MONTE-CARLO SIMULATION ON TRANSPUTER ARRAYS

Journal article

A Monte Carlo simulation of a simple statistical physics model is decomposed onto a multi-processor (transputer) array in two essentially different ways: using 'geometric' and 'algorithmic' concurrency. The geometric decomposition (in which each processor handles a small sector of the physical system) is characterized by high efficiency in utilization of processors, and relative simplicity in programming. The algorithmic decomposition (in which each processor handles a small sub-task of the full algorithm, typically in a pipelined mode) is characterized by greater flexibility in the data-size (size of the physical system) and minimal memory requirements for a majority of the processors in the array. These assertions are made concrete in relation to our specific problem (a two-dimensional spin system simulation) which is, in many respects representative of a wide class of problems of interest to theoretical physicists. © 1988.

Authors: Askew, C; Carpenter, D; Chalker, J; Hey, A; Moore, M

• Publication status: Published
• Journal: PARALLEL COMPUTING
• Volume: 6
• Issue: 2
• Pages: 247-258
• Publication date: 1988-02-01
• DOI: 10.1016/0167-8191(88)90089-0
• ISSN: 0167-8191
• Language: English
• Keywords: Multiprocessors; transputer array; two-dimensional spin system simulation; Monte Carlo simulation; parallelization; parallelism