Using OpenGL instead of CUDA for machine learning


In this project, we

  1. Added an OpenGL backend for MXNet/TVM - a general-purpose tensor computation framework, so that it automatically compiles a Python program into an OpenGL shader that runs on the GPU on a computer that does not have CUDA.

  2. Explored optimizations of OpenGL shader programs so that a fundamental computation task needed in machine learning - matrix multiplication - has comparable performance with OpenCL on the same machine.

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