3 ms·
>dstack is a streamlined alternative to Kubernetes and Slurm, specifically designed for AI. It simplifies container orchestration for AI workloads both in the c
by htrp 2y ago
>dstack is a streamlined alternative to Kubernetes and Slurm, specifically designed for AI. It simplifies container orchestration for AI workloads both in the cloud and on-prem, speeding up the development, training, and deployment of AI models.
Any explanation for how it simplifies orchestration.
>dstack supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box.
Any plans for trainium ?
- cheptsov 2y ago> Any explanation for how it simplifies orchestration. There are many examples in the docs. Here are few: 1. ALl accelerators are supported natively (no operators are required). 2. Distributed task work out of the box [1] 3. For inference, OpenAI compatible gateway is provided automatically for any models deployed; along with authentication. [2] 4. Cluster management is a lot more convenient for AI compared to K8S [3] More than anything else, dstack is more lightweight; no one need to know K8S. I'm biased but we talk to a lot of users that choose dstack because they don't want to deal with K8S >dstack supports NVIDIA GPU, AMD GPU, and Google Cloud TPU out of the box. AWS accelerators are in the plan of course! [1] https://dstack.ai/docs/reference/dstack.yml/task/#distributed-tasks https://dstack.ai/docs/reference/dstack.yml/task/#distribute... [2] https://dstack.ai/docs/services https://dstack.ai/docs/services [3] https://dstack.ai/docs/concepts/fleets/ https://dstack.ai/docs/concepts/fleets/