There are two considerations here. (1) Python single threaded performance: Here, most of the libraries we are using are implemented in C++ (like numpy, TensorF

There are two considerations here. (1) Python single threaded performance: Here, most of the libraries we are using are implemented in C++ (like numpy, TensorFlow, Cython to speed up the code, etc.). Ray is orthogonal to that. (2) Python parallel performance: Here Python is mostly problematic because of its lack of support for threading (the GIL is one problem here); we handle this problem by using multiple processes and shared memory throughout. Efficient serialization makes this feasible. The core of Ray is implemented in C++, so performance is not an issue for that; also all of the serialization is implemented in C++.