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We present PPT-Multicore, an analytical model embedded in the PerformancePrediction Toolkit (PPT) to predict parallel application performance running ona multicore processor. PPT-Multicore builds upon our previous work towards amulticore cache model. We extract LLVM basic block labeled memory trace usingan architecture-independent LLVM-based instrumentation tool only once in anapplication's lifetime. The model uses the memory trace and other parametersfrom an instrumented sequentially executed binary. We use a probabilistic andcomputationally efficient reuse profile to predict the cache hit rates andruntimes of OpenMP programs' parallel sections. We model Intel's Broadwell,Haswell, and AMD's Zen2 architectures and validate our framework usingdifferent applications from PolyBench and PARSEC benchmark suites. The resultsshow that PPT-Multicore can predict cache hit rates with an overall averageerror rate of 1.23% while predicting the runtime with an error rate of 9.08%.

PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling