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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Hashes for accera_gpu-1.2.13-cp310-cp310-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2d87badfa84d0bd35f27249ba78e9be74f90cf28ec09ebd2621067edae3478f2 |
|
MD5 | 7be7f4479567e6d319a56794dc11eddd |
|
BLAKE2b-256 | a790d8a9586a173c0e09705d9d91c167eb00e512859efb908cebc8fbf221c26d |
Hashes for accera_gpu-1.2.13-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e29b375af517ffcd98e5425c6380d259414621f11cdcbc1009b2bffb13dc1bc6 |
|
MD5 | e183145c456b2d234bc7d6158b907cdb |
|
BLAKE2b-256 | 89e10115db4087fa811b9bff605d8c22f213e9efbe3a2b72a67a5c5ac2a5a91c |
Hashes for accera_gpu-1.2.13-cp39-cp39-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d8888b4ea2d417edc90d6ad9a642bd8d510bb9f122156f2169844ef2faa13458 |
|
MD5 | 17dc79ad6e044e5fe31f0f85089824cf |
|
BLAKE2b-256 | dbeab28c8cf829b6acc8da6a4a8668e90201af5a1409462334c68f0b707ed99b |
Hashes for accera_gpu-1.2.13-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b1fb7e741dba0136d6c998bd048fb72cbcd9294d3b883a7fa274c1e0ba5ba09b |
|
MD5 | 24e7b9fcc7b9c21144ae020a0a1ee941 |
|
BLAKE2b-256 | 6234272c970134774aa2a6512d596dc95ba34aa20fb77106f641d7018c603291 |
Hashes for accera_gpu-1.2.13-cp38-cp38-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 553e0258222cb64756d22d962e1e8329ac604bd754e66db6ae941e6df2cfed9c |
|
MD5 | 40e152561c4580e707297a2e9214e3fb |
|
BLAKE2b-256 | ff2956b7d7c8094838d704c2d15f961d79dcf89d2365eff50c53a14c739fe6ce |
Hashes for accera_gpu-1.2.13-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 221e229ace7639d5c9da18d7834675282754cbbf214a53d3c0aeb686d26d29cd |
|
MD5 | 1b1ce7800874e83870a103b9dd3a518f |
|
BLAKE2b-256 | f7b400230d3c271fdc7a57692eb7d9a5b0f69a16bfca675f7bee6642744b265f |
Hashes for accera_gpu-1.2.13-cp37-cp37m-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bb14a27d80783e42844980d9c4b6799787027bb69cf6b9ce2160aba6df3a6082 |
|
MD5 | baa16d77412d75e43c97f23607369bd4 |
|
BLAKE2b-256 | d3b4493c567a72ac94ff6f5799088573eca65ad0a73c2b31251ce65a3bfd4c67 |
Hashes for accera_gpu-1.2.13-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3ea3de6c093c5ba772e6b1257de20f4f7f672314d1b1fb711a9083e6aff6e30f |
|
MD5 | 5eeac45d50628f540dade6cee3441dac |
|
BLAKE2b-256 | f55a6d1cb5505c423955003ac58ac76561c90541323665b2544248826f472bef |