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2020 Mar 24
2
Machine learning and compiler optimizations: using inter-procedural analysis to select optimizations
I am a grad CS student at Stanford and wanted to engage with EJ Park, Giorgis Georgakoudis, Johannes Doerfert to further develop the Machine Learning and Compiler Optimization concept. My background is in machine learning, cluster computing, distributed systems etc. I am a good C/C++ developer and have a strong background in algorithms and data structure. I am also taking an advanced compiler
2020 Mar 27
2
Machine learning and compiler optimizations: using inter-procedural analysis to select optimizations
Hi Johannes - great we are engaging on this. Some responses now and some later. 1. When you say setup LLVM dev environment +. clang + tools etc, do you mean setup LLVM compiler code from the repo and build it locally? If so, yes, this is all done from my end - that is, I have built all this on my machine and compiled and run a couple of function passes. I have look at some LLVM emits from clang
2020 Mar 31
2
Machine learning and compiler optimizations: using inter-procedural analysis to select optimizations
1. Thanks for the clarifications. I will stick to non-containerized OS X for now. 2. As an aside, I did try to build a Debian docker container by git cloning into it and using the Dockerfile in LLVM/utils/docker as a starting point: - some changes needed to updated packages (GCC in particular needs to be latest) and the Debian image (Debian 9 instead of Debian 8) pretty much sets up the docker
2020 Mar 31
2
Machine learning and compiler optimizations: using inter-procedural analysis to select optimizations
Hi Johannes: 1. Attached is the submitted PDF. 2. I have a notes section where I state: I am still unsure of the GPU extension I proposed as I dont know how LLVM plays into the GPU cross over space like how nvcc (Nvidia's compiler integrates gcc and PTX) does.I dont know if there is a chance that function graphs in the CPU+GPU name spaces are seamless/continupus within nvcc or if nvcc is just