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A parallel automatic differentiation algorithm for simulation models

机译:仿真模型的并行自动微分算法

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Automatic differentiation is a technique to compute the exact values of derivatives numerically, without using any formula manipulation software. Recently it has been included in several simulation algorithms especially those which require real-time computation. This paper presents new software to compute first and second-order derivatives in parallel on a distributed memory multiprocessor system. The code has been extensively tested on a Transputer network; the results are very encouraging, showing a substantial speed-up for several test problems.
机译:自动微分是一种无需使用任何公式操作软件即可通过数值计算导数的精确值的技术。最近,它已被包括在几种仿真算法中,尤其是那些需要实时计算的算法。本文介绍了一种新软件,可在分布式内存多处理器系统上并行计算一阶和二阶导数。该代码已在Transputer网络上进行了广泛的测试;结果非常令人鼓舞,显示出明显加快了一些测试问题。

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