Skip to main content

Accera Compilers

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.

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-1.2.13-cp310-cp310-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

accera_compilers-1.2.13-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-1.2.13-cp39-cp39-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

accera_compilers-1.2.13-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-1.2.13-cp38-cp38-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

accera_compilers-1.2.13-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-1.2.13-cp37-cp37m-win_amd64.whl (27.8 MB view details)

Uploaded CPython 3.7m Windows x86-64

accera_compilers-1.2.13-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

File details

Details for the file accera_compilers-1.2.13-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 04e907e6945a9b5815d9e1d9ab88d47df98a2cba84c5f76bdb430a4afe6e9a31
MD5 dc31ca05a7fd7c40c6e1d151e8645726
BLAKE2b-256 b1bc268d130c422fabe03ab8867d6dcf46f90499c9660880a05051bb1a171257

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3960b03be9463ed9d3edd7fa297b659f2950a6c03389486a4bd7c38c64e0e735
MD5 9553f22159b9ad6286c3f241a01b31e9
BLAKE2b-256 2e9b7a5f0d64f6249cfdd47770c263ff3cec6ae4806bebcedc9ad1c62f189a60

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f55ea5febab40b3172bda51b7bdb4090f188dd91b5219d1d34cecbe6ee635ba3
MD5 6691e5917cda53a16fd5a2bcee7c06b1
BLAKE2b-256 ca24dbf9024d962f669aabdae8f002cebdcf890436ee8e8d4d276eb35d4e0b4e

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 25abe6dfa5b926bce9d4276824852d232f8f9662cc87802948bee2b72d62337b
MD5 98588c7b133793906404c3872d3e50b2
BLAKE2b-256 4dc6c7b690db25ce5435dc0541e68190395bc5006e5137bb34b6c53caaab97f1

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 8b8f70a0fd8bbd4ffffbf5b295c02547df47c21c1c487d29236b8e8a53cfc829
MD5 883d4c1bde23f8253bfb7d88def612c3
BLAKE2b-256 df55884ae105cbed610821b4e3e982352cbffe871713d3547e5b8273be9fa35a

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1daf98e30dd9b07eca81f18e95af4245c983005adbdf2a58dc97c05a0b4941b0
MD5 5275efc6fbf05a878170f79f57b658dd
BLAKE2b-256 7b22d06ed200e49061a83bf62e988f302e8e5ed0e955dd7035e11265e5b7642e

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 3f876c72bef4d03b1f786d3ddd22ad4502c62d2848fd20a040957ff7d1b4e2b7
MD5 a63fedbc83fc3242d6001ec2e30a6c06
BLAKE2b-256 56469da20ded8590cc46b605312d6c1cce2ab0ba277d4c1b40bd925d046aaa1a

See more details on using hashes here.

File details

Details for the file accera_compilers-1.2.13-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for accera_compilers-1.2.13-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c7e0edc125f6d656d85d0c942499e5d2c83ca9f80b1aba2c0461f8569c9db2f
MD5 b52f837bdec976e10a9716b6459d2254
BLAKE2b-256 408378e587b89db87f20480f50a2351f75c9a50def5cc27ae040abddf3c754ac

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