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Description
L-Edit MEMS stands out as the premier platform for 3D MEMS design. The initial phase of creating a digital twin for MEMS devices starts with capturing designs in L-Edit. Designers in the MEMS field gain significant advantages from an integrated environment that encompasses device design, modeling for fabrication, and connections to FEM analysis tools. As the leading standard for MEMS design, L-Edit MEMS is uniquely equipped with true native curve support, making it the sole tool crafted specifically for MEMS and integrated circuit design. This platform serves as the cornerstone for the MEMS digital twin, facilitating not only device design but also 3D modeling of fabrication and simulations through established partnerships. Users can generate a 3D solid model based on layout data and descriptions of the fabrication process. It provides an insightful 3D graphical representation of the MEMS fabrication journey. Furthermore, it supports multi-physics simulations in conjunction with widely-used FEM analysis tools, allowing for the export of models to FEM/BEM simulators for thorough 3D evaluations. With its component libraries, design reuse is made simple and efficient, enhancing productivity in the MEMS design process. Ultimately, L-Edit MEMS offers a comprehensive suite of tools that empowers designers to innovate and streamline their workflows effectively.
Description
NVIDIA Modulus is an advanced neural network framework that integrates the principles of physics, represented through governing partial differential equations (PDEs), with data to create accurate, parameterized surrogate models that operate with near-instantaneous latency. This framework is ideal for those venturing into AI-enhanced physics challenges or for those crafting digital twin models to navigate intricate non-linear, multi-physics systems, offering robust support throughout the process. It provides essential components for constructing physics-based machine learning surrogate models that effectively merge physics principles with data insights. Its versatility ensures applicability across various fields, including engineering simulations and life sciences, while accommodating both forward simulations and inverse/data assimilation tasks. Furthermore, NVIDIA Modulus enables parameterized representations of systems that can tackle multiple scenarios in real time, allowing users to train offline once and subsequently perform real-time inference repeatedly. As such, it empowers researchers and engineers to explore innovative solutions across a spectrum of complex problems with unprecedented efficiency.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
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
Siemens
Founded
1847
Country
United States
Website
eda.sw.siemens.com/en-US/ic/ic-custom/mems-design/mems/
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/modulus