Hi All, I've recently wrapped up an ML framework research project that I've been working on for some time. It addresses a lot of difficult design problems, and works around a lot of compiler bugs and Linux library deficiencies.
It's written almost entirely in Swift 4.0 with some C and Cuda kernels. Development and testing were done primarily on Ubuntu 16.04, but it will also build on MacOS. Linux was the primary environment, because there aren't any modern Macs that can host big NVIDIA hardware The framework interfaces with many common C libraries such as: *Cuda, cuDNN, lmdb, png, jpeg, zlib* Anyone in the community that is trying to work with these libraries might benefit from the Swift wrapper classes and examples of successful use. There are other isolated technology pieces that might be of use also. Other people's projects and examples helped me along the way, so I am hoping that my work will help some of you as well. The code and overview docs are published on GitHub docs: https://github.com/ewconnell/Netlib/wiki code: https://github.com/ewconnell/Netlib Happy coding, Ed :)
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