out-of-core, data-parallelism, I/O, optimizing compilers, distributed-memory machines
The difficulty of handling out-of-core data limits the performance of supercomputers as well as the potential of the parallel machines. Since writing an efficient out-of-core version of a program is a difficult task and 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 first present an out-of-core compilation strategy based on a disk storage abstraction. Then we offer 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. We introduce memory coefficient and processor coefficient concepts to characterize the behavior of out-of-core programs under different memory constraints. We also enhance our algorithm to handle data-parallel programs which contain multiple loop nest. Our initial 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.
Kandemir, Mahmut; Choudhary, Alok; Ramanujam, J.; and Bordawekar, Rajesh, "Compilation techniques for out-of-core parallel computations" (1998). Electrical Engineering and Computer Science. 80.
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