Open some-guy1 opened 6 years ago
Sorry for long delay. I think it should be possible to make it work using the procedure in the README. I should have access to a Windows machine with GPU next week, I'll give it a try but cannot commit on anything. Have you tried building it? Where did it fail?
Well I have been unable to get Rtools to work properly. I have never built an R package and I dont know what I am doing. Your CPU distribution works great and exactly as expected. However, when I try to follow the instructions to build my own, "R CMD INSTALL" always says it failed to install and deletes the directory.
I am hoping you could periodically also output a GPU version of MxnetR for the latest most compatible CUDA (i.e. 9.0.x, or whatever it needs to be).
If I can compile the GPU version, I'll add it and let you know. In the meantime, an alternative option could be to run through a docker image. I maintain a CPU and GPU images here: https://hub.docker.com/r/jeremiedb/dockerml/, tag: gpu-openblas. Only used the cpu version on windows machine, but GPU should work as well, using nvidia-docker.
Sorry for slow response, I have been ultra busy. I have never used a docker before. I will look for a tutorial.
Hi, it appears like nvidia-docker isn't supported right now on windows.
However, good news is that I just built a mxnet 1.2.0 (as of April 25) GPU version, based on CUDA 9.1 and cudnn7. Here's the download link:
install.packages("https://s3.ca-central-1.amazonaws.com/jeremiedb/share/mxnet/GPU/mxnet.zip", repos = NULL)
:-O excellent. I will try it this weekend!
Ok I gave it a try. Seems to have installed successfully and a super simple test case works (i.e. make a small matrix with zeros through the GPU). So that is good.
But when I try to run an actual mx.model.FeedForward.create
I am getting "cudaMalloc failed: out of memory"
I set the batch size to 1 and I still get the error.
My GPU Card is: GTX 1060 with 6GB of memory My total RAM for the computer is 32GB.
Do I need to change some sort of configuration file to get this to work?
Hello, sorry for long delay. About memory consumption, there's been an ongoing issue with the optimizers that should be fixed through this PR: https://github.com/apache/incubator-mxnet/pull/11374
I'll probably update the Windows GPU package within a week to integrate that memory fix.
Ok gotchya. Although I am training a GAN, so I am using quite a bit of memory. Could be my fault.
Hi, really appreciate you keeping this up to date! Thanks!!
Is there any way to get gpu support for Windows with the latest builds?