Abstract

Current operating systems offer poor performance when a numeric application's working set does not fit in main memory. As a result, programmers who wish to solve "out-of-core" problems efficiently are typically faced with the onerous task of rewriting an application to use explicit I/O operations (e.g., read/write). In this paper, we propose and evaluate a fully-automatic technique which liberates the programmer from this task, provides high performance, and requires only minimal changes to current operating systems. In our scheme, the compiler provides the crucial information on future access patterns without burdening the programmer, the operating system supports non-binding prefetch and release hints for managing I/O, and the operating system cooperates with a run-time layer to accelerate performance by adapting to dynamic behavior and minimizing prefetch overhead. This approach maintains the abstraction of unlimited virtual memory for the programmer, gives the compiler the exibility to aggressively move prefetches back ahead of references, and gives the operating system the exibility to arbitrate between the competing resource demands of multiple applications. We have implemented our scheme using the SUIF compiler and the Hurricane operating system. Our experimental results demonstrate that our fully-automatic scheme effectively hides the I/O latency in out-of-core versions of the entire NAS Parallel benchmark suite, thus resulting in speedups of roughly twofold for five of the eight applications, with one application speeding up by over threefold.

 

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