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Contrary to the claims there, the CPU does matter: if the network is relatively small, it's easy to get bottle-necked feeding the GPU. Same thing applies to st
by gcp 10y ago
Contrary to the claims there, the CPU does matter: if the network is relatively small, it's easy to get bottle-necked feeding the GPU.
Same thing applies to storage, for the same reasons. There's a reason AMD is selling deep learning cards with Flash drives built in.
The choice of CPU cooler is silly. The CPU chosen is a 65W model, which will be cooled quietly even by the boxed cooler (and we don't need to care about overclocking with a non-K). By his own admission, the rig draws 250W, so the idea that 650W must be cooled is nonsense, and even then, only a part of that is due to the CPU.
It's probably worth looking more closely at the GPU, notably, if that cooler stays quiet when the card is under full load.
You do not need a monitor, keyboard or mouse to use such a machine. You can just ssh into it. You might need to borrow a set to set up the BIOS.
If you "run out of memory for your applications" on the GPU, have you considered simply lowering the mini-batch size? (See, this is why we got a good CPU, it removes the hurt from feeding smaller batches)
- nl 10y agoThere's a reason AMD is selling deep learning cards with Flash drives built in. For those not familiar with them, this is the Radeon Pro SSG[1] This has a built in M2 drive, but this is used as video card memory, NOT main storage. It could possibly allow big (HUGE) models or batches, but doesn't prove fast IO is often a bottleneck. Practically no one[2] is using these for deep learning. They are marketed to the oil and gas modelling and visualization market and notably the product page (linked above) makes no mention of neural networks or deep learning, and it has never been mentioned in AMD's publicity. Yes, it might be good for deep learning. And yet, modern deep models do want more memory. But there is a lot that needs to happen for this to be useful: AMD needs to release something like CuDNN and they need to make sure OpenCL is supported as well as CUDA is. [1] https://arstechnica.com/gadgets/2016/07/amd-radeon-pro-ssg-graphics-card-specs-price-release-date/ https://arstechnica.com/gadgets/2016/07/amd-radeon-pro-ssg-g..., http://www.amd.com/en-us/press-releases/Pages/amd-radeon-pro-2016jul25.aspx http://www.amd.com/en-us/press-releases/Pages/amd-radeon-pro... [2] I'm sure you'll find someone. But show me a published paper or any kind, or even benchmarks showing the use of the extra memory somewhere.
- gcp 10y agodoesn't prove fast IO is often a bottleneck. It's not often a bottleneck. In fact it usually isn't. But when it is, you're left wondering why you didn't get an SSD. They're cheap enough now.
- deepnotderp 10y agoMIOpen is AMD's cuDNN alternative.
- rockdoe 10y agoWhich does not actually exist. It's announced but unreleased.