Environment variables

Here are the environment variables CuPy uses.

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++.

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

Default: ${HOME}/.cupy/kernel_cache

Path to the directory to store kernel cache. See Overview for details.

CUPY_CACHE_SAVE_CUDA_SOURCE

Default: 0

If set to 1, CUDA source file will be saved along with compiled binary in the cache directory for debug purpose. Note: the source file will not be saved if the compiled binary is already stored in the cache.

CUPY_CACHE_IN_MEMORY

Default: 0

If set to 1, CUPY_CACHE_DIR and CUPY_CACHE_SAVE_CUDA_SOURCE will be ignored, and the cache is in memory. This environment variable allows reducing disk I/O, but is ignoed when nvcc is set to be the compiler backend.

CUPY_DUMP_CUDA_SOURCE_ON_ERROR

Default: 0

If set to 1, when CUDA kernel compilation fails, CuPy dumps CUDA kernel code to standard error.

CUPY_CUDA_COMPILE_WITH_DEBUG

Default: 0

If set to 1, CUDA kernel will be compiled with debug information (--device-debug and --generate-line-info).

CUPY_GPU_MEMORY_LIMIT

Default: 0 (unlimited)

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.

CUPY_SEED

Set the seed for random number generators.

CUPY_EXPERIMENTAL_SLICE_COPY

Default: 0

If set to 1, the following syntax is enabled:

cupy_ndarray[:] = numpy_ndarray

CUPY_ACCELERATORS

Default: "" (no accelerators)

A comma-separated string of backend names (cub or cutensor) which indicates the acceleration backends used in CuPy operations and its priority. All accelerators are disabled by default.

CUPY_TF32

Default: 0

If set to 1, it allows CUDA libraries to use Tensor Cores TF32 compute for 32-bit floating point compute.

CUPY_CUDA_ARRAY_INTERFACE_SYNC

Default: 1

This controls CuPy’s behavior as a Consumer. If set to 0, a stream synchronization will not be performed when a device array provided by an external library that implements the CUDA Array Interface is being consumed by CuPy. For more detail, see the Synchronization requirement in the CUDA Array Interface v3 documentation.

CUPY_CUDA_ARRAY_INTERFACE_EXPORT_VERSION

Default: 3

This controls CuPy’s behavior as a Producer. If set to 2, the CuPy stream on which the data is being operated will not be exported and thus the Consumer (another library) will not perform any stream synchronization. For more detail, see the Synchronization requirement in the CUDA Array Interface v3 documentation.

NVCC

Default: 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.

Note

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

Default: 0

Build CuPy for AMD ROCm Platform (experimental). For building the ROCm support, see Building CuPy for ROCm for further detail.

CUPY_NVCC_GENERATE_CODE

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.