatly enhance the scalability of their codes to be able to exploit it. To better support them in their porting and tuning process, many parallel-tools research groups have already started to work on scaling their methods, techniques, and tools to extreme processor counts. In this paper, we survey existing profiling and tracing tools, report on our experience in using them in extreme scaling environments, review working and promising new methods and techniques, and discuss strategies for solving open issues and problems. Copyright © 2010 John Wiley & Sons, Ltd.