Personal tools
You are here: Home Publications Scientific Computing Kernels on the Cell Processor
Document Actions

Samuel Williams, John Shalf, Leonid Oliker, Shoaib Kamil, Parry Husbands, and Katherine Yelick (2007)

Scientific Computing Kernels on the Cell Processor

International Journal of Parallel Programming, 35(3):263–298.

In this work, we examine the potential of using the recently-released STI Cell processor as a building block for future high-end scientific computing systems. Our work contains several novel contributions. First, we introduce a performance model for Cell and apply it to several key numerical kernels: dense matrix multiply, sparse matrix vector multiply, stencil computations, and 1D/2D FFTs. Next, we validate our model by comparing results against published hardware data, as well as our own Cell blade implementations. Additionally, we compare Cell performance to benchmarks run on leading superscalar (AMD Opteron), VLIW (Intel Itanium2), and vector (Cray X1E) architectures. Our work also explores several different kernel implementations and demonstrates a simple and effective programming model for Cell’s unique architecture. Finally, 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.

by admin last modified 2008-02-15 04:37
« November 2017 »
Su Mo Tu We Th Fr Sa
1234
567891011
12131415161718
19202122232425
2627282930
 

Powered by Plone

CScADS Collaborators include:

Rice University ANL UCB UTK WISC