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Podcast: Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM

Kaynak: InfoQ ·

In this episode, Edoardo Vacchi discusses the evolving landscape of WebAssembly on the backend, running Java workloads on GPUs using TornadoVM, and optimizing distributed AI inference using llm-d and vLLM on Kubernetes. Edoardo explains how llm-d manages cache locality (KV and prefix caches), request routing, and batch inference across Kubernetes clusters to maximize expensive GPU utilization. By Edoardo Vacchi

Podcast: Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM nedir?

Podcast: Distributed LLM Inference on Kubernetes with llm-d, Wasm, & TornadoVM, Makale kategorisinde yer alan ve InfoQ üzerinden sunulan bir keşiftir. In this episode, Edoardo Vacchi discusses the evolving landscape of WebAssembly on the backend, running Java workloads on GPUs using TornadoVM, and optimizing distributed AI infere

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