Hawkeye framework brings hardware-awareness to coding agents
Moh1tAgarwal · x · 2026-08-21
Addressing the bottleneck of software support for diverse ML chips, the Hawkeye framework aims to equip coding agents with hardware awareness.
- Context: Achieving peak performance on new ML chips relies heavily on hardware-specific kernel optimizations, an area where current coding agents struggle.
- Solution: Hawkeye grounds agents in a minimal yet comprehensive taxonomy of optimization strategies.
- Methodology: For new GPU or accelerator architectures, users only need to write 10 unit tests and solution kernels. Agents can then effectively scale test-time compute with this minimal supervision to write hardware-aware kernels.
- Impact: Hawkeye enables kernel porting across architectures (Ampere, Hopper, Blackwell), vendors (NVIDIA, AMD), and precisions (FP8, NVFP4, MXFP4) while consistently leveraging hardware-specific features.
Related event: Hawkeye Lets AI Agents Write High-Performance GPU Kernels from ~10 Examples(4 posts)→
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