Enable reverse-mode automatic differentiation of (CUDA) GPU kernels using Clad


Clad is an automatic differentiation (AD) clang plugin for C++. Given a C++ source code of a mathematical function, it can automatically generate C++ code for computing derivatives of the function. Clad has found uses in statistical analysis and uncertainty assessment applications. In scientific computing and machine learning, GPU multiprocessing can provide a significant boost in performance and scalability. This project focuses on enabling the automatic differentiation of CUDA GPU kernels using Clad. This will allow users to take advantage of the power of GPUs while benefiting from the accuracy and speed of automatic differentiation.

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