Parallel algorithms in computational science
Parallel algorithms in computational science
Optimal broadcast and summation in the LogP model
SPAA '93 Proceedings of the fifth annual ACM symposium on Parallel algorithms and architectures
LogP: a practical model of parallel computation
Communications of the ACM
Optimal and near-optimal algorithms for k-item broadcast
Journal of Parallel and Distributed Computing
Efficient Parallel Algorithms for 2-Dimensional Ising Spin Models
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
The Monte Carlo Method in Science and Engineering
Computing in Science and Engineering
Parallel implementation of the heisenberg model using Monte Carlo on GPGPU
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part III
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In this paper, we design and implement a variety of parallel algorithms for both sweep spin selection and random spin selection. We analyze our parallel algorithms on LogP, a portable and general parallel machine model. We then obtain rigorous theoretical runtime results on LogP for all the parallel algorithms. Moreover, a guiding equation is derived for choosing data layouts (blocked vs. stripped) for sweep spin selection. In regard to random spin selection, we are able to develop parallel algorithms with efficient communication schemes. We introduce two novel schemes, namely the FML scheme and the 驴-scheme. We analyze randomness of our schemes using statistical methods and provide comparisons between the different schemes.