N2D2
CAD framework for designing and simulating DNNs on embedded platforms
Pricing
See website
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
—Overview
What is N2D2?
CEA-List's N2D2 is a CAD framework designed to facilitate the creation, simulation, and deployment of Deep Neural Networks (DNN) specifically tailored for embedded systems. It provides tools for developers to design efficient neural networks that can run on resource-constrained devices.
Key differentiator
“N2D2 stands out as a specialized CAD framework focused on the design, simulation, and deployment of DNNs specifically optimized for embedded systems.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Teams working on AI projects for resource-constrained devices
Developers needing to simulate and optimize DNNs for embedded systems
✕ Not a fit for
Projects requiring real-time processing with high latency requirements
Applications that do not require optimization for embedded hardware
Cost structure
Pricing
Free Tier
None
Starts at
See website
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Next step
Get Started with N2D2
Step-by-step setup guide with code examples and common gotchas.