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features
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Description

LAMMPS, which stands for Large-scale Atomic/Molecular Massively Parallel Simulator, is a powerful molecular dynamics software tailored for materials modeling. It has the capability to simulate various particle ensembles across liquid, solid, and gas phases, accommodating a diverse range of systems including atomic, polymeric, biological, solid-state, granular, coarse-grained, mesoscopic, and macroscopic forms by utilizing numerous interatomic potentials, force fields, and boundary conditions. Designed for two or three-dimensional simulations, LAMMPS can handle systems ranging from a handful of particles to billions, ensuring efficient performance on parallel computing architectures while also being user-friendly for modifications and extensions. The software incorporates potentials that cater to solid-state materials like metals and semiconductors, soft matter such as biomolecules and polymers, as well as coarse-grained or mesoscopic systems. Additionally, it serves as a versatile tool for modeling atomic interactions or, more broadly, as a parallel particle simulator applicable across atomic, meso, or continuum scales, making it a valuable resource in computational materials science.

Description

PanGu-α has been created using the MindSpore framework and utilizes a powerful setup of 2048 Ascend 910 AI processors for its training. The training process employs an advanced parallelism strategy that leverages MindSpore Auto-parallel, which integrates five different parallelism dimensions—data parallelism, operation-level model parallelism, pipeline model parallelism, optimizer model parallelism, and rematerialization—to effectively distribute tasks across the 2048 processors. To improve the model's generalization, we gathered 1.1TB of high-quality Chinese language data from diverse fields for pretraining. We conduct extensive tests on PanGu-α's generation capabilities across multiple situations, such as text summarization, question answering, and dialogue generation. Additionally, we examine how varying model scales influence few-shot performance across a wide array of Chinese NLP tasks. The results from our experiments highlight the exceptional performance of PanGu-α, demonstrating its strengths in handling numerous tasks even in few-shot or zero-shot contexts, thus showcasing its versatility and robustness. This comprehensive evaluation reinforces the potential applications of PanGu-α in real-world scenarios.

API Access

Has API

API Access

Has API

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Integrations

No details available.

Integrations

No details available.

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
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

LAMMPS

Country

United States

Website

www.lammps.org

Vendor Details

Company Name

Huawei

Founded

1987

Country

China

Website

arxiv.org/abs/2104.12369

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