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Average Ratings 0 Ratings
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
No
API Access
Has API
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Integrations
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Integrations
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Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
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