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Parallel algorithm for efficient calculation of second derivatives of conformational energy function in internal coordinates

机译:高效计算内部坐标中构象能量函数二阶导数的并行算法

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A parallel algorithm for efficient calculation of the second derivatives (Hessian) of the conformational energy in internal coordinates is proposed, This parallel algorithm is based on the master/slave model. A master processor distributes the calculations of components of the Hessian to one or more slave processors that, after finishing their calculations, send the results to the master processor that assembles all the components of the Hessian. Our previously developed molecular analysis system for conformational energy optimization, norm,al mode analysis, and Monte Carlo simulation for internal coordinates is extended to use this parallel algorithm for Hessian calculation on a massively parallel computer. The implementation of our algorithm uses the message passing Interface and works effectively on both distributed-memory parallel computers and shared-memory parallel computers. We applied this system to the Newton-Raphson energy optimization of the structures of glutaminyl transfer RNA (Gln-tRNA) with 74 nucleotides and glutaminyl-tRNA synthetase (GlnRS) with 540 residues to analyze the performance of our system. The parallel speedups for the Hessian calculation were 6.8 for Gln-tRNA with 24 processors and 11.2 for GlnRS with 54 processors. The parallel speedups for the Newton-Raphson optimization were 6.3 for Gln-tRNA with 30 processors and 12.0 for GlnRS with 62 processors. (C) 1998 John Wiley & Sons, Inc. [References: 19]
机译:提出了一种有效计算内部坐标中构象能量二阶导数(Hessian)的并行算法,该并行算法基于主/从模型。主处理器将粗麻布成分的计算分发给一个或多个从属处理器,这些处理器在完成计算后,将结果发送到组装粗麻布成分的主处理器。我们先前开发的用于构象能量优化,范式,模态分析和内部坐标的蒙特卡罗模拟的分子分析系统已扩展为在大规模并行计算机上使用此并行算法进行Hessian计算。我们算法的实现使用消息传递接口,并且可以在分布式内存并行计算机和共享内存并行计算机上有效地工作。我们将该系统应用于具有74个核苷酸的谷氨酰转移RNA(Gln-tRNA)和具有540个残基的谷氨酰胺-tRNA合成酶(GlnRS)的牛顿-拉夫森能量优化中,以分析系统的性能。对于具有24个处理器的Gln-tRNA,Hessian计算的并行加速为6.8,对于具有54个处理器的GlnRS,并行加速为11.2。对于具有30个处理器的Gln-tRNA,Newton-Raphson优化的并行加速比为6.3,对于具有62个处理器的GlnRS,并行加速为12.0。 (C)1998 John Wiley&Sons,Inc. [参考:19]

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