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Parallel Calculation of Sensitivity Derivatives for Aircraft Design using Automatic Differentiation

机译:使用自动微分并行计算飞机设计中的灵敏度导数

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摘要

Sensitivity derivative (SD) calculation via automatic differentiation (AD) typical of that required for the aerodynamic design of a transport-type aircraft is considered. Two ways of computing SD via code generated by the ADIFOR automatic differentiation tool are compared for efficiency and applicability to problems involving large numbers of design variables. A vector implementation on a Cray Y-MP computer is compared with a coarse-grained parallel implementation on an IBM SP1 computer, employing a Fortran M wrapper. The SD are computed for a swept transport wing in turbulent, transonic flow; the number of geometric design variables varies from 1 to 60 with coupling between a wing grid generation program and a state-of-the-art, 3-D computational fluid dynamics program, both augmented for derivative computation via AD. For a small number of design variables, the Cray Y-MP implementation is much faster. As the number of design variables grows, however, the IBM SP1 becomes an attractive alternative in terms of compute speed, job turnaround time, and total memory available for solutions with large numbers of design variables. The coarse-grained parallel implementation also can be moved easily to a network of workstations.
机译:考虑了通过自动微分(AD)计算的灵敏度导数(SD),这通常是运输型飞机的空气动力学设计所需的。比较了通过ADIFOR自动微分工具生成的代码计算SD的两种方法,以提高效率和适用于涉及大量设计变量的问题。使用Fortran M包装器,将Cray Y-MP计算机上的矢量实现与IBM SP1计算机上的粗粒度并行实现进行了比较。 SD是针对湍流,跨音速流中的后掠运输机翼计算的;几何设计变量的数量从1到60不等,这取决于机翼栅格生成程序和最新的3-D计算流体动力学程序之间的耦合,两者均通过AD进行了微分计算。对于少量设计变量,Cray Y-MP的实现要快得多。但是,随着设计变量数量的增加,就计算速度,作业周转时间和具有大量设计变量的解决方案可用的总内存而言,IBM SP1成为有吸引力的替代方案。粗粒度并行实现也可以轻松地移动到工作站网络。

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