Skip to main content

Accera GPU Support

Project description

Accera GPU

Accera

Accera is a programming model, a domain-specific programming language embedded in Python (eDSL), and an optimizing cross-compiler for compute-intensive code. Accera currently supports CPU and GPU targets and focuses on optimization of nested for-loops.

Writing highly optimized compute-intensive code in a traditional programming language is a difficult and time-consuming process. It requires special engineering skills, such as fluency in Assembly language and a deep understanding of computer architecture. Manually optimizing the simplest numerical algorithms already requires a significant engineering effort. Moreover, highly optimized numerical code is prone to bugs, is often hard to read and maintain, and needs to be reimplemented every time a new target architecture is introduced. Accera aims to solve these problems.

Accera has three goals:

  • Performance: generate the fastest implementation of any compute-intensive algorithm.
  • Readability: do so without sacrificing code readability and maintainability.
  • Writability: a user-friendly programming model, designed for agility.

accera-gpu

The accera-gpu package contains add-ons for GPU support. You can find documentation and examples on Github.

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

accera_gpu-1.2.10-cp310-cp310-win_amd64.whl (5.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

accera_gpu-1.2.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (35.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

accera_gpu-1.2.10-cp310-cp310-macosx_10_15_x86_64.whl (38.9 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

accera_gpu-1.2.10-cp39-cp39-win_amd64.whl (5.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

accera_gpu-1.2.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (35.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

accera_gpu-1.2.10-cp39-cp39-macosx_10_15_x86_64.whl (38.9 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

accera_gpu-1.2.10-cp38-cp38-win_amd64.whl (5.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

accera_gpu-1.2.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (35.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

accera_gpu-1.2.10-cp38-cp38-macosx_10_15_x86_64.whl (38.9 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

accera_gpu-1.2.10-cp37-cp37m-win_amd64.whl (5.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

accera_gpu-1.2.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (35.9 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

accera_gpu-1.2.10-cp37-cp37m-macosx_10_15_x86_64.whl (38.9 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

File details

Details for the file accera_gpu-1.2.10-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 ddd4a8a195ab07a08ca3fe2697dabd3bf1983795f1b2ce975fbe7ac2f64a86a1
MD5 8f7086dc15ad20cdd8dd5d347caf299f
BLAKE2b-256 f9411845d78fda055c110db5cddae7d951098a919e2c3e7a6e87ef42f1432572

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6f1f1ebfc259dbe61450f1b90a3715bd7738ad397606e6de1d250118703f94ba
MD5 695812439b8e28b07e20040f253157b2
BLAKE2b-256 ce8bee9506434b72f30b5cb7d3d2c33614893bc66b46a9c336842ecacd15e1be

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 cacacf2f114f4fb2174c20b69ad273cb15287968eca5f181721e3295c9a83aa2
MD5 2d0327e38b16e05a8b81f64e7da7ab00
BLAKE2b-256 bc075eaafc1642cb1325e5dd5ced05b7670273af8824e32b74be873931c555d2

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 9c8ee63f0aa9b77b688bf6b1d23f2cc6c710faf067f0005f6c2c727551451b93
MD5 f4610dfd14d7c0212cad9334d505c88e
BLAKE2b-256 3193579ea19203e54f10f232ed13abb5d15631470902b63eaffb799d0e21909a

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2a79a9e4fad0aacae30f192f04fbf59fc63ad607308349645b33fb1963105a6a
MD5 5d4360d9202de152e0b6c4f2a6b15409
BLAKE2b-256 32d22cb2dba9d59fb595636bca103fa756b21173a29712f381d4e3ade7dda0cc

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 6220f526375a1ce5b61f36da900bbd39e82dd40645c48e947f0fa972e2633a8e
MD5 747f7094f6645699e5af8edaf12506bb
BLAKE2b-256 2d01e073f7fce79c4351622d0e3ebcd162d7f5ee3450fb530d4937119acb8bf7

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 e51c2269c8a363dbdf21695e04b72a0af0802b175501a973beaba29102778af7
MD5 51c7f06db9aebb86793964430242b4da
BLAKE2b-256 71d87eea03ded228beacbe77bac2a1c853ab32cc92a876f8e3e8c4a79994dc0d

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c32145d62701deca8bfcd1d303b7ca4314b1fa88cf8cd08649d775e62b555c4d
MD5 6ca22de2d3d7fac94522e2203c33499a
BLAKE2b-256 6dbab2bacb19e72dda0d4e2f051ca85fbaf5b3012d670e648ec7809466aeedae

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 0de040e04721cf52234e0bb5ee669b3a64b690180822ae05ca972f775b119fe2
MD5 3904c686799bf66efeaba2511c3ddc69
BLAKE2b-256 2071ed6c977105a711903b5f4168231f498da3f893e52996e7415d2ac714f0d5

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 a6175d47773dd1d78195431b86c8e69404eaf0673cef33035fcd1d41d73a9492
MD5 6348aebdab2a91def4abd44be69e3a3a
BLAKE2b-256 95400be0b6012179b839d160c2b6f3dcbc822144ffefaf928e3ae9531b3f625a

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0821b87254f0e21db5b51b2a108a8c9baf3695eb5371adc11a0b3350c423facd
MD5 08a57315415e29f30aa974c7fb8e099f
BLAKE2b-256 89705b324ed78ed6fc23bd007681f8932aeb292f0fe44765c2c2c11be83f0bae

See more details on using hashes here.

File details

Details for the file accera_gpu-1.2.10-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_gpu-1.2.10-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b77bdfbc9f4e50b3e152ec895ff18208a4ec7e44412c56e3d482e35c66e729dc
MD5 0999dd7986796e5338b2d3b68136d52d
BLAKE2b-256 86853217743de017fc157b8f0806077ee2a501569ef346968b23bb055ce3ce88

See more details on using hashes here.

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