Compiler and Runtime Support for Programming in Adaptive Parallel Environments

For better utilization of computing resources, it is important to consider parallel programming environments in which the number of available processors varies at runtime. In this paper, we discuss runtime support for data parallel programming in such an adaptive environment. Executing programs in an adaptive environment requires redistributing data when the number of processors changes, and also requires determining new loop bounds and communication patterns for the new set of processors. We have developed a runtime library to provide this support. We discuss how the runtime library can be used by compilers of HPF-like languages to generate code for an adaptive environment. We present performance results for Navier-Stokes solver on a multigrid template run on a network of workstations and an IBM SP-2. Our experiments show that if the number of processors is not varies frequently, the cost of data distribution is not significant when compared to the time required for the actual computation. Overall, our work establishes the feasibility of compiling HPF for a network on non-dedicated workstations, which are likely to be an important resource for parallel programming in the future.