Current implementations of MPI are coarse-grained, with a single MPI process per processor, however, there is nothing in the MPI specification precluding a finer-grain interpretation of the standard. We have implemented Fine-grain MPI (FG-MPI), a system that allows execution of hundreds and thousands of MPI processes on one node or communicating between nodes inside a cluster. FG-MPI uses fibers (coroutines) to support multiple MPI processes inside an operating system process. These are full-fledged MPI processes each with their own MPI rank. FG-MPI is based on MPICH2 middleware and uses the Nemesis communication subsystem for intra-node and inter-node communication.

Alan Wagner will give experimental results for applications using thousands of MPI processes and compare its performance with several fine-grain multicore languages. FG-MPI also made it possible to investigate problems related to scaling of MPI to a larger number of processes. I will present the design and evaluation of techniques to support the scalability of communicators and groups in MPI. Performance results are given for the execution of an MPI benchmark program with upwards of 100,000 MPI processes with communicators created for various groups of different sizes and types.

Brief Biography:

Alan Wagner (BSc Dalhousie University, MSc University of Alberta, PhD, University of Toronto) is an Associate Professor in Computer Science at the University of British Columbia. His research interests include MPI middleware and message-passing systems, networking, data-mining, and computational finance.