Comments (5)
suhangpro
commented on May 25, 2024
According to NCCL readme, you should now use make -j src.build. Please kindly let me know if this works, and we will update our instructions!
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bonbonjour
commented on May 25, 2024
thanks, It works!
Do I need to run the rest instructions in NCCL readme?
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suhangpro
commented on May 25, 2024
Yes, NCCL readme has the up-to-date installation instructions. In fact, you do not need to install NCCL at all for single-gpu usages. Just skip the whole NCCL part, and change the cmake -DUSE_CUDNN=1 -DUSE_NCCL=1 -Dpython_version=3 .. line to cmake -DUSE_CUDNN=1 -Dpython_version=3 ..
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suhangpro
commented on May 25, 2024
Updated in commit f821913
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bonbonjour
commented on May 25, 2024
thank you very much!!
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Related Issues (19)
- Joint 2D-3D experiments HOT 3
- My server GPU has problem. How I can disable GPU in training and test? HOT 2
- UnicodeDecodeError: 'utf-8' codec can't decode byte 0xbc in position 334: invalid start byte HOT 1
- don't have attribute height HOT 1
- Joint 2D-3D experiments release plan HOT 1
- train with another dataset HOT 5
- Joint 2D-3D experiments release plan
- alternate dataset
- eval bug HOT 1
- Cannot train the dataset which has more than 500items total in ShapeNet Part segmentation datesat. HOT 1
- Docker compatibility with NVIDIA 2080Ti HOT 1
- Some bug in running facade3d in my Ubuntu16.04 HOT 1
- Docker Env HOT 4
- Inconsistent cuda driver and runtime HOT 3
- Some about Joint 2D-3D
- index error HOT 1
- ImportError: No module named 'splatnet' HOT 4
- dataset problem HOT 1
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