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This introduces new functions: ``` // returns kernel(args...) running on the CPU. Eigen::run_on_cpu(Kernel kernel, Args&&... args); // returns kernel(args...) running on the GPU. Eigen::run_on_gpu(Kernel kernel, Args&&... args); Eigen::run_on_gpu_with_hint(size_t buffer_capacity_hint, Kernel kernel, Args&&... args); // returns kernel(args...) running on the GPU if using // a GPU compiler, or CPU otherwise. Eigen::run(Kernel kernel, Args&&... args); Eigen::run_with_hint(size_t buffer_capacity_hint, Kernel kernel, Args&&... args); ``` Running on the GPU is accomplished by: - Serializing the kernel inputs on the CPU - Transferring the inputs to the GPU - Passing the kernel and serialized inputs to a GPU kernel - Deserializing the inputs on the GPU - Running `kernel(inputs...)` on the GPU - Serializing all output parameters and the return value - Transferring the serialized outputs back to the CPU - Deserializing the outputs and return value on the CPU - Returning the deserialized return value All inputs must be serializable (currently POD types, `Eigen::Matrix` and `Eigen::Array`). The kernel must also be POD (though usually contains no actual data). Tested on CUDA 9.1, 10.2, 11.3, with g++-6, g++-8, g++-10 respectively. This MR depends on !622, !623, !624.
Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
For more information go to http://eigen.tuxfamily.org/.
For pull request, bug reports, and feature requests, go to https://gitlab.com/libeigen/eigen.