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International Parallel and Distributed Processing Symposium (IPDPS'03)
HiDISC: A Decoupled Architecture for Data-Intensive Applications
Nice, France
April 22-April 26
ISBN: 0-7695-1926-1
Won W. Ro, University of Southern California
Jean-Luc Gaudiot, University of California at Irvine
Stephen P. Crago, University of Southern California
Alvin M. Despain, University of Southern California

This paper presents the design and performance evaluation of our high-performance decoupled architecture, the HiDISC (Hierarchical Decoupled Instruction Stream Computer). HiDISC provides low memory access latency by introducing enhanced data prefetching techniques at both the hardware and the software levels. Three processors, one for each level of the memory hierarchy, act in concert to mask the memory latency.

Our performance evaluation benchmarks include the Data-Intensive Systems Benchmark suite and the DIS Stressmark suite. Our simulation results point to a distinct advantage of the HiDISC system over current prevailing superscalar architectures for both sets of the benchmarks. On the average, a 12% improvement in performance is achieved while 17% of cache misses are eliminated.

Index Terms:
Data prefetching, Decoupled architecture, Data-intensive applications, Memory access latency, and Speculative pre-execution.
Citation:
Won W. Ro, Jean-Luc Gaudiot, Stephen P. Crago, Alvin M. Despain, "HiDISC: A Decoupled Architecture for Data-Intensive Applications," ipdps, pp.3b, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003
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