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They are very, very few cases where getting an expensive GPU - anything more than a Nvidia 1060 would make financial sense. The 1050 is a beginner card is it i

by ktta 9y ago

They are very, very few cases where getting an expensive GPU - anything more than a Nvidia 1060 would make financial sense. The 1050 is a beginner card is it is perfectly fine to learn and run small nets. More importantly, you can decide if machine learning is for you. Then, comes to second investment, which is actually running real-world models. Although the online GPU offering is expensive (you can also look around for cloud GPUs with lower SLA requirements for a lot cheaper) you'd be using them for a lot lesser time. Even if you go with the big three, you can get good pricing if you look around. AWS has a single GPU with 1,536 CUDA cores and 4GB RAM. Looking at the Spot Pricing[1] which is $0.25 an hour, you can get 3000 hours of compute for $750, which is the price of 1080Ti (which is the most cost effective card on the market today). Now, I would say, 3000 hours is more than enough time one needs to run whatever they want to. You can get a lot more if you go with some other service other than the big three. If your usage exceeds that, then you are probably using it for commercial purposes, in which case you need to account for a lot more variables (downtime, maintenance, etc). Then you should also consider the deprecating perf/$ your GPU gives you every year over the new ones in the market - especially since the perf jump is a lot more than what we're seeing with CPUs. If you are doing it for learning, I'd say you're doing something wrong, because you shouldn't need that much power. Also, consider the electricity costs and possible over usage of your computer. [1]:https://aws.amazon.com/ec2/spot/pricing/ https://aws.amazon.com/ec2/spot/pricing/ (check US East N. Virginia)

solomatov 9y ago
There are two problems with your approach: * Setting up machine on AWS is more complicated than locally, and requires some admin skills. * If you use spot instances, you need to handle checkpointing, which requires persistent storage, and all of this stuff requires even more admin skills The goal of a person who starts working with deep learning is to learn deep learning, not how to setup machines, manage them, work with checkpoints, etc. Also, don't forget that there's a large market for used GPUs and you can get real bargains.
- ktta 9y ago
  >Setting up machine on AWS is more complicated than locally, and requires some admin skills. There are tons of guides online where you can learn how to do so in <5 mins. Setting up the computer by yourself is more complicated I would say, and would take a first timer days rather than hours. >If you use spot instances, you need to handle checkpointing Again, not a big deal to learn. >The goal of a person who starts working with deep learning is to learn deep learning, not how to setup machines, manage them, work with checkpoints, etc. I mean, if you're buying a GPU and setting it up, you're more than likely assembling the computer by yourself. You'll also have to maintain it properly. Then you'll have to look for correct drivers and other software which can get frustrating (it did for me). On the other hand, I just could use a step by step process for the AWS instances since they had a few specific types of GPUs and I didn't have to even think, just copy/paste the commands from the webpage to the terminal. There are even AMIs which setup everything for you, which would require even less effort, but I don't trust them so I go with a clean disk. Moreover, learning how to use AWS is a much more valuable skill than putting together computers so time well invested I would say.

by ktta 9y ago

solomatov 9y ago

There are two problems with your approach: * Setting up machine on AWS is more complicated than locally, and requires some admin skills. * If you use spot instances, you need to handle checkpointing, which requires persistent storage, and all of this stuff requires even more admin skills The goal of a person who starts working with deep learning is to learn deep learning, not how to setup machines, manage them, work with checkpoints, etc. Also, don't forget that there's a large market for used GPUs and you can get real bargains.

ktta 9y ago
>Setting up machine on AWS is more complicated than locally, and requires some admin skills. There are tons of guides online where you can learn how to do so in <5 mins. Setting up the computer by yourself is more complicated I would say, and would take a first timer days rather than hours. >If you use spot instances, you need to handle checkpointing Again, not a big deal to learn. >The goal of a person who starts working with deep learning is to learn deep learning, not how to setup machines, manage them, work with checkpoints, etc. I mean, if you're buying a GPU and setting it up, you're more than likely assembling the computer by yourself. You'll also have to maintain it properly. Then you'll have to look for correct drivers and other software which can get frustrating (it did for me). On the other hand, I just could use a step by step process for the AWS instances since they had a few specific types of GPUs and I didn't have to even think, just copy/paste the commands from the webpage to the terminal. There are even AMIs which setup everything for you, which would require even less effort, but I don't trust them so I go with a clean disk. Moreover, learning how to use AWS is a much more valuable skill than putting together computers so time well invested I would say.