Agentic CUDA Optimizer - Automated GPU Kernel Optimization
Show HN: Agentic CUDA Kernel Optimizer
Agentic CUDA Optimizer is an open-source tool that automatically turns workload descriptions into optimized GPU kernels. Powered by LangGraph, it cycles through code generation, correctness checks, benchmarking, and refinement, even querying NVIDIA docs and Nsight Compute counters. A C++ harness compiles and runs kernels via NVRTC and the CUDA Driver API, while Python handles validation and ranking. It retains the fastest validated implementation and supports custom inputs. Ideal for developers seeking to accelerate CUDA kernel development without manual tuning.
An agentic CUDA kernel optimizer that turns workload descriptions into GPU implementations through an automated cycle of code generation, correctness checks, benchmarking, and refinement.
- fooblaster
Can someone explain why this isn't better accomplished through a single prompt to Claude code or codex? I don't think I understand.
- generalizations
Very cool. Did you also try using the karpathy autoresearch? How do you think this compares?
- asamadx
respect for shipping something this technical solo, this is the kind of project that usually needs a team to even validate correctness. how are you handling regression testing across kernel variants, feels like the hardest part of an agentic optimizer isn't finding a faster kernel, it's proving the faster one didn't quietly break something