Unstructured Computational Aerodynamics on Many Integrated Core Architecture
Name:
1-s2.0-S0167819116300564-main.pdf
Size:
888.2Kb
Format:
PDF
Description:
Accepted Manuscript
Type
ArticleKAUST Department
Applied Mathematics and Computational Science ProgramComputer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Extreme Computing Research Center
Date
2016-06-11Online Publication Date
2016-06-11Print Publication Date
2016-11Permanent link to this record
http://hdl.handle.net/10754/613013
Metadata
Show full item recordAbstract
Shared memory parallelization of the flux kernel of PETSc-FUN3D, an unstructured tetrahedral mesh Euler flow code previously studied for distributed memory and multi-core shared memory, is evaluated on up to 61 cores per node and up to 4 threads per core. We explore several thread-level optimizations to improve flux kernel performance on the state-of-the-art many integrated core (MIC) Intel processor Xeon Phi “Knights Corner,” with a focus on strong thread scaling. While the linear algebraic kernel is bottlenecked by memory bandwidth for even modest numbers of cores sharing a common memory, the flux kernel, which arises in the control volume discretization of the conservation law residuals and in the formation of the preconditioner for the Jacobian by finite-differencing the conservation law residuals, is compute-intensive and is known to exploit effectively contemporary multi-core hardware. We extend study of the performance of the flux kernel to the Xeon Phi in three thread affinity modes, namely scatter, compact, and balanced, in both offload and native mode, with and without various code optimizations to improve alignment and reduce cache coherency penalties. Relative to baseline “out-of-the-box” optimized compilation, code restructuring optimizations provide about 3.8x speedup using the offload mode and about 5x speedup using the native mode. Even with these gains for the flux kernel, with respect to execution time the MIC simply achieves par with optimized compilation on a contemporary multi-core Intel CPU, the 16-core Sandy Bridge E5 2670. Nevertheless, the optimizations employed to reduce the data motion and cache coherency protocol penalties of the MIC are expected to be of value for CFD and many other unstructured applications as many-core architecture evolves. We explore large-scale distributed-shared memory performance on the Cray XC40 supercomputer, to demonstrate that optimizations employed on Phi hybridize to this context, where each of thousands of nodes are comprised of two sockets of Intel Xeon Haswell CPUs with 32 cores per node.Citation
Unstructured Computational Aerodynamics on Many Integrated Core Architecture 2016 Parallel ComputingSponsors
The authors are very appreciative of collaborations with Intel Research Laboratories, the Extreme Computing Research Center at KAUST, and Professor Rio Yokota of the Tokyo Institute of Technology. Support in the form of computing resources was provided by the KAUST Supercomputing Laboratory, and KAUST Information Technology Research Division.Publisher
Elsevier BVJournal
Parallel ComputingAdditional Links
http://linkinghub.elsevier.com/retrieve/pii/S0167819116300564ae974a485f413a2113503eed53cd6c53
10.1016/j.parco.2016.06.001