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Learn how dstack orchestrates GPU workloads across any cloud, simplifying infrastructure setup, using spot instances, and reducing training and inference costs.
Developing, training, and deploying LLMs (Large Language Models) can be a challenging task. Managing the infrastructure can be a lot of pain, even when you’re using a major cloud provider. It can be even more challenging if you’re using alternative GPU providers. However, dstack, an open-source orchestration engine, can significantly simplify running GPU workloads across any cloud GPU provider.
dstack is an open-source container orchestrator maximizing GPU utilization for heterogeneous ML workloads.
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