Skip to main content

NVIDIA cuTENSOR

Project description

cuTENSOR is a high-performance CUDA library for tensor primitives.

Key Features

  • Extensive mixed-precision support:

    • FP64 inputs with FP32 compute.

    • FP32 inputs with FP16, BF16, or TF32 compute.

    • Complex-times-real operations.

    • Conjugate (without transpose) support.

  • Support for up to 64-dimensional tensors.

  • Arbitrary data layouts.

  • Trivially serializable data structures.

  • Main computational routines:

    • Direct (i.e., transpose-free) tensor contractions.

      • Support just-in-time compilation of dedicated kernels.

    • Tensor reductions (including partial reductions).

    • Element-wise tensor operations:

      • Support for various activation functions.

      • Support for padding of the output tensor

      • Arbitrary tensor permutations.

      • Conversion between different data types.

Documentation

Please refer to https://docs.nvidia.com/cuda/cutensor/index.html for the cuTENSOR documentation.

Installation

The cuTENSOR wheel can be installed as follows:

pip install cutensor-cuXX

where XX is the CUDA major version (currently CUDA 11 & 12 are supported). The package cutensor (without the -cuXX suffix) is deprecated. If you have cutensor installed, please remove it prior to installing cutensor-cuXX.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

cutensor_cu12-2.0.2-py3-none-win_amd64.whl (145.0 MB view details)

Uploaded Python 3 Windows x86-64

File details

Details for the file cutensor_cu12-2.0.2-py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for cutensor_cu12-2.0.2-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 e2ae37dc9e4a1643dee9318ffdbd212097660e69826328953830cead567fd543
MD5 f413c9a16db6dc129c90c44beeb47ee4
BLAKE2b-256 08a13fb72bd0593dc4e451d5e6f81c43562b38622a24d68642ff9bda8df35ac0

See more details on using hashes here.

Provenance

File details

Details for the file cutensor_cu12-2.0.2-py3-none-manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for cutensor_cu12-2.0.2-py3-none-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 18c96a4f1e8a559eec626527f5928d5f5b575f6c2b9c45e87309a025ae682334
MD5 1cc1e67fe05b55aae6f604f5518efc44
BLAKE2b-256 edd661fc3511bc9e4cdb423b69964e3d344090b4093cbf9d3c8cc469ef4642d0

See more details on using hashes here.

Provenance

File details

Details for the file cutensor_cu12-2.0.2-py3-none-manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for cutensor_cu12-2.0.2-py3-none-manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 1db559bdfe4345ac19ee66ab7ee49a54e98b1529fc96de812ade3dbc0a90ef47
MD5 6fb2971ae31c6dbb75a284618de6355f
BLAKE2b-256 f751786c275bc675e3f5d8d207c378652bfbd4c4103174ce857f1a04ff194211

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page