The potential of the cell processor for scientific computing

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 using the forthcoming STI Cell processor as a building block for future high-end computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key scientific computing kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. The difficulty of programming Cell, which requires assembly level intrinsics for the best performance, makes this model useful as an initial step in algorithm design and evaluation. Next, we validate the accuracy of our model by comparing results against published hardware results...

• Type: Conference
• Year: 2006
• Where: CF
• Authors: Samuel Williams, John Shalf, Leonid Oliker, Shoaib Kamil, Parry Husbands, Katherine A. Yelick
• Keywords: Applied Computing, Cell, CF 2006, Performance, STI Cell Processor