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What is MPI for Python (mpi4py)?

In recent times, high-performance computing has become increasingly available to a larger pool of researchers in the scientific field than it ever has been before. The effective synergy of high-quality open-source software and reasonably priced hardware has played a crucial role in the widespread utilization of Beowulf class clusters and workstation clusters. Among the various approaches to parallel computation, message-passing has stood out as a notably efficient model. This approach is particularly advantageous for distributed memory systems and is heavily relied upon in today’s most challenging scientific and engineering tasks related to modeling, simulation, design, and signal processing. However, the environment for portable message-passing parallel programming used to be complicated, as developers had to navigate a multitude of incompatible choices. Fortunately, this scenario has vastly improved since the MPI Forum established its standard specification, which has simplified the development process considerably. Consequently, researchers are now able to dedicate more of their efforts to advancing their scientific research instead of dealing with the intricacies of programming. This shift not only enhances productivity but also fosters innovation across various disciplines.

What is GASP?

GASP is a highly adaptable flow solver that effectively manages both structured and unstructured multi-block setups, adeptly solving the Reynolds Averaged Navier-Stokes (RANS) equations as well as the heat conduction equations relevant to solid materials. The solver employs a hierarchical-tree architecture for organization, which facilitates smooth pre- and post-processing all within a unified interface. It is capable of addressing both steady and unsteady three-dimensional RANS equations along with their various subsets, utilizing a multi-block grid topology that supports unstructured meshes made up of tetrahedra, hexahedra, prisms, and pyramids. Furthermore, GASP incorporates a portable extensible toolkit designed for scientific computations, significantly enhancing its adaptability. By decoupling turbulence and chemistry processes, the system achieves greater computational efficiency. It is compatible with a diverse range of parallel computing environments, including cluster configurations, and maintains a user-friendly approach to integrated domain decomposition. This robust architecture makes GASP an excellent choice for numerous applications in fluid dynamics, ensuring that users can tackle complex simulations with confidence. Additionally, its continual updates and support reflect a commitment to staying at the forefront of technological advancements in computational fluid dynamics.

Media

Media

Integrations Supported

C
C++
Fortran
NumPy
Python

Integrations Supported

C
C++
Fortran
NumPy
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

MPI for Python

Company Website

mpi4py.readthedocs.io/en/stable/

Company Facts

Organization Name

AeroSoft

Company Location

United States

Company Website

www.aerosoftinc.com/gasp_main.php

Categories and Features

Categories and Features

CFD

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling

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