An efficient sweep parallel algorithm used when solving the nonlinear Schrödinger equation by the implicit Crank-Nicolson scheme with a spatial and time mesh refinement mechanism is considered. Its performance on distributed-memory multiprocessors is analyzed. It is shown on the basis of computational experiments and the well-known theoretical model (Amdahl's law) that the proposed algorithm scales well and achieves efficiency and speedup over the sequential algorithm up to 0.7 and 30, respectively. The effect of the numerical mesh size (range, 10⁴-10⁶) and the network communication delays (CPU number range, 6 - 128) on the performance of computing is discussed.

Key words: mathematical simulation, parallel algorithms, high performance computing, Schrödinger equation

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