Profiling a parallel language based on fine-grained communication

Authors:
Bjoern Haake;Klaus E. Schauser;Chris Scheiman
Affiliations:
Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA;Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA;Department of Computer Science, University of California, Santa Barbara, Santa Barbara, CA
Venue:
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Year:
1996

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Abstract

Fine tuning the performance of large parallel programs is a very difficult task. A profiling tool can provide detailed insight into the utilization and communication of the different processors, which helps identify performance bottlenecks. In this paper we present a profiler for the fine-grained parallel programming language Split-C, which provides a simple global address space memory model. As our experience shows, it is much more challenging to profile programs that make use of efficient, low-overhead communication. We incorporated techniques which minimize profiling effects on the running program. We quantify the profiling overhead and present several Split-C applications which show that the profiler is useful in determining performance bottlenecks.