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CuAD: Source-to-Source Automatic Differentiation of CUDA Kernels for Discrete Adjoints in Computational Fluid Dynamics
Discrete adjoint methods give the sensitivities that aerodynamic design and data assimilation require, but they remain hard to obtain for flow solvers that run on graphics processors. This paper presents CuAD, a source-to-source automatic differentiation tool that reads CUDA kernels and writes their
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