Abstract:
Parallel programming is an emerging trend for writing parallel applications for
compute clusters with multiple processing cores not only for the scientific community
but also for the research students and industry. Message Passing Interface
(MPI) has emerged as a de facto standard for writing parallel applications as a programming
language independent communication protocol which provides the procedures
and rules for passing messages. MPI has been implemented in many high
level languages including Fortran, C and Java. One such java implementation is
MPJ Express - an open source Java message passing library. The parallel execution
of programs especially in distributed memory model requires data exchange among
various processors using Collective Communication operations. These operations
are responsible for data distribution, consolidation as well as computation and as
such are critical to the performance of parallel applications. The current version
(0.38) of the MPJ Express implements linear algorithms for Collective Communication
operations which form the main source of overhead while executing parallel
programs. This work aims at optimization of existing Collective Communication
operations, evaluation using established benchmarks and subsequent integration in
MPJ Express. The main contribution of this work is to replace the current implementation
by a scalable version of collective primitives thus improving the MPJ
Express for Java HPC community. A percentage improvement of 1% to 90% is
reported in this work for newly implemented Collective primitives.
