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The Potential of the Cell Processor for Scientific Computing Samuel Williams John Shalf Leonid Oliker Parry Husbands Shoaib Kamil Katherine Yelick
ABSTRACT: The slowing pace of commodity microprocessor performance improvements combined with
ever-increasing chip power demands has become of utmost concern to computational scientists. As a
result, the high performance computing community is examining alternative architectures that
address the limitations of modern cache-based designs. In this work, we examine the potential of
the using the forthcoming STI Cell processor as a building block for future high-end computing
systems. Our work contains several novel contributions. We are the first to present quantitative
Cell performance data on scientific kernels and show direct comparisons against leading
superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1) architectures. Since
neither Cell hardware nor cycle-accurate simulators are currently publicly available, we develop
both analytical models and simulators to predict kernel performance. Our work also explores the
complexity of mapping several important scientific algorithms onto the Cell s unique architecture.
Additionally, we propose modest microarchitectural modifications that could significantly increase
the efficiency of double-precision calculations. Overall results demonstrate the tremendous
potential of the Cell architecture for scientific computations in terms of both raw performance
and power efficiency.
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