Restructuring I/O-intensive computations for locality

This paper describes restructuring techniques for out-of-core programs (i.e., those that deal with very large quantities of data) based on exploiting locality using a combination of loop and data transformations. Writing efficient out-of-core program is an arduous task. As a result, compiler optimizations directed at improving YO performance are becoming increasingly important. We describe how a compiler can improve the performance of the code by determining appropriate file layouts for out-of-core arrays and finding suitable loop transformations. In addition to optimizing a single loop nest, our solution can handle a sequence of loop nests. We also show how to generate code when the file layouts are optimized. Preliminary experimental results obtained on an Intel Paragon distributed-memory message-passing multiprocessor demonstrate marked improvements in performance due to the optimizations described in this paper