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PyTorch compile got faster? on GB200 - Printable Version +- Inference (https://www.datasculpting.ai/inference) +-- Forum: Drivers / Frameworks / Toolkits (https://www.datasculpting.ai/inference/forumdisplay.php?fid=8) +--- Forum: PyTorch / JAX / Other Frameworks (https://www.datasculpting.ai/inference/forumdisplay.php?fid=34) +--- Thread: PyTorch compile got faster? on GB200 (/showthread.php?tid=473) Pages:
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PyTorch compile got faster? on GB200 - deltastation - 09-24-2026 Thought I'd post a small recipe because a lot of threads ask similar things. Maybe useful as a starting point: PyTorch on A6000, keeping HBM constraints in mind from the start. Feel free to tear it apart if you see something dumb. Re: PyTorch compile got faster? on GB200 - visionforge - 09-24-2026 Thanks, that helps. I ended up in about the same place using Ollama. The biggest change for me was simplifying the stack instead of adding one more optimization layer. Re: PyTorch compile got faster? on GB200 - thetaplane - 09-25-2026 Quote:Thanks, that helps. I ended up in about the same place using Ollama. The biggest change for me was simplifying the stack instead of adding one more op subscribed, curious where this lands. Re: PyTorch compile got faster? on GB200 - benchplease - 09-26-2026 I'd approach it in a boring order. If you're on vLLM, I'd confirm the version first and then reduce variables until the behavior is obvious. Re: PyTorch compile got faster? on GB200 - southspark - 09-26-2026 Tried to reproduce it just now. I couldn't reproduce the slowdown until I pushed context much higher. Re: PyTorch compile got faster? on GB200 - torchkite - 09-26-2026 Maybe, but I had the opposite result. I get why that seems right, but on M3 Max the bottleneck felt elsewhere. Could be a workload difference, but I wouldn't generalize too fast from one setup. Re: PyTorch compile got faster? on GB200 - thetarunner - 09-26-2026 Can you fill in a bit more context? Do you see the same thing with a smaller batch or shorter prompt? I'm happy to test one more variant if you want a second data point. Re: PyTorch compile got faster? on GB200 - kernelmike - 09-28-2026 My first guess would be this: Start by verifying the driver/runtime combo, then test with a smaller prompt, then look at embeddings. Once you know the plain path works, then add the faster path back in piece by piece. Re: PyTorch compile got faster? on GB200 - torchshed - 09-28-2026 worth checking the driver first. Re: PyTorch compile got faster? on GB200 - deltastation - 09-28-2026 Maybe, but I had the opposite result. I get why that seems right, but on A6000 the bottleneck felt elsewhere. |