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QCon SF 2024: Scaling Out Batch GPU Inference with Ray
A recent presentation at QConSF 2024 showcased Anyscale's Ray as a scalable solution for batch GPU inference. Ray Data, a component of the platform, optimizes task scheduling and streaming execution to maximize GPU utilization and minimize data movement costs. The integration of Ray Data with vLLM, an open-source LLM inference framework, has enabled efficient and cost-effective processing of large datasets. Key features discussed included continuous batching, pipeline parallelism, and dynamic request batching in Ray Serve.

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Source: https://www.infoq.com/news/2024/11/batch-inference-ray/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global