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Whenever I see code for neural networks in caffe/torch/theano, it bothers me a lot that its not easy to get them up and running on windows. I can't believe MS i

Whenever I see code for neural networks in caffe/torch/theano, it bothers me a lot that its not easy to get them up and running on windows. I can't believe MS is missing this boat. I believe this field is exploding right now and the only one seem to be aligned is NVIDIA. MS has sponsored development of nodejs for windows before. I'm hoping they will do something similar for these frameworks soon.

ogrisel 11y ago
Intel is playing catch up with Xeon Phi and OpenCL with open source projects like: https://01.org/beignet https://01.org/beignet and https://github.com/01org/idlf https://github.com/01org/idlf . It's not at the level of being as fast as cuDNN nor integrated in major deep learning libraries but at least we can expect some competition in the coming years.
- ilurk 11y ago
  That doesn't sound like a worthwhile approach to me. Xeon are server CPUs. So that means that whoever bothers buying Xeons with scientific computing in mind may as well go all the way and buy nVidia GPUs instead. So instead of making that framework available to all Intel Haswell and newer families and try to persuade the customer from having to buy nVidia GPUs, they cut themselves short.
  - sp332 11y ago
    The Xeon Phi is not a Xeon. It's a co-processor. https://www-ssl.intel.com/content/www/us/en/processors/xeon/xeon-phi-detail.html https://www-ssl.intel.com/content/www/us/en/processors/xeon/... The main advantage is that you can run almost-normal x86 code on it. Each core gets its own cache, so it's not really the same as programming for GPUs.
nl 11y ago
NVidia could do a lot better. Getting CuDNN working on OSX (or Linux) isn't exactly a trivial task.
- ogrisel 11y ago
  They should start by making the library download-able without a registration form so that people could provide scripted installation for it. The registration form is the reason it's not included in the dl-machine Amazon EC2 image for instance: https://github.com/deeplearningparis/dl-machine https://github.com/deeplearningparis/dl-machine
albertzeyer 11y ago
Theano should work on Windows. And the community is very friendly. So, in case of install trouble, just ask them. Or better: help to make it simpler. (If it is not a principle Windows thing, like missing package manager or so.) Of course, many Theano-based scripts you will find somewhere are probably only tested on a very specialized environment, and this might expect some Unix-like environment. But this is something which you cannot really solve, other than contribute to the script and fix it. About the related Nvidia CUDA discussion: OpenCL support by Theano is in the works. Not sure how far it is.

ogrisel 11y ago

Intel is playing catch up with Xeon Phi and OpenCL with open source projects like: https://01.org/beignet https://01.org/beignet and https://github.com/01org/idlf https://github.com/01org/idlf . It's not at the level of being as fast as cuDNN nor integrated in major deep learning libraries but at least we can expect some competition in the coming years.

ilurk 11y ago
That doesn't sound like a worthwhile approach to me. Xeon are server CPUs. So that means that whoever bothers buying Xeons with scientific computing in mind may as well go all the way and buy nVidia GPUs instead. So instead of making that framework available to all Intel Haswell and newer families and try to persuade the customer from having to buy nVidia GPUs, they cut themselves short.
- sp332 11y ago
  The Xeon Phi is not a Xeon. It's a co-processor. https://www-ssl.intel.com/content/www/us/en/processors/xeon/xeon-phi-detail.html https://www-ssl.intel.com/content/www/us/en/processors/xeon/... The main advantage is that you can run almost-normal x86 code on it. Each core gets its own cache, so it's not really the same as programming for GPUs.

nl 11y ago

NVidia could do a lot better. Getting CuDNN working on OSX (or Linux) isn't exactly a trivial task.

ogrisel 11y ago
They should start by making the library download-able without a registration form so that people could provide scripted installation for it. The registration form is the reason it's not included in the dl-machine Amazon EC2 image for instance: https://github.com/deeplearningparis/dl-machine https://github.com/deeplearningparis/dl-machine

albertzeyer 11y ago

Theano should work on Windows. And the community is very friendly. So, in case of install trouble, just ask them. Or better: help to make it simpler. (If it is not a principle Windows thing, like missing package manager or so.) Of course, many Theano-based scripts you will find somewhere are probably only tested on a very specialized environment, and this might expect some Unix-like environment. But this is something which you cannot really solve, other than contribute to the script and fix it. About the related Nvidia CUDA discussion: OpenCL support by Theano is in the works. Not sure how far it is.