dstack
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About
dstack is an open-source platform that streamlines GPU allocation and AI workload orchestration for machine learning teams. It serves as an alternative to tools like Kubernetes and Slurm, designed for use across top cloud providers (AWS, GCP, Azure, etc.) and on-prem clusters. Key features include efficient cloud GPU provisioning and utilization, simplifying development, training, and deployment. It allows orchestrating workloads on existing clusters by merely listing hostnames and SSH credentials. ML engineers can launch containerized development environments for experimentation. dstack also simplifies scheduling jobs on clusters and single instances for pre-training, fine-tuning models, and other AI/data workloads. Furthermore, it enables easy deployment of auto-scaling, OpenAI-compatible model endpoints with custom code and Docker images. It aims to let ML teams focus on their research and data by abstracting infrastructure complexities.
Platform
Features
• open-source platform
• integration with major cloud gpu providers
• auto-scaling model endpoint deployment
• job scheduling on clusters and instances
• containerized development environments
• workload orchestration on existing clusters
• efficient cloud gpu provisioning
• gpu allocation and orchestration
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