(ROCm) AMD-GPU-Boost: Unlock Full Performance on Consumer AMD GPUs
https://github.com/Painter3000/AMD-GPU-BOOST
I've been frustrated with AMD GPU performance in AI/ML applications - my RX 6800 XT was only using ~25% of its potential in PyTorch. The issue? ROCm was designed for MI-series enterprise GPUs and severely underdetects consumer GPU capabilities.
ROCm reports only 36 compute units instead of 72, and uses warp size 32 instead of the optimal 64 for RDNA2/3. This affects the entire RX 6000/7000 series.
AMD-GPU-BOOST fixes this at runtime by monkey-patching PyTorch's device detection. Results: - 4x performance improvement in inference - "NVIDIA-only" apps now run perfectly on AMD - Works with ComfyUI, Stable Diffusion, WAN 2.1, etc.
The tool includes a GUI installer for easy Pinokio integration and supports 18+ GPU models from RX 6400 to RX 7900 XTX.
This has been a major pain point for the AMD AI community - curious what the HN crowd thinks about runtime hardware detection fixes vs. proper driver/framework solutions.
Demo: My RX 6800 XT went from 1152 threads (36×32) to 4608 threads (72×64) - exactly what the hardware specs promise.
ROCM is so poor. Their OS support is poor.
It's clearly the sole reason holding AMD back from competing with nvidia in any real way.
Did you try upstreaming this?
“What do you think – is runtime patching a legitimate option or should AMD urgently address this issue?”