Added Concurrency to Improve MPI Performance on Multicore

MPI implementations typically equate an MPI process with an OS-process, resulting in a coarse-grain programming model where MPI processes are bound to the physical cores. Fine-Grain (FG-MPI) extends the MPICH2 implementation of MPI and implements an integrated runtime system to allow multiple MPI processes to execute concurrently inside an OS-process. FG-MPI´s integrated approach makes it possible to add more concurrency than available parallelism, while minimizing the overheads related to context switches, scheduling and synchronization. In this paper we evaluate the benefits of added concurrency for cache awareness and message size and show that performance gains are possible by using FG-MPI to adjust the grain-size of a program to better fit the cache and potential advantages in passing smaller versus larger messages. We evaluate the use of FG-MPI on the complete set of the NAS parallel benchmarks over large problem sizes, where we show significant performance improvement (20%-30%) for three of the eight benchmarks. We discuss the characteristics of the benchmarks with regards to trade-offs between the added costs and benefits.