5 ms·

If by "super fast deep learning machine" you actually mean, mid tier gaming computer. Uh, sure. Don't spend more on an ITX board, when you can fit 4x to 7x th

If by "super fast deep learning machine" you actually mean, mid tier gaming computer. Uh, sure. Don't spend more on an ITX board, when you can fit 4x to 7x the video cards in a full size ATX computer using pci-e risers, while paying less for the board. Don't lose 5 percent of your cpu overclock or more by having an itx friendly cooler instead of a D15 noctua or better. Choose your video card wisely, AMD does some things better than NVIDIA depending on what software you're running. If you chose an ITX platform for deep learning fun, uh, you should really add the couple shoeboxes extra space to your platform and have 4x-7x the power available to upgrade into.

siscia 10y ago
Try to bring good in the conversation. What piece you would have use? Why? What tradeoffs you have considered? You sound expert in the field, try to share your knowledge with the community in a constructive way so that we can all benefit from it. I develop software for living and still I haven't any clue of what you said, while I followed quite well the article and I thought he was making reasonable choice. Please show me better.
- crawfordcomeaux 10y ago
  I'd like to second this request and note it took me years to figure out that people saying "focus on the positive" in this context would be satisfied by me phrasing things in terms of what to do rather than what not to do. Concrete examples are key for this approach.
- croon 10y ago
  Not parent, but I've built my own computers for almost 20 years. As the articles author himself questions, he should have gotten the marginally more expensive CPU, and definitely the GPU with more RAM. * The overclockable CPU doesn't just mean that you very easily could get a 10%+ performance boost without much work, but also that you often (depending on your specific chip) can lower the voltage and make it run much cooler/quieter, which is something I increasingly care about if I'm using it a lot. * He writes that fitting the model in RAM is basically the most important part, but then saves less than a dinner out by basically halving the RAM on the GPU he bought. The chip is otherwise the same though, so performance is only dependent on whether you fill that RAM or not. * The Noctua D15 the parent mentioned is a CPU cooler where Noctua is a long standing high performant brand, and D15 is a specific model with a 15 inch fan and comparable sized heat sink. There are of course other brands, but I myself also usually end up with Noctuas. The reason it's important is that however fast you can dissipate heat from the cpu/case, the less chance of throttling, and the larger headroom for potential overclocks you get. Airflow and room for larger heatsinks is also why he recommended not going for an ITX. A linked benefit is again the potential for a quieter system. I haven't gone much into ML (yet), but I currently have a system with: * I7 6700K (the difference to I5 6600K being higher base clock and hyperthreading, which is more important to computational work than to gaming, so if you have the money, definitely go for the I7) * 32GB DDR4 (as author mentioned, RAM is cheap). The clock/timings on RAM isn't really as important, but try to find the best you can find for a given price point. * An Nvidia GTX 1080: It's not Titan X or Z, but almost, at less price. It definitely blows the budget for a $1000 system, but I agree that the entire 10 series is good. If the limit is a firm $1000, I would get something like this: https://pcpartpicker.com/list/XHV9Fd https://pcpartpicker.com/list/XHV9Fd And if more funds is available, I'd get more storage and RAM, then a better CPU, then a better GPU, then maybe bump the chassis up to an R5 (same brand), possibly another motherboard. In that order. There's always something better, so you compromise based on budget.
  - IanCal 10y ago
    I've got a near identical build, and my process was the same as you. I added a decent pcie nvme drive, and spent more than I guess I could have done on a motherboard that supports up to 128G ram so I can extend it later. I'm waiting for ram to drop in price a bit, or to hit a problem where I need more than 32 sooner, before bumping that up and probably adding more storage. It's been great sshing in from my laptop, submitting a job that completes far more quickly and keeping my laptop cool.
    - croon 10y ago
      I kept my old 512GB Samsung 850 Pro, but will definitely get an nvme when I need more space/speed. Getting another 32 RAM will hold me over until I'll build a new one, so that part I'm not worried about. Yeah, it's supremely fast, my only regret is not having enough time to do something fun with it. For work I'm stuck with the clients platform approved machine, which is not what I would've picked. Tough to complain, but if I'm ever between contracts, I'll likely get into some fun project.
  - deleted 10y ago
    [deleted]
  - hermiti 10y ago
    I have a machine that I am using for deep learning and it has 32GB of ECC RAM paired with a Xeon CPU w/ Quadro, and that 32GB of RAM is gone almost instantly. Now I'm looking at building another machine as it has gotten to the point where I am spending a great deal of time waiting. I would be interested to see what other people are using for their setups, and how that can differ for things like high-resolution style transfer or generic neural networks, etc...and at what point they have to switch from geforce/quadro cards to tesla.
  - mamcx 10y ago
    Was years ago when I build my last PC and I'm out of the game. I'm tempted in build a hackintosh: https://www.tonymacx86.com/threads/hackintosh-cutting-edge-kaby-lake-nvme-ddr4-4k-viable.214249/#post-1433129 https://www.tonymacx86.com/threads/hackintosh-cutting-edge-k... - Intel i7 Kaby Lake - No decided on motherboard. The one that cause me less trouble (for hackintosh) is fine. - GTI 750ti (have) or buy a pascal nvidia. - NVMe drive if possible - 32 GB RAM. - Probably a Thermaltake CORE P3 case. Not decided. I was thinking in use a Liquid Cooler but wonder if the Noctua could be better/less noise?
rspeer 10y ago
> Choose your video card wisely, AMD does some things better than NVIDIA depending on what software you're running. Deep learning toolkits basically have two modes of operation: the CPU way, and the proprietary NVIDIA way. There is no point to putting an AMD chip in a machine you hope to use for deep learning. Some toolkits may go through the motions of supporting AMD via OpenCL, but that's not going to be the case that they make sure works well, or works at all. This is a problem, as NVIDIA is awful at maintaining drivers, results are being published based on "well, my NVIDIA black box decided to do this", and it contributes to deep learning veering toward a local maximum. But specifically choosing to do deep learning with an AMD chip is a pointless sacrifice.

siscia 10y ago

Try to bring good in the conversation. What piece you would have use? Why? What tradeoffs you have considered? You sound expert in the field, try to share your knowledge with the community in a constructive way so that we can all benefit from it. I develop software for living and still I haven't any clue of what you said, while I followed quite well the article and I thought he was making reasonable choice. Please show me better.

crawfordcomeaux 10y ago
I'd like to second this request and note it took me years to figure out that people saying "focus on the positive" in this context would be satisfied by me phrasing things in terms of what to do rather than what not to do. Concrete examples are key for this approach.
croon 10y ago
Not parent, but I've built my own computers for almost 20 years. As the articles author himself questions, he should have gotten the marginally more expensive CPU, and definitely the GPU with more RAM. * The overclockable CPU doesn't just mean that you very easily could get a 10%+ performance boost without much work, but also that you often (depending on your specific chip) can lower the voltage and make it run much cooler/quieter, which is something I increasingly care about if I'm using it a lot. * He writes that fitting the model in RAM is basically the most important part, but then saves less than a dinner out by basically halving the RAM on the GPU he bought. The chip is otherwise the same though, so performance is only dependent on whether you fill that RAM or not. * The Noctua D15 the parent mentioned is a CPU cooler where Noctua is a long standing high performant brand, and D15 is a specific model with a 15 inch fan and comparable sized heat sink. There are of course other brands, but I myself also usually end up with Noctuas. The reason it's important is that however fast you can dissipate heat from the cpu/case, the less chance of throttling, and the larger headroom for potential overclocks you get. Airflow and room for larger heatsinks is also why he recommended not going for an ITX. A linked benefit is again the potential for a quieter system. I haven't gone much into ML (yet), but I currently have a system with: * I7 6700K (the difference to I5 6600K being higher base clock and hyperthreading, which is more important to computational work than to gaming, so if you have the money, definitely go for the I7) * 32GB DDR4 (as author mentioned, RAM is cheap). The clock/timings on RAM isn't really as important, but try to find the best you can find for a given price point. * An Nvidia GTX 1080: It's not Titan X or Z, but almost, at less price. It definitely blows the budget for a $1000 system, but I agree that the entire 10 series is good. If the limit is a firm $1000, I would get something like this: https://pcpartpicker.com/list/XHV9Fd https://pcpartpicker.com/list/XHV9Fd And if more funds is available, I'd get more storage and RAM, then a better CPU, then a better GPU, then maybe bump the chassis up to an R5 (same brand), possibly another motherboard. In that order. There's always something better, so you compromise based on budget.
- IanCal 10y ago
  I've got a near identical build, and my process was the same as you. I added a decent pcie nvme drive, and spent more than I guess I could have done on a motherboard that supports up to 128G ram so I can extend it later. I'm waiting for ram to drop in price a bit, or to hit a problem where I need more than 32 sooner, before bumping that up and probably adding more storage. It's been great sshing in from my laptop, submitting a job that completes far more quickly and keeping my laptop cool.
  - croon 10y ago
    I kept my old 512GB Samsung 850 Pro, but will definitely get an nvme when I need more space/speed. Getting another 32 RAM will hold me over until I'll build a new one, so that part I'm not worried about. Yeah, it's supremely fast, my only regret is not having enough time to do something fun with it. For work I'm stuck with the clients platform approved machine, which is not what I would've picked. Tough to complain, but if I'm ever between contracts, I'll likely get into some fun project.
- deleted 10y ago
  [deleted]
- hermiti 10y ago
  I have a machine that I am using for deep learning and it has 32GB of ECC RAM paired with a Xeon CPU w/ Quadro, and that 32GB of RAM is gone almost instantly. Now I'm looking at building another machine as it has gotten to the point where I am spending a great deal of time waiting. I would be interested to see what other people are using for their setups, and how that can differ for things like high-resolution style transfer or generic neural networks, etc...and at what point they have to switch from geforce/quadro cards to tesla.
- mamcx 10y ago
  Was years ago when I build my last PC and I'm out of the game. I'm tempted in build a hackintosh: https://www.tonymacx86.com/threads/hackintosh-cutting-edge-kaby-lake-nvme-ddr4-4k-viable.214249/#post-1433129 https://www.tonymacx86.com/threads/hackintosh-cutting-edge-k... - Intel i7 Kaby Lake - No decided on motherboard. The one that cause me less trouble (for hackintosh) is fine. - GTI 750ti (have) or buy a pascal nvidia. - NVMe drive if possible - 32 GB RAM. - Probably a Thermaltake CORE P3 case. Not decided. I was thinking in use a Liquid Cooler but wonder if the Noctua could be better/less noise?

rspeer 10y ago

> Choose your video card wisely, AMD does some things better than NVIDIA depending on what software you're running. Deep learning toolkits basically have two modes of operation: the CPU way, and the proprietary NVIDIA way. There is no point to putting an AMD chip in a machine you hope to use for deep learning. Some toolkits may go through the motions of supporting AMD via OpenCL, but that's not going to be the case that they make sure works well, or works at all. This is a problem, as NVIDIA is awful at maintaining drivers, results are being published based on "well, my NVIDIA black box decided to do this", and it contributes to deep learning veering toward a local maximum. But specifically choosing to do deep learning with an AMD chip is a pointless sacrifice.