Environment variables¶

Here are the environment variables CuPy uses.

`CUDA_PATH`	Path to the directory containing CUDA. The parent of the directory containing `nvcc` is used as default. When `nvcc` is not found, `/usr/local/cuda` is used. See Working with Custom CUDA Installation for details.
`CUPY_CACHE_DIR`	Path to the directory to store kernel cache. `${HOME}/.cupy/kernel_cache` is used by default. See Overview for details.
`CUPY_CACHE_SAVE_CUDA_SOURCE`	If set to 1, CUDA source file will be saved along with compiled binary in the cache directory for debug purpose. It is disabled by default. Note: source file will not be saved if the compiled binary is already stored in the cache.
`CUPY_CACHE_IN_MEMORY`	If set to 1, `CUPY_CACHE_DIR` (and its default) and `CUPY_CACHE_SAVE_CUDA_SOURCE` will be ignored, and the cache is in memory. This env var allows reducing disk I/O, but is ignoed when `nvcc` is set to be the compiler backend.
`CUPY_DUMP_CUDA_SOURCE_ON_ERROR`	If set to 1, when CUDA kernel compilation fails, CuPy dumps CUDA kernel code to standard error. It is disabled by default.
`CUPY_CUDA_COMPILE_WITH_DEBUG`	If set to 1, CUDA kernel will be compiled with debug information (`--device-debug` and `--generate-line-info`). It is disabled by default.
`CUPY_GPU_MEMORY_LIMIT`	The amount of memory that can be allocated for each device. The value can be specified in absolute bytes or fraction (e.g., `"90%"`) of the total memory of each GPU. See Memory Management for details. `0` (unlimited) is used by default.
`CUPY_SEED`	Set the seed for random number generators.
`CUPY_EXPERIMENTAL_SLICE_COPY`	If set to 1, the following syntax is enabled: `cupy_ndarray[:] = numpy_ndarray`.
`CUPY_ACCELERATORS`	A comma-separated string of backend names (`cub` or `cutensor`) which indicates the acceleration backends used in CuPy operations and its priority. Default is empty string (all accelerators are disabled).
`CUPY_TF32`	If set to 1, it allows CUDA libraries to use Tensor Cores TF32 compute for 32-bit floating point compute. The default is 0 and TF32 is not used.
`NVCC`	Define the compiler to use when compiling CUDA source. Note that most CuPy kernels are built with NVRTC; this environment is only effective for RawKernels/RawModules with `nvcc` backend or when using `cub` as the accelerator.

Moreover, as in any CUDA programs, all of the CUDA environment variables listed in the CUDA Toolkit Documentation will also be honored. When CUPY_ACCELERATORS or NVCC environment variables are set, g++-6 or later is required as the runtime host compiler. Please refer to Installing CuPy from Source for the details on how to install g++.

For installation¶

These environment variables are used during installation (building CuPy from source).

`CUDA_PATH`	See the description above.
`CUTENSOR_PATH`	Path to the cuTENSOR root directory that contains `lib` and `include` directories. (experimental)
`NVCC`	Define the compiler to use when compiling CUDA files.
`CUPY_PYTHON_350_FORCE`	Enforce CuPy to be installed against Python 3.5.0 (not recommended).
`CUPY_INSTALL_USE_HIP`	For building the ROCm support, see Building CuPy for ROCm for further detail.
`CUPY_NVCC_GENERATE_CODE`	To build CuPy for a particular CUDA architecture. For example, `CUPY_NVCC_GENERATE_CODE="arch=compute_60,code=sm_60"`. For specifying multiple archs, concatenate the `arch=...` strings with semicolons (`;`). When this is not set, the default is to support all architectures.