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AWS is tricky in terms of how storage is provisioned - I don't remember details, but it's easy to put your datasets on storage that is connected to your GPU ser
by p1esk 6y ago
AWS is tricky in terms of how storage is provisioned - I don't remember details, but it's easy to put your datasets on storage that is connected to your GPU servers over 1Gb link. That could easily become a bottleneck. Datasets should live on Elastic Block Storage or something like that, over high speed links. Again, it's been a while since I looked into that, so I don't remember the details.
- Reelin 6y agoThe earlier comment claimed that the GPUs (!!!) were located elsewhere on the network; I suspect that the scenario you describe is what they intended to refer to. (IIRC AWS offers compute optimized instances with a volume that's guaranteed to be backed by blocks on a local NVMe drive.)
- nl 6y agoI think they are confused with AWS Elastic Inference. That is a different thing which does have network attached accelerators: Amazon Elastic inference accelerators are GPU-powered hardware devices that are designed to work with any EC2 instance, Sagemaker instance, or ECS task to accelerate deep learning inference workloads at a low cost. When you launch an EC2 instance or an ECS task with Amazon Elastic Inference, an accelerator is provisioned and attached to the instance over the network. https://aws.amazon.com/machine-learning/elastic-inference/faqs/ https://aws.amazon.com/machine-learning/elastic-inference/fa...