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Description

Fortran has been meticulously crafted for high-performance tasks in the realms of science and engineering. It boasts reliable and well-established compilers and libraries, enabling developers to create software that operates with impressive speed and efficiency. The language's static and strong typing helps the compiler identify numerous programming mistakes at an early stage, contributing to the generation of optimized binary code. Despite its compact nature, Fortran is remarkably accessible for newcomers. Writing complex mathematical and arithmetic expressions over extensive arrays feels as straightforward as jotting down equations on a whiteboard. Moreover, Fortran supports native parallel programming, featuring an intuitive array-like syntax that facilitates data exchange among CPUs. This versatility allows users to execute nearly identical code on a single processor, a shared-memory multicore architecture, or a distributed-memory high-performance computing (HPC) or cloud environment. As a result, Fortran remains a powerful tool for those aiming to tackle demanding computational challenges.

Description

Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Cython
MPI for Python (mpi4py)
AdaMULTI IDE
Arm Forge
Arm MAP
CUDA
CodeConvert
Codecov
Coiled
Devin
Geany
Helix Editor
Mayhem Code Security
NVIDIA FLARE
Oracle SQL Developer
UEStudio
Unify AI
Zed
h5py
jEdit

Integrations

Cython
MPI for Python (mpi4py)
AdaMULTI IDE
Arm Forge
Arm MAP
CUDA
CodeConvert
Codecov
Coiled
Devin
Geany
Helix Editor
Mayhem Code Security
NVIDIA FLARE
Oracle SQL Developer
UEStudio
Unify AI
Zed
h5py
jEdit

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Fortran

Country

United States

Website

fortran-lang.org

Vendor Details

Company Name

NumPy

Website

numpy.org

Product Features

Product Features

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Alternatives

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