semvec/pypi-packages huggingface dataset:
accera-llvm 15.0.101
Accera LLVM Binaries
License: MIT License
Requires Python: ~=3.7

# Accera LLVM

## Introduction

[Accera](https://pypi.org/project/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-llvm

The `accera-llvm` package contains pre-compiled custom LLVM 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](https://github.com/microsoft/Accera).

Supported platforms:

* Linux (manylinux) x64
* macOS x64
* Windows x64
accera-gpu 1.2.29
Accera GPU Support
License: MIT License
Requires Python: ~=3.7

# Accera GPU

## Accera

[Accera](https://pypi.org/project/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](https://github.com/microsoft/Accera).
accera-compilers 1.2.29
Accera Compilers
License: MIT License
Requires Python: ~=3.7

# Accera Compilers

## Accera

[Accera](https://pypi.org/project/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](https://github.com/microsoft/Accera).