cuStreamz defers its computation down to cuDF which uses a combination of ahead of time compiled kernels via libcudf and just in time compiled kernels via Numba, CuPy, and Jitify for its execution. As far as I know none…
PyTorch supports both `__cuda_array_interface__` and dlpack which allows effectively sharing the GPU pointer without having to go through a host numpy array. Tensorflow is actively working on adding support for dlpack…
cuStreamz defers its computation down to cuDF which uses a combination of ahead of time compiled kernels via libcudf and just in time compiled kernels via Numba, CuPy, and Jitify for its execution. As far as I know none…
PyTorch supports both `__cuda_array_interface__` and dlpack which allows effectively sharing the GPU pointer without having to go through a host numpy array. Tensorflow is actively working on adding support for dlpack…