Continuous Performance Monitoring for Large-Scale Parallel Applications

Traditional performance analysis techniques are performed after a parallel program has completed. In this paper, we describe an online method for continuously monitoring the performance of a parallel program, specifically the fraction of the time spent in various activities as the program executes. Our implementation of both a visualization client and the parallel performance framework that gathers utilization data are described. The data gathering uses a scalable and asynchronous reduction with an appropriate lossless compressed data format. The overheads in the initial system are low, even when run on thousands of processors. The data gathering occurs in an out-of-band communication mechanism, interleaving itself transparently with the execution of the parallel application by leveraging a message-driven runtime system.

@inproceedings{CCS_Streaming_Projections,
 author = {Isaac Dooley and Chee Wai Lee and Laxmikant Kale},
 title = {Continuous Performance Monitoring for Large-Scale Parallel Applications},
 booktitle = {16th annual IEEE International Conference on High Performance Computing (HiPC 2009)},
 year = {2009},
 month = {December},
 location = {Cochi, India}
}