Performance modeling of parallel applications on multicore computers remains a challenge in computational co-design due to the complex design of multicore processors including private and shared memory hierarchies. We present a Scalable Analytical Shared Memory Model to predict the performance of parallel applications that runs on a multicore computer and shares the same level of cache in the hierarchy. This model uses a computationally efficient, probabilistic method to predict the reuse distance profiles, where reuse distance is a hardware architecture-independent measure of the patterns of virtual memory accesses. It relies on a stochastic, static basic block-level analysis of reuse profiles measured from the memory traces of applications ran sequentially on small instances rather than using a multi-threaded trace. The results indicate that the hit-rate predictions on the shared cache are accurate.
@article{arxiv.1907.12666,
title = {Modeling Shared Cache Performance of OpenMP Programs using Reuse Distance},
author = {Atanu Barai and Gopinath Chennupati and Nandakishore Santhi and Abdel-Hameed A. Badawy and Stephan Eidenbenz},
journal= {arXiv preprint arXiv:1907.12666},
year = {2019}
}