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Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques (1999)
Newport Beach, California
Oct. 12, 1999 to Oct. 16, 1999
ISSN: 1089-795X
ISBN: 0-7695-0425-6
pp: 98
John B. Carter , University of Utah
Wilson C. Hsieh , University of Utah
Lixin Zhang , University of Utah
Sally A. McKee , University of Utah
Image processing applications tend to access their data non-sequentially and reuse that data infrequently. As a result, they tend to perform poorly on conventional memory systems due to high cache and TLB miss rates and are particularly sensitive to the growing latency of main memory. In this paper, we analyze the memory performance of three image processing algorithms (volume rendering, image warping, and image filtering) on both a conventional memory system and on the Impulse memory system. The Impulse memory system allows application software to control how, when, and where data are loaded into a conventional processor cache. It does this by letting software configure how the memory controller interprets the physical addresses exported by the processor, which enables an application to dynamically change how data are fetched. Sparse data can be accessed densely, which improves both cache and TLB utilization, and memory latency is hidden by prefetching data within the memory controller. We find that for these image processing codes, using an Impulse memory system yields speedups of 40% to 226% over an otherwise identical machine with a conventional memory system.
memory architecture, memory latency, memory bandwidth, bus utilization, cache efficiency, image processing, virtual memory
John B. Carter, Wilson C. Hsieh, Lixin Zhang, Sally A. McKee, "Memory System Support for Image Processing", Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques, vol. 00, no. , pp. 98, 1999, doi:10.1109/PACT.1999.807426
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