Analytic Queueing Network Models for Parallel Processing of Task Systems
IEEE Transactions on Computers
PAPS: the parallel program performance prediction toolset
Proceedings of the 7th international conference on Computer performance evaluation : modelling techniques and tools: modelling techniques and tools
Automated Scalability Analysis of Message-Passing Parallel Programs
IEEE Parallel & Distributed Technology: Systems & Technology
Compile-Time Performance Prediction of HPF/Fortran 90D
IEEE Parallel & Distributed Technology: Systems & Technology
Analytic Queueing Models for Programs with Internal Concurrency
IEEE Transactions on Computers
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Today's massively parallel machines are typically message-passing systems consisting of hundreds or thousands of processors. Implementing parallel applications efficiently in this environment is a challenging task, and poor parallel design decisions can be expensive to correct. Tools and techniques that allow the fast and accurate evaluation of different parallelization strategies would significantly improve the productivity of application developers and increase throughput on parallel architectures. This paper investigates one of the major issues in building tools to compare parallelization strategies: determining what type of performance models of the application code and of the computer system are sufficient for a fast and accurate comparison of different strategies. The paper is built around a case study employing the Performance Prediction Tool (PerPreT) to predict performance of the Parallel Spectral Transform Shallow Water Model code (PSTSWM) on the Intel Paragon.