Linode Linode GPU Instances

eva2000 · Jun 24, 2019

Not sure how many folks use GPUs on their servers for tasks like machine learning or AI or graphics rendering/transcoding? Linode announced GPU instances using NVIDIA Quadro RTX 6000 GPU recently at Introducing Linode GPU Instances.

We are excited to announce the pilot launch of Linode GPU instances. These instances are tailored towards workloads such as machine learning, artificial intelligence, high quality graphics rendering, video transcoding and scientific computing.

Linode GPU instances are built on NVIDIA Quadro RTX 6000 GPU cards. This is the first time these cards are being offered by a cloud provider, and includes all three major types of processing cores (CUDA, Tensor, and Ray Tracing). It’s the next step in cloud computing for Linode, and advances our mission of making cloud computing simple and accessible to everyone.
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And here's a Linode employee's post on rationale for choosing NVIDIA Quadro RTX 6000 GPUs at Linode GPU Instances | Hacker News

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-vi...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.
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