Accera Compilers

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for kernhanda from gravatar.com kernhanda Avatar for masonremy from gravatar.com masonremy Avatar for microsoft from gravatar.com microsoft Avatar for onglisa from gravatar.com onglisa

Unverified details

These details have not been verified by PyPI
Meta
Classifiers

Project description

Accera Compilers

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-compilers

The accera-compilers package contains pre-compiled compiler binaries used to produce optimized code using the Accera eDSL. It is not designed for standalone use, but is automatically installed when you pip install accera. You can find documentation and examples on Github.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for kernhanda from gravatar.com kernhanda Avatar for masonremy from gravatar.com masonremy Avatar for microsoft from gravatar.com microsoft Avatar for onglisa from gravatar.com onglisa

Unverified details

These details have not been verified by PyPI
Meta
Classifiers

Release history Release notifications | RSS feed

1.2.29

1.2.28

1.2.27

1.2.26

1.2.25

1.2.24

1.2.23

1.2.22

1.2.21

1.2.20

1.2.19

1.2.18

1.2.17

1.2.16

This version

1.2.15

1.2.14

1.2.13

1.2.12

1.2.11

1.2.10

1.2.9

1.2.8

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_compilers-1.2.15-cp310-cp310-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

accera_compilers-1.2.15-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.5 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

accera_compilers-1.2.15-cp310-cp310-macosx_11_0_x86_64.whl (42.5 MB view details)

Uploaded CPython 3.10 macOS 11.0+ x86-64

accera_compilers-1.2.15-cp39-cp39-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

accera_compilers-1.2.15-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.5 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

accera_compilers-1.2.15-cp39-cp39-macosx_11_0_x86_64.whl (42.5 MB view details)

Uploaded CPython 3.9 macOS 11.0+ x86-64

accera_compilers-1.2.15-cp38-cp38-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

accera_compilers-1.2.15-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.5 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

accera_compilers-1.2.15-cp38-cp38-macosx_10_15_x86_64.whl (42.5 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

accera_compilers-1.2.15-cp37-cp37m-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.7m Windows x86-64

accera_compilers-1.2.15-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (39.5 MB view details)

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

accera_compilers-1.2.15-cp37-cp37m-macosx_10_15_x86_64.whl (42.5 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

File details

Details for the file accera_compilers-1.2.15-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 695b57f533ef05f4f3528d7465e1efb39ed2f269f6159ae6027713b6af5b5346
MD5 5d0049ec2cdae0809bf6900b747f6319
BLAKE2b-256 c89d925903a8ad139e7d5e1b6bc3a6a01bb3577c786ff124ca6619ae76ab4b80

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 81a3f91964fd42b43b0789f65d9c955de888a71b783e86e64d926fc6d6e5677c
MD5 a5fed81154aae0bd533dd10367e6558d
BLAKE2b-256 75989d30df6d3f2e42e063d21273b0de5f9131c7cc71225178cf4315a28ca190

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp310-cp310-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp310-cp310-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 beabc5a483d8814d427db35a0fff373a8cd818883732a542eed902a51062a73f
MD5 b4d6a5adcbd1bf1522317b2ace5b1a55
BLAKE2b-256 45b478ddb00747d1c93ffbceaa92e6ee8230118a1e65386c252d113ecd8227fc

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5aff679d3b8e60af670086cca1c3fddef318406ebdb8458940aee2451901fbb7
MD5 60f06f96ccdb286929d4990eeb5adcf1
BLAKE2b-256 14c47ba2d2667ae1332fae4c923fbb1b3556513ca2f8b6cf9a657c7776bce4bb

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4308e5662f7894851687e5a66a1f7d65d0f0c5096077fa3830bf370e787f9377
MD5 d9522485e7f694b6eba1dac9bdf91c3a
BLAKE2b-256 1dc7d4d67a2eb12a99fd0b1c2a34154205bd4c06facc4f00f926d11f05e7f28e

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp39-cp39-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp39-cp39-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 693cf98e6a745391774cd92db5219a49c5b3e6856d2944c7ddc18d744423e1f9
MD5 8784d9b93ab7d854668f222d4c401e34
BLAKE2b-256 6665cd0a302c897589e6913c2ab052738e96aa1a7eb2a35107fb507d233bce02

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 98de0c77bb000ba3b08077c32cc767ef9e3ef3434940ea2f83c9808d06b5b434
MD5 dac1eba59c7d3a71c6e06635271a8501
BLAKE2b-256 54962725bf5bbea962239327b414ee6b9bb3bb4350e331826ac7aa1ba7033d6e

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 73ddbc57f1bf609c1b41efdc6010ce4529a7814aa2657b0c00d392e3ab6543a7
MD5 6efbf5a20dacddeacc58cb99edc2d876
BLAKE2b-256 a39188dcd8df23676f63fa853e411f5253ab6ea6bb9e3ca799b36a27c18013d1

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 6d432554207929d9428b942260a4521fa721b87c2879885ed21ebadb2569658a
MD5 e35b858a96e61e5e64947fb5efcf2066
BLAKE2b-256 73243892e79a1b49b4294c5716af3195afb76895b5ecb62a583cc435f91f5391

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3f3beba2ed4b61a6388ea326510485c27ee697bf9974e66c95509997efbb87f6
MD5 91062def137d93707d09529212539098
BLAKE2b-256 c2f11aff1e600ce384cada93da76bd552f34863d8cbfa2f1eac26d0aa61b41fd

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fe1fb95bba84b7f37e3af2c5ca337823ab4eff2ea487aac68b6630a2fb450180
MD5 f755f153a0ed79bb5a902f2975883062
BLAKE2b-256 1e82d7f96e100f433fd72b21b2cdba440b8e92193a3b1b831c399dcd87730ad3

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.15-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.15-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 8f5bcf14642fe79e1b8140145367049abf315430624c21123adf33fba0419ab2
MD5 2e0cb9568e62ed0abdd787fe3fdc3324
BLAKE2b-256 2f802502614943fb64b37bc1e99ac8633faf3d67b6f6cb8f3b0583df7d135344

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