that project might be abandoned but this strategy is used in nvidia and nvidia adjacent projects (through llvm): https://github.com/rapidsai/cudf/blob/branch-0

that project might be abandoned but this strategy is used in nvidia and nvidia adjacent projects (through llvm): https://github.com/rapidsai/cudf/blob/branch-0.20/python/cudf/cudf/utils/cudautils.py#L215 https://github.com/rapidsai/cudf/blob/branch-0.20/python/cud... https://github.com/gmarkall/numba/blob/master/numba/cuda/compiler.py https://github.com/gmarkall/numba/blob/master/numba/cuda/com... >but we also need high level expressibility that doesn't require writing kernels in C the above are possible because C is actually just a frontend to PTX https://docs.nvidia.com/cuda/parallel-thread-execution/index.html https://docs.nvidia.com/cuda/parallel-thread-execution/index... fundamentally you are not going to ever be able to have a way to write cuda kernels without thinking about cuda architecture anymore so than you'll ever be able to write async code without thinking about concurrency.