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Linode GPU Instances

172 points by gr2020 7y ago

minimaxir 7y ago
Huh. Given that cheap cloud GPUs are nowadays sought for training AI, launching with a Workstation-oriented GPU is an odd product decision.
- ksec 7y ago
  Are there any difference? Seems to support CUDA as well, I don't see anything wrong with it. Also seems to be a lot cheaper than AWS counterpart.
  - minimaxir 7y ago
    It seems like a Quadro RTX 6000 is comparable performance-wise to a P100 (https://askgeek.io/en/gpus/vs/NVIDIA_Quadro-RTX-6000-vs-NVIDIA_Tesla-P100-SXM2 https://askgeek.io/en/gpus/vs/NVIDIA_Quadro-RTX-6000-vs-NVID...), although there are no tests for the ML angle. A P100 on GCP is $1.46/hr alone, so maybe Linode is a good deal if the performance is indeed comparable.
    - elabajaba 7y ago
      RTX 6000 is significantly faster than a P100 outside of FP64, and is the fastest or 2nd fastest GPU outside of FP64 work [1] (the GV100 is sometimes faster, sometimes slower than the RTX 6000 but costs more). For FP64, GV100 based GPUS are quite a bit faster than P100s. Also, you should really ignore pretty much all of the comparison sites that show up when you search for computer component comparisons as they're nearly all awful. The one you posted doesn't show a single benchmark comparison between them, and compares numbers like clock speed which isn't comparable between architectures, or memory clock speed instead of memory bandwidth leading to the laughable conclusion that the RTX 6000 has "9.9x more memory clock speed: 14000 MHz vs 1408 MHz" vs the P100 when the P100 uses HBM2 and has 732.2 GB/s vs 672.0 GB/s of actual memory bandwidth. [1] https://www.reddit.com/r/hardware/comments/9xx6cz/nvidia_quadro_rtx_50006000_teardown_review/ https://www.reddit.com/r/hardware/comments/9xx6cz/nvidia_qua...
      - svd4anything 7y ago
        https://www.techpowerup.com/gpu-specs/quadro-rtx-6000.c3307 https://www.techpowerup.com/gpu-specs/quadro-rtx-6000.c3307 Has this section: Theoretical Performance Pixel Rate 169.9 GPixel/s Texture Rate 509.8 GTexel/s FP16 (half) performance 32.62 TFLOPS (2:1) FP32 (float) performance 16.31 TFLOPS FP64 (double) performance 509.8 GFLOPS (1:32) Perhaps for at least rough performance comparisons it is a good start. My impression the current favorite card by DIY types is an RTX 2080 Ti. https://www.techpowerup.com/gpu-specs/geforce-rtx-2080-ti.c3305 https://www.techpowerup.com/gpu-specs/geforce-rtx-2080-ti.c3... However I think nvidia will take legal action against any service provider trying to use those in a cloud or server offering.
bufferoverflow 7y ago
Can you rent them by minute?
- perennate 7y ago
  Linode bills per-hour: https://www.linode.com/docs/platform/billing-and-support/billing-and-payments/ https://www.linode.com/docs/platform/billing-and-support/bil...
ilaksh 7y ago
Looks amazing. Linode has worked really well for me over the years. One thing I noticed when recently trying to get a GPU cloud instance, the high core counts are usually locked until you put in a quota increase. Then sometimes they want to call you. So I wonder if Linode will have to do that or if they can figure out another way to handle it that would be more convenient. I also wonder if Linode could somehow get Windows on these? I know they generally don't do anything other than Linux though. My graphics project where I am trying to run several hundred ZX Spectrum libretro cores on one screen only runs on Windows.
keytarsolo 7y ago
That pricing isn't too bad. They come with decent SSD storage too, which is key for the large datasets that make a GPU instance worthwhile. Linode skews more towards smaller scale customers with many of their offerings so I think the GPUs here make sense. The real test will be how often they upgrade them and what they upgrade them too.
thenightcrawler 7y ago
Isn't AWS cheaper? edit: could be wrong thought I read of AWS being .65 dollars an hour for deep learning GPU use. edit2: Did a quick look, the .65 dollars doesn't include the actual instance, so its around 1.8 an hour on the low end, I think this cheaper.
- perennate 7y ago
  p2.xlarge comes with an NVIDIA Tesla K80 GPU for $0.90/hr, but this is now an "old" GPU and the RTX Quadro 6000 should have much higher performance (but I was unable to find any machine learning benchmarks). p3.2xlarge has NVIDIA Tesla V100 GPU which is NVIDIA's most recent deep learning GPU, but it's $3.06/hr. That said, AWS is among the most expensive providers if you just need a deep learning GPU (but obviously AWS offers a lot of other useful things). For example, OVH Public Cloud has Tesla V100 for $2.66/hr. And comparable NVIDIA GPUs that are not "datacenter-grade" should be even cheaper; AWS, GCP, Azure, etc. are unable to offer them because of contracts when they buy e.g. the Tesla V100.
  - zachruss92 7y ago
    The K80s are super outdated now. Google used to offer them for free for 12hrs a day on their Colab platform, but they upgraded them to using the Tesla T4s. Note you can get a K80 on GCP (unreserved) for $.45/hr. This is a good deal.
  - tarasmatsyk 7y ago
    K80 is the crappiest cards I've used last year. For sure it was a good choice 2 years ago, but now you are better to upgrade as any new desktop card is better than K80
- tarasmatsyk 7y ago
  It depends, for full-time usage, it is a bit more expensive, I think it is a matter of a few hundred, probably less. We've happily migrated from AWS as only one GPU instance cost us near 1k/m. BTW, the newest and the only available GPU instances now should be better RTX6000 even being more expensive.
coherentpony 7y ago
Does anybody know if there are any cloud instances with AMD GPUs?
- azinman2 7y ago
  What would you want it for over nvidia in the cloud?
  - noir_lord 7y ago
    Testing if nothing else, I'd you are shipping to be people running AMD GPUs then that would be useful without having to buy a card and another machine for it to go in
- jamesblonde 7y ago
  GPUEater do, i think. Right now, though, they are a viable option for an on-premise use case where you have a budget of say a $100k dollars or more and need a huge amount of compute and have larger models to train. The Vega R7 gives you 16GB Ram (11GB in the 2080Ti) and is just slightly lower performance than the 2080Ti (322 vs 302 images/sec for resnet-50 from here: https://www.youtube.com/watch?v=neb1C6JlEXc https://www.youtube.com/watch?v=neb1C6JlEXc ). And you have servers with PCI-4.0 support, so that distributed training scales (yes, 2080-Ti supports nvlink, but nvlink servers cost way more). Simple math example. A PCI-4.0 server with 256GB Ram and 8xVegaR7 should cost around $10K. With a couple of switches and racks, you can get 100s of GPUs for just a couple of hundred thousand dollars (note, only 2 GPU servers per rack for now is normal, otherwise you have to buy non-commodity racks with high power draw).
MuffinFlavored 7y ago
Can these be used for crypto mining at any level of efficiency? I was able to mine GRLC back in the day on AWS spot instances at a VERY mild degree of profitability.
- elabajaba 7y ago
  Doubtful, since these are just fully unlocked TU102 GPUs (same as the Titan RTX, 2080ti is the same TU102 GPU but partially locked at 4352 cores vs 4608 for the Quadro RTX 6000/8000 and Titan RTX). If you could be profitable with this at $1000/month then people would be flocking out to buy 2080tis for $1100 and getting 90-95% of the hashrate.
- walrus01 7y ago
  not really, most cryptocurrency is at the stage where the only thing effective is a combination of custom ASICs and nearly free electricity. About twelve months ago I looked into mining ethereum with state of the art GPUs and it would not have had a reasonable ROI unless I was literally paying $0.00 per kWh. And that was before its value per coin dropped a lot.
  - kohtatsu 7y ago
    Let's replace baseboard heaters with cryptominers.
  - latchkey 7y ago
    When the value dropped, the network hashrate dropped and difficulty went down so things actually became profitable again. The best time to mine is during the drops, not the highs, unless you follow buy high, sell low and don't believe the market will correct for the better again (which it has). Of course, it depends on electricity prices, but it is profitable to mine ethereum, especially if you know how to tune the cards to maximize hash/consumption. That said, mining is competitive and difficult and unless you are going to go really large, don't bother. If you are interested in learning about it, definitely experiment though don't expect to make a lot of money.
- tootahe45 7y ago
picozeta 7y ago
I would go with Hetzner: https://www.hetzner.com/dedicated-rootserver/ex51-ssd-gpu https://www.hetzner.com/dedicated-rootserver/ex51-ssd-gpu GTX1080 for 100$ a month. Grantend, it is older, but it still works for DL. Let's say you do 10 experiments a month for ~20 hours. Thats 0.5$/hour and I don't think it is 3 times faster. If you then want to do even more learning the price goes even down. //DISCLAIMER: I do not work for them, but used it for DL in the past and it was for sure cheaper than GCP or AWS. If you have to do lots of experiments (>year) go with your own hardware, but do not underestimate the convenience of >100MByte/s if you download many big training sets.
- icelancer 7y ago
  I have one of these instances. It's awesome and I recommend it highly.
- svd4anything 7y ago
  How does data in/out work in practice with them? I see this 4 Tbit bandwidth but do you happen to know what that translates to and what happens if you exceed that? Also check availability shows a 5 day wait current: “EX51-SSD-GPU for Falkenstein (FSN1): Due to very high demand for these server models, its current setup time is approximately up to 5 workdays.*” Or maybe there are other regions/dcs.
  - indalo 7y ago
    I have like 18 of their auction servers that are unmetered at 1gbps and really make that bandwidth sweat. I've never had issues honestly, and they've never tried to dreamhost me. I love it.
  - picozeta 7y ago
    So far I did not reach that limit (I used it to train networks for image segmentation) so I had mostly ingress and only downloaded large amounts to the machine not from it (which is free like with most providers). But you can just ask them. I have to say that not everything was 100% smooth - sometimes the proprietary NVidia driver crashed (you have to use the right CUDA and driver combination) my Linux instance and hanged the system, so I had to hard-reboot it (which is supported via their admin console) which takes some minutes. However that's not their fault as I heard the driver is a big pile of crap shit anyway because NVidia is too embarrassed to post it to LKML.
ThomWilhelm3 7y ago
Will this profitably mine bitcoins? :p
- beatgammit 7y ago
  No.
dkobran 7y ago
Interesting to see another cloud provider go with Quadro chips. NVIDIA repackages the same silicon under several different brands (GeForce, Quadro, GRID, Tesla) and we (https://paperspace.com https://paperspace.com) have found Quadro to offer the best price/performance value. Despite minor performance characteristics, such as FP16 support in the Tesla family, Quadros can run all of the same workloads eg graphics, HPC, Deep Learning etc. If you’re interested in a similar instance for less $/hr, check out the Paperspace P6000.
m0zg 7y ago
Still way too much money when a 2x 2080Ti comparably specced machine under my desk costs less than 2.5 months of their billing rate, and 4x 1080Ti servers in my garage cost about 1 month of their 4-GPU machine _and_ have more SSD storage. This pricing is totally insane, especially if not billed per-minute (which in Linode's case it is not) and if there are no cheaper preemptible/spot instances.
- svd4anything 7y ago
  I’m starting to think one can adopt the simple rule of switch to a DIY build whenever there enough work to keep a GPU busy for 2 months, otherwise if the workload is intermittent then better strategy is leasing, especially considering the purchase cost/performance is constantly dropping.
  - dillonmckay 7y ago
    It would seem there could be a market for multi-month rentals of a ML/gaming rig, with return shipping/packaging?
- trey-jones 7y ago
  What's the cost for power? Serious question, and I'm not suggesting that this cost should account for a large percentage of the price, but genuinely curious. If your GPUs are working every hour of the month for you, how much is it costing you in electricity?
  - m0zg 7y ago
    Quad GPU machines draw about 1.3KW each on average when under load. That's about $100/mo where I live, assuming they're 100% loaded 24x7 for the entire month. Realistically it's less. So it's not free, but it's not a crazy amount either.
deleted 7y ago
[deleted]
Who_me 7y ago
Hey peeps full disclosure I work as one of Linode's RnD engineers. I want to try to get to as many of these as I can. One of the biggest questions is why the Quadro RTX 6000? Few things: 1. Cost it has the same performance as the 8000. The difference is 8 more GB of RAM that comes at a steep premium. Cost is important to us as it allows us to be at a more affordable price point. 2. We have all heard or used the Tesla V100, and it's a great card. The biggest issue is that it's expensive. So one of the things that caught our eye is the RTX 6000 has a fast Single-Precision Performance, Tensor Performance, and INT8 performance. Plus the Quadro RTX supports INT4. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-6000-us-nvidia-704093-r4-web.pdf https://www.nvidia.com/content/dam/en-zz/Solutions/design-vi... https://images.nvidia.com/content/technologies/volta/pdf/tesla-volta-v100-datasheet-letter-fnl-web.pdf https://images.nvidia.com/content/technologies/volta/pdf/tes... Yes, these are manufactures numbers, but it caused us pause. As always, your mileage may vary. 3. RT cores. This is the first time (TMK) that a cloud provider is bringing RT cores into the market. There are many use cases for RT that have yet to be explored. What will we come up with as a community?! Now with all that being said, there is a downside, FP64 aka double precision. The Tesla V100 does this very well, whereas the Quadro RTX 6000 does poorly in comparison. We think although those workloads are important, the goal was to find a solution that fits a vast majority of the use cases. So is the marketing true to get the most out of MI/AI/Etc? Do you need a Tesla to get the best performance? Or is the Tesla starting to show its age? Give the cards a try I think you'll find these new RTX Quadros with Turning architecture are not the same as the Quadros of the past.
- tntn 7y ago
  > This is the first time (TMK) that a cloud provider is bringing RT cores into the market. Your knowledge is incomplete. T4 has been available in google cloud for many months.
  - Who_me 7y ago
    I stand corrected thank you!
- jamesblonde 7y ago
hmart 7y ago
I love Linode support. There are cheaper places but I have my Key VPSs there.
zonidjan 7y ago
Oh, hey! It only adds 1/5th of the GPU's purchase price.

172 points by gr2020 7y ago

Huh. Given that cheap cloud GPUs are nowadays sought for training AI, launching with a Workstation-oriented GPU is an odd product decision.

ksec 7y ago
Are there any difference? Seems to support CUDA as well, I don't see anything wrong with it. Also seems to be a lot cheaper than AWS counterpart.
- minimaxir 7y ago
  It seems like a Quadro RTX 6000 is comparable performance-wise to a P100 (https://askgeek.io/en/gpus/vs/NVIDIA_Quadro-RTX-6000-vs-NVIDIA_Tesla-P100-SXM2 https://askgeek.io/en/gpus/vs/NVIDIA_Quadro-RTX-6000-vs-NVID...), although there are no tests for the ML angle. A P100 on GCP is $1.46/hr alone, so maybe Linode is a good deal if the performance is indeed comparable.
  - elabajaba 7y ago
    RTX 6000 is significantly faster than a P100 outside of FP64, and is the fastest or 2nd fastest GPU outside of FP64 work [1] (the GV100 is sometimes faster, sometimes slower than the RTX 6000 but costs more). For FP64, GV100 based GPUS are quite a bit faster than P100s. Also, you should really ignore pretty much all of the comparison sites that show up when you search for computer component comparisons as they're nearly all awful. The one you posted doesn't show a single benchmark comparison between them, and compares numbers like clock speed which isn't comparable between architectures, or memory clock speed instead of memory bandwidth leading to the laughable conclusion that the RTX 6000 has "9.9x more memory clock speed: 14000 MHz vs 1408 MHz" vs the P100 when the P100 uses HBM2 and has 732.2 GB/s vs 672.0 GB/s of actual memory bandwidth. [1] https://www.reddit.com/r/hardware/comments/9xx6cz/nvidia_quadro_rtx_50006000_teardown_review/ https://www.reddit.com/r/hardware/comments/9xx6cz/nvidia_qua...
    - svd4anything 7y ago
      https://www.techpowerup.com/gpu-specs/quadro-rtx-6000.c3307 https://www.techpowerup.com/gpu-specs/quadro-rtx-6000.c3307 Has this section: Theoretical Performance Pixel Rate 169.9 GPixel/s Texture Rate 509.8 GTexel/s FP16 (half) performance 32.62 TFLOPS (2:1) FP32 (float) performance 16.31 TFLOPS FP64 (double) performance 509.8 GFLOPS (1:32) Perhaps for at least rough performance comparisons it is a good start. My impression the current favorite card by DIY types is an RTX 2080 Ti. https://www.techpowerup.com/gpu-specs/geforce-rtx-2080-ti.c3305 https://www.techpowerup.com/gpu-specs/geforce-rtx-2080-ti.c3... However I think nvidia will take legal action against any service provider trying to use those in a cloud or server offering.

bufferoverflow 7y ago

Can you rent them by minute?

perennate 7y ago
Linode bills per-hour: https://www.linode.com/docs/platform/billing-and-support/billing-and-payments/ https://www.linode.com/docs/platform/billing-and-support/bil...

ilaksh 7y ago

Looks amazing. Linode has worked really well for me over the years. One thing I noticed when recently trying to get a GPU cloud instance, the high core counts are usually locked until you put in a quota increase. Then sometimes they want to call you. So I wonder if Linode will have to do that or if they can figure out another way to handle it that would be more convenient. I also wonder if Linode could somehow get Windows on these? I know they generally don't do anything other than Linux though. My graphics project where I am trying to run several hundred ZX Spectrum libretro cores on one screen only runs on Windows.

keytarsolo 7y ago

That pricing isn't too bad. They come with decent SSD storage too, which is key for the large datasets that make a GPU instance worthwhile. Linode skews more towards smaller scale customers with many of their offerings so I think the GPUs here make sense. The real test will be how often they upgrade them and what they upgrade them too.

thenightcrawler 7y ago

Isn't AWS cheaper? edit: could be wrong thought I read of AWS being .65 dollars an hour for deep learning GPU use. edit2: Did a quick look, the .65 dollars doesn't include the actual instance, so its around 1.8 an hour on the low end, I think this cheaper.

perennate 7y ago
p2.xlarge comes with an NVIDIA Tesla K80 GPU for $0.90/hr, but this is now an "old" GPU and the RTX Quadro 6000 should have much higher performance (but I was unable to find any machine learning benchmarks). p3.2xlarge has NVIDIA Tesla V100 GPU which is NVIDIA's most recent deep learning GPU, but it's $3.06/hr. That said, AWS is among the most expensive providers if you just need a deep learning GPU (but obviously AWS offers a lot of other useful things). For example, OVH Public Cloud has Tesla V100 for $2.66/hr. And comparable NVIDIA GPUs that are not "datacenter-grade" should be even cheaper; AWS, GCP, Azure, etc. are unable to offer them because of contracts when they buy e.g. the Tesla V100.
- zachruss92 7y ago
  The K80s are super outdated now. Google used to offer them for free for 12hrs a day on their Colab platform, but they upgraded them to using the Tesla T4s. Note you can get a K80 on GCP (unreserved) for $.45/hr. This is a good deal.
- tarasmatsyk 7y ago
  K80 is the crappiest cards I've used last year. For sure it was a good choice 2 years ago, but now you are better to upgrade as any new desktop card is better than K80
tarasmatsyk 7y ago
It depends, for full-time usage, it is a bit more expensive, I think it is a matter of a few hundred, probably less. We've happily migrated from AWS as only one GPU instance cost us near 1k/m. BTW, the newest and the only available GPU instances now should be better RTX6000 even being more expensive.

coherentpony 7y ago

Does anybody know if there are any cloud instances with AMD GPUs?

azinman2 7y ago
What would you want it for over nvidia in the cloud?
- noir_lord 7y ago
  Testing if nothing else, I'd you are shipping to be people running AMD GPUs then that would be useful without having to buy a card and another machine for it to go in
jamesblonde 7y ago
GPUEater do, i think. Right now, though, they are a viable option for an on-premise use case where you have a budget of say a $100k dollars or more and need a huge amount of compute and have larger models to train. The Vega R7 gives you 16GB Ram (11GB in the 2080Ti) and is just slightly lower performance than the 2080Ti (322 vs 302 images/sec for resnet-50 from here: https://www.youtube.com/watch?v=neb1C6JlEXc https://www.youtube.com/watch?v=neb1C6JlEXc ). And you have servers with PCI-4.0 support, so that distributed training scales (yes, 2080-Ti supports nvlink, but nvlink servers cost way more). Simple math example. A PCI-4.0 server with 256GB Ram and 8xVegaR7 should cost around $10K. With a couple of switches and racks, you can get 100s of GPUs for just a couple of hundred thousand dollars (note, only 2 GPU servers per rack for now is normal, otherwise you have to buy non-commodity racks with high power draw).

MuffinFlavored 7y ago

Can these be used for crypto mining at any level of efficiency? I was able to mine GRLC back in the day on AWS spot instances at a VERY mild degree of profitability.

elabajaba 7y ago
Doubtful, since these are just fully unlocked TU102 GPUs (same as the Titan RTX, 2080ti is the same TU102 GPU but partially locked at 4352 cores vs 4608 for the Quadro RTX 6000/8000 and Titan RTX). If you could be profitable with this at $1000/month then people would be flocking out to buy 2080tis for $1100 and getting 90-95% of the hashrate.
walrus01 7y ago
not really, most cryptocurrency is at the stage where the only thing effective is a combination of custom ASICs and nearly free electricity. About twelve months ago I looked into mining ethereum with state of the art GPUs and it would not have had a reasonable ROI unless I was literally paying $0.00 per kWh. And that was before its value per coin dropped a lot.
- kohtatsu 7y ago
  Let's replace baseboard heaters with cryptominers.
- latchkey 7y ago
  When the value dropped, the network hashrate dropped and difficulty went down so things actually became profitable again. The best time to mine is during the drops, not the highs, unless you follow buy high, sell low and don't believe the market will correct for the better again (which it has). Of course, it depends on electricity prices, but it is profitable to mine ethereum, especially if you know how to tune the cards to maximize hash/consumption. That said, mining is competitive and difficult and unless you are going to go really large, don't bother. If you are interested in learning about it, definitely experiment though don't expect to make a lot of money.
tootahe45 7y ago

picozeta 7y ago

I would go with Hetzner: https://www.hetzner.com/dedicated-rootserver/ex51-ssd-gpu https://www.hetzner.com/dedicated-rootserver/ex51-ssd-gpu GTX1080 for 100$ a month. Grantend, it is older, but it still works for DL. Let's say you do 10 experiments a month for ~20 hours. Thats 0.5$/hour and I don't think it is 3 times faster. If you then want to do even more learning the price goes even down. //DISCLAIMER: I do not work for them, but used it for DL in the past and it was for sure cheaper than GCP or AWS. If you have to do lots of experiments (>year) go with your own hardware, but do not underestimate the convenience of >100MByte/s if you download many big training sets.

icelancer 7y ago
I have one of these instances. It's awesome and I recommend it highly.
svd4anything 7y ago
How does data in/out work in practice with them? I see this 4 Tbit bandwidth but do you happen to know what that translates to and what happens if you exceed that? Also check availability shows a 5 day wait current: “EX51-SSD-GPU for Falkenstein (FSN1): Due to very high demand for these server models, its current setup time is approximately up to 5 workdays.*” Or maybe there are other regions/dcs.
- indalo 7y ago
  I have like 18 of their auction servers that are unmetered at 1gbps and really make that bandwidth sweat. I've never had issues honestly, and they've never tried to dreamhost me. I love it.
- picozeta 7y ago
  So far I did not reach that limit (I used it to train networks for image segmentation) so I had mostly ingress and only downloaded large amounts to the machine not from it (which is free like with most providers). But you can just ask them. I have to say that not everything was 100% smooth - sometimes the proprietary NVidia driver crashed (you have to use the right CUDA and driver combination) my Linux instance and hanged the system, so I had to hard-reboot it (which is supported via their admin console) which takes some minutes. However that's not their fault as I heard the driver is a big pile of crap shit anyway because NVidia is too embarrassed to post it to LKML.

ThomWilhelm3 7y ago

Will this profitably mine bitcoins? :p

beatgammit 7y ago
No.

dkobran 7y ago

Interesting to see another cloud provider go with Quadro chips. NVIDIA repackages the same silicon under several different brands (GeForce, Quadro, GRID, Tesla) and we (https://paperspace.com https://paperspace.com) have found Quadro to offer the best price/performance value. Despite minor performance characteristics, such as FP16 support in the Tesla family, Quadros can run all of the same workloads eg graphics, HPC, Deep Learning etc. If you’re interested in a similar instance for less $/hr, check out the Paperspace P6000.

m0zg 7y ago

Still way too much money when a 2x 2080Ti comparably specced machine under my desk costs less than 2.5 months of their billing rate, and 4x 1080Ti servers in my garage cost about 1 month of their 4-GPU machine _and_ have more SSD storage. This pricing is totally insane, especially if not billed per-minute (which in Linode's case it is not) and if there are no cheaper preemptible/spot instances.

svd4anything 7y ago
I’m starting to think one can adopt the simple rule of switch to a DIY build whenever there enough work to keep a GPU busy for 2 months, otherwise if the workload is intermittent then better strategy is leasing, especially considering the purchase cost/performance is constantly dropping.
- dillonmckay 7y ago
  It would seem there could be a market for multi-month rentals of a ML/gaming rig, with return shipping/packaging?
trey-jones 7y ago
What's the cost for power? Serious question, and I'm not suggesting that this cost should account for a large percentage of the price, but genuinely curious. If your GPUs are working every hour of the month for you, how much is it costing you in electricity?
- m0zg 7y ago
  Quad GPU machines draw about 1.3KW each on average when under load. That's about $100/mo where I live, assuming they're 100% loaded 24x7 for the entire month. Realistically it's less. So it's not free, but it's not a crazy amount either.

deleted 7y ago

[deleted]

Who_me 7y ago

Hey peeps full disclosure I work as one of Linode's RnD engineers. I want to try to get to as many of these as I can. One of the biggest questions is why the Quadro RTX 6000? Few things: 1. Cost it has the same performance as the 8000. The difference is 8 more GB of RAM that comes at a steep premium. Cost is important to us as it allows us to be at a more affordable price point. 2. We have all heard or used the Tesla V100, and it's a great card. The biggest issue is that it's expensive. So one of the things that caught our eye is the RTX 6000 has a fast Single-Precision Performance, Tensor Performance, and INT8 performance. Plus the Quadro RTX supports INT4. https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/quadro-rtx-6000-us-nvidia-704093-r4-web.pdf https://www.nvidia.com/content/dam/en-zz/Solutions/design-vi... https://images.nvidia.com/content/technologies/volta/pdf/tesla-volta-v100-datasheet-letter-fnl-web.pdf https://images.nvidia.com/content/technologies/volta/pdf/tes... Yes, these are manufactures numbers, but it caused us pause. As always, your mileage may vary. 3. RT cores. This is the first time (TMK) that a cloud provider is bringing RT cores into the market. There are many use cases for RT that have yet to be explored. What will we come up with as a community?! Now with all that being said, there is a downside, FP64 aka double precision. The Tesla V100 does this very well, whereas the Quadro RTX 6000 does poorly in comparison. We think although those workloads are important, the goal was to find a solution that fits a vast majority of the use cases. So is the marketing true to get the most out of MI/AI/Etc? Do you need a Tesla to get the best performance? Or is the Tesla starting to show its age? Give the cards a try I think you'll find these new RTX Quadros with Turning architecture are not the same as the Quadros of the past.

tntn 7y ago
> This is the first time (TMK) that a cloud provider is bringing RT cores into the market. Your knowledge is incomplete. T4 has been available in google cloud for many months.
- Who_me 7y ago
  I stand corrected thank you!
jamesblonde 7y ago

hmart 7y ago

I love Linode support. There are cheaper places but I have my Key VPSs there.

zonidjan 7y ago

Oh, hey! It only adds 1/5th of the GPU's purchase price.