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