V100-gpu_2l和gpu_4l分区计算会爆炸
2024-11-25 00:39:11
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https://github.com/google-deepmind/alphafold3/issues/59
We ran the "2PV7" example from the docs on all GPU models available on our cluster with the following results:
gpu ranking_score driver_ver cuda rtx_2080_ti -99.68 535.183.06 12.2 rtx_3090 0.67 550.127.05 12.4 rtx_4090 0.67 550.127.05 12.4 titan_rtx -99.78 550.127.05 12.4 quadro_rtx_6000 -99.74 550.90.07 12.4 v100 -99.78 550.127.05 12.4 a100_pcie_40gb 0.67 550.127.05 12.4 a100_80gb 0.67 550.127.05 12.4
Specifically, a ranking score of -99 corresponds to noise/explosion, and a ranking score of 0.67 corresponds to a visually compelling output structure.
Update (20.11): added driver/cuda versions reported by nvidia-smi.
These are the GPU capabilities (see https://developer.nvidia.com/cuda-gpus) for the GPUs mentioned:
rtx_2080_ti7.5(bad) rtx_3090 8.6 rtx_4090 8.9 titan_rtx7.5(bad) quadro_rtx_60007.5(bad) v100 7.0(bad) a100_pcie_40gb 8.0 a100_80gb8.0