GRID*p: Interactive Data-Parallel Programming on the Grid with MATLAB

The Computational Grid has emerged as an attractive platform for developing large-scale distributed applications that run on heterogeneous computing resources. This scalability, however, comes at the cost of increased complexity: each application has to handle the details of resource provisioning and data and task scheduling. To address this problem, we present GRID*p an interactive parallel system built on top of MATLAB*p and Globus that provides a MATLAB-like problem solving environment for the Grid. Applications under GRID*p achieve automatic data parallelism through the transparent use of distributed data objects, while the GRID*p runtime takes care of data partitioning, task scheduling and inter-node messaging. We evaluate the simplicity and performance of GRID*p with two different types of parallel applications consisting of matrix and graph computations one of which investigates an open problem in combinatorial scientific computing. Our results show that GRID*p delivers promising performance for highly parallel applications, at the same time greatly simplifying their development.