Managing Locality in Grand Challenge Applications: A Case Study of the Gyrokinetic Toroidal Code
September 24, 2008
10:00 AM
5700, L202
Host: Jeff Vetter (vetter@ornl.gov)
ABSTRACT:
Achieving high performance with grand challenge applications on today's large-scale parallel systems requires tailoring applications for the characteristics of the modern microprocessor architectures. As part of the US Department of Energy's Scientific Discovery through Advanced Computing (SciDAC-2) program, we studied and tuned the Gyrokinetic Toroidal Code (GTC), a particle-in-cell code for simulating turbulent transport of particles and energy in burning plasma, developed at Princeton Plasma Physics Laboratory. In this talk, we present a performance study of the application which revealed several opportunities for improving performance by enhancing its data locality.
We tuned GTC by performing three kinds of transformations: static data structure reorganization to improve spatial locality, loop nest restructuring for better temporal locality, and dynamic data reordering at run-time to enhance both spatial and temporal reuse. Experimental results show that these changes improve execution time by more than 20% on large parallel systems, including a Cray XT4.
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