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I last experimented with CUDA.jl a year ago, and it was very useable then. This is a good reminder to re-evaluate the Julia deep learning ecosystem. If I were w
by version_five 5y ago
I last experimented with CUDA.jl a year ago, and it was very useable then. This is a good reminder to re-evaluate the Julia deep learning ecosystem. If I were working for myself I would definitely try to do more with Julia (for machine learning). Realistically, python has such an established base that it will take some time to get orgs that are already all in on python to come over.
- dnautics 5y agoI think it's not dumb to target Greenfield users: just installing python gpu wheels is often difficult enough that several companies exist (indirectly) because it's so difficult to do right (e.g. selling a gpu PC with that stuff preinstalled)
- queuebert 5y agoI just finished setting up a new machine to run some Kaggle stuff. Both Tensorflow and PyTorch had issues with CUDA versions and dependencies that weren't immediately fixed with a clean virtualenv, while both Knet.jl and Flux.jl installed flawlessly.
- wdroz 5y agoFor Pytorch and Tensorflow, you can use conda to install them with the right CUDA and cudnn versions.
- kwertzzz 5y agoFor Pytorch, I had no issues with conda. But with Tensorflow from conda, the training process just hangs (consuming 100% of CPU but no GPU resources, despite my GPUs are recognized). I got more luck with installing Tensorflow with pip. Given the fact that Tensorflow documentation does not mention conda, I wondering how well this is supported.
- wdroz 5y agoYou install cudatoolkit from conda then tensorflow with pip.