# Compiling from Source[[compiling]]

To compile from source, the CUDA Toolkit is required. Ensure `nvcc` is installed; if not, follow these steps to install it along with the CUDA Toolkit:

```bash
wget https://raw.githubusercontent.com/TimDettmers/bitsandbytes/main/install_cuda.sh
# Use the following syntax: cuda_install CUDA_VERSION INSTALL_PREFIX EXPORT_TO_BASH
#   CUDA_VERSION options include 110 to 122
#   EXPORT_TO_BASH: 0 for False, 1 for True

# Example for installing CUDA 11.7 at ~/local/cuda-11.7 and exporting the path to .bashrc:
bash install_cuda.sh 117 ~/local 1
```

For a single compile run with a specific CUDA version, set `CUDA_HOME` to point to your CUDA installation directory. For instance, to compile using CUDA 11.7 located at `~/local/cuda-11.7`, use:

```
CUDA_HOME=~/local/cuda-11.7 CUDA_VERSION=117 make cuda11x
```

## General Compilation Steps

1. Use `CUDA_VERSION=XXX make [target]` to compile, where `[target]` includes options like `cuda92`, `cuda10x`, `cuda11x`, and others.
2. Install with `python setup.py install`.

Ensure `nvcc` is available in your system. If using Anaconda, determine your CUDA version with PyTorch using `conda list | grep cudatoolkit` and match it by downloading the corresponding version from the [CUDA Toolkit Archive](https://developer.nvidia.com/cuda-toolkit-archive).

To install CUDA locally without administrative rights:

```bash
wget https://raw.githubusercontent.com/TimDettmers/bitsandbytes/main/install_cuda.sh
# Follow the same syntax and example as mentioned earlier
```

The compilation process relies on the `CUDA_HOME` environment variable to locate CUDA. If `CUDA_HOME` is unset, it will attempt to infer the location from `nvcc`. If `nvcc` is not in your path, you may need to add it or set `CUDA_HOME` manually. For example, if `python -m bitsandbytes` indicates your CUDA path as `/usr/local/cuda-11.7`, you can set `CUDA_HOME` to this path.

If compilation issues arise, please report them.

## Compilation for Kepler Architecture

From version 0.39.1, bitsandbytes no longer includes Kepler binaries in pip installations, requiring manual compilation. Follow the general steps and use `cuda11x_nomatmul_kepler` for Kepler-targeted compilation.
