Multi-core Acceleration of Chemical Kinetics for Simulation and
Prediction [
abstract]
John C. Linford, John Michalakes, Manish Vachharajani, and Adrian SanduProceedings of the International Conference on High Performance Computing, Networking, Storage, and Analysis (SC), November 2009.
Accept Rate: 22% (59/261).
This work implements a computationally-intense chemical
kinetics kernel from a large-scale community atmospheric model on
three multi-core platforms: NVIDIA CUDA, the Cell Broadband Engine,
and Intel Quad-Core Xeon CPUs. A comparative performance analysis for
each platform in double and single precision on coarse and fine grids
is presented. Platform-specific design and optimization is discussed
in a mechanism-agnostic way, permitting the optimization of many
chemical mechanisms. Combined with the Kinetic PreProcessor (KPP),
this approach allows many chemical mechanisms to be automatically
optimized and ported to a variety of multi-core platforms. Speedups of
40x in single precision and 18x in double precision are observed when
compared to eight Xeon cores.