Improving the performance of out-of-core computations

The difficulty of handling out-of-core data limits the potential of parallel machines and high-end supercomputers. Since writing an efficient out-of-core version of a program is a difficult task and since virtual memory systems do not perform well on scientific computations, we believe that there is a clear need for compiler-directed explicit I/O approach for out-of-core computations. In this paper, we present a compiler algorithm to optimize locality of disk accesses in out-of-core codes by choosing a good combination of file layouts on disks and loop transformations. The transformations change the access order of array data. Experimental results obtained on IBM SP-2 and Intel Paragon provide encouraging evidence that our approach is successful at optimizing programs which depend on disk-resident data in distributed-memory machines.