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TAO schedules LLMs and tools together, saving GPU cycles
What is TAO: Tool-Aware Joint Scheduling for LLM-Based Agentic Serving?
TAO introduces a joint scheduler that decides when to run LLM inference on clustered GPUs and when to invoke external tools on distributed CPUs, factoring in tool-return readiness. This tool-aware approach cuts idle GPU time and boosts overall throughput versus heuristic baselines.
Who it is for
Anyone building LLM-driven agents or services can use the ideas to get more work done on the same hardware.