SCHEDULE: NOV 16-22, 2013

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Swendsen-Wang Multi-Cluster Algorithm for the 2D/3D Ising Model on Xeon Phi and GPU

SESSION: Engineering Scalable Applications

EVENT TYPE: Papers

TIME: 4:00PM - 4:30PM

SESSION CHAIR: Andrew M. Canning

AUTHOR(S):Florian Wende, Thomas Steinke

ROOM:401/402/403

ABSTRACT:
Simulations of the critical Ising model by means of local update algorithms suffer from critical slowing down. One way to partially compensate for the influence of this phenomenon on the runtime of simulations is using increasingly faster and parallel computer hardware. Another approach is using algorithms that do not suffer from critical slowing down, such as cluster algorithms. This paper reports on the Swendsen-Wang multi-cluster algorithm on Intel Xeon Phi coprocessor 5110P, Nvidia Tesla M2090 GPU, and x86 multi-core CPU. We present shared memory versions of the said algorithm for the simulation of the two- and three-dimensional Ising model. We use a combination of local cluster search and global label reduction by means of atomic hardware primitives. Further, we describe an MPI version of the algorithm on Xeon Phi and CPU, respectively. Significant performance improvements over known implementations of the Swendsen-Wang algorithm are demonstrated.

Chair/Author Details:

Andrew M. Canning (Chair) - Lawrence Berkeley National Laboratory

Florian Wende - Zuse Institute Berlin

Thomas Steinke - Zuse Institute Berlin

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The full paper can be found in the ACM Digital Library