SUPPLE: An efficient run-time support for non-uniform parallel loops

This paper presents SUPPLE (SUPort for Parallel Loop Execution), an innovative run{time support for the execution of parallel loops with regular stencil data references and non{uniform iteration costs. SUPPLE relies upon a static block data distribution to exploit locality, and combines static and dynamic policies for scheduling non{uniform iterations. It adopts, as far as possible, a static scheduling policy derived from the owner computes rule, and moves data and iterations among processors only if a load imbalance actually occurs. SUPPLE always tries to overlap communications with useful computations by reordering loop iterations and prefetching remote ones in the case of workload imbalance. The SUPPLE approach has been validated by m a n y experimental results obtained by running a multi-dimensional ame simulation kernel on a 64{node Cray T 3 D. W e h a ve fed the benchmark code with several synthetic input data sets built on the basis of a load imbalance model. We h a ve compared our results with those obtained with a CRAFT Fortran implementation of the benchmark.