Name
Abstract | ||
|---|---|---|
A Modern Graphics Processing unit (GPU) is able to perform massively parallel scientific computations at low cost. We extend our implementation of the checkerboard algorithm for the two-dimensional Ising model [T. Preis et al., Journal of Chemical Physics 228 (2009) 4468–4477] in order to overcome the memory limitations of a single GPU which enables us to simulate significantly larger systems. Using multi-spin coding techniques, we are able to accelerate simulations on a single GPU by factors up to 35 compared to an optimized single Central Processor Unit (CPU) core implementation which employs multi-spin coding. By combining the Compute Unified Device Architecture (CUDA) with the Message Parsing Interface (MPI) on the CPU level, a single Ising lattice can be updated by a cluster of GPUs in parallel. For large systems, the computation time scales nearly linearly with the number of GPUs used. As proof of concept we reproduce the critical temperature of the 2D Ising model using finite size scaling techniques. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.cpc.2010.05.005 | Computer Physics Communications |
Keywords | Field | DocType |
Monte Carlo simulation,GPU computing,Ising model,Phase transition,Finite size scaling | Monte Carlo method,Central processing unit,GPU cluster,CUDA,Computer science,Massively parallel,Parallel computing,Computational science,Ising model,General-purpose computing on graphics processing units,Graphics processing unit | Journal |
Volume | Issue | ISSN |
181 | 9 | 0010-4655 |
Citations | PageRank | References |
33 | 2.75 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Benjamin Block | 1 | 33 | 2.75 |
| Peter Virnau | 2 | 180 | 19.44 |
| Tobias Preis | 3 | 150 | 14.45 |