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KDA (Kernel Design Agents) is an open-source agent-centric workflow from MIT HAN Lab for using coding agents to research, implement, verify, and iterate on performance-sensitive CUDA kernel tasks. It helped Databricks achieve rank #1 on NVIDIA's SOL-ExecBench leaderboard.
MIT HAN Lab proposes a method to automatically design and optimize CUDA kernels using an AI agent workflow. Through a process of task contracts, agent loops, and small-step verification, the agent can autonomously iterate and optimize within a specialized toolchain, replacing manual tuning.