forked from mrq/bitsandbytes-rocm
21 lines
1.6 KiB
Markdown
21 lines
1.6 KiB
Markdown
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# Compiling from source
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Basic steps.
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1. `make cudaXXX` where `cudaXXX` is among `cuda92, cuda10x, cuda110, cuda11x`
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2. `CUDA_VERSION=XXX python setup.py install`
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To run these steps you will need to have the nvcc compiler installed that comes with a CUDA installation. If you use anaconda (recommended) then you can figure out which version of CUDA you are using with PyTorch via the command `conda list | grep cudatoolkit`. Then you can install the nvcc compiler by downloading and installing the same CUDA version from the [CUDA toolkit archive](https://developer.nvidia.com/cuda-toolkit-archive).
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For your convenience, there is a install script int he root directory that installs CUDA 11.1 locally and configures it automatically. After installing you should add the `bin` sub-directory to the `$PATH` variable to make the compiler visible to your system. To do this you can add this to your `.bashrc` by executing these commands:
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```bash
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echo "export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64/" >> ~/.bashrc
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echo "export PATH=$PATH:/usr/local/cuda/bin/" >> ~/.bashrc
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source ~/.bashrc
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```
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By default, the Makefile will look at your `CUDA_HOME` environmental variable to find your CUDA version for compiling the library. If this path is not set it is inferred from the path of your `nvcc` compiler.
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Either `nvcc` needs to be in path for the `CUDA_HOME` variable needs to be set to the CUDA directory root (e.g. `/usr/local/cuda`) in order for compilation to succeed
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If you have problems compiling the library with these instructions from source, please open an issue.
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