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 algorithms for parallelizing Monte Carlo simulations for 2D Ising spin models
The Journal of Supercomputing
The tao of parallelism in algorithms
Proceedings of the 32nd ACM SIGPLAN conference on Programming language design and implementation
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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 regards 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 provided comparisons between the different schemes.