Machine Learning Inference IP 

Scales from 1 to 864 TOPs
Serves All Markets - Includes Safety Enhanced Version for Automotive Designs
Runs Classic ML Models, LLMs, Transformers - Every Operator, Every Network!

SIMPLIFY YOUR SOC DESIGN

And Speed Up Porting of New ML Models

Quadric has the leading processor architecture optimized for on-device artificial intelligence computing. Only the Quadric Chimera GPNPU delivers high ML inference performance and also runs complex C++ code without forcing the developer to artificially partition code between two or three different kinds of processors.

Quadric’s Chimera GPNPU is a licensable processor that scales from 1 to 864 TOPs.  Chimera GPNPUs run all ML networks - including classical backbones, vision transformers, and large language models.

simplify your soc design

And Speed Up Porting of New ML Models

Quadric is the leading processor architecture optimized for on-device artificial intelligence computing. Only the Quadric Chimera GPNPU delivers high ML inference performance and also runs complex C++ code without forcing the developer to artificially partition code between two or three different kinds of processors.

Quadric’s Chimera GPNPU is a licensable processor that scales from 1 to 864 TOPs.  Chimera GPNPUs run all ML networks - including classical backbones, vision transformers, and large language models.

Design your Soc faster with Chimera GPNPU

One architecture for ML inference plus pre-and-post processing simplifies SoC hardware design and radically speeds up ML model porting and software  application programming.

Three REASONS TO CHOOSE the chimera GPNPU

1
Handles matrix and vector operations and scalar (control) code in one execution pipeline. No need to artificially partition application code (C++ code, ML graph code) between different kinds of processors.
2
Runs EVERY kind of model - from classic backbones, to vision transformers, to Large Language Models (LLMs)
3
Up to 864 TOPs. A solution for every application segment - including ASIL-ready cores for Automotive applications
Find out more about the chimera GPNPU

Quadric Developer studio

Quadric’s DevStudio provides easy simulation of AI software and visualization of SoC design choices.
Learn more about developer studio

Quadric In the news

Quadric Insights
ConvNext is a Winner!
July 19, 2024

On Chimera QC Ultra it runs 28x faster than DSP+NPU ConvNext is one of today’s leading new ML networks. Frankly, it just doesn’t run on most NPUs. So if your AI/ML solution relies on an […]

Read More
KANs Upend the AL/ML Scene, and We’re Ready
July 3, 2024

What’s the biggest challenge for AI/ML? Power consumption. How are we going to meet it?  In late April 2024, a novel AI research paper was published by researchers from MIT and CalTech proposing a fundamentally […]

Read More
Failback Fails.  Massive Failure!
May 29, 2024

Not just a little slow down. A massive failure! Conventional AI/ML inference silicon designs employ a dedicated, hardwired matrix engine – typically called an “NPU” – paired with a legacy programmable processor – either a […]

Read More
ConvNext is a Winner!
July 19, 2024

On Chimera QC Ultra it runs 28x faster than DSP+NPU ConvNext is one of today’s leading new ML networks. Frankly, it just doesn’t run on most NPUs. So if your AI/ML solution relies on an […]

Read More
KANs Upend the AL/ML Scene, and We’re Ready
July 3, 2024

What’s the biggest challenge for AI/ML? Power consumption. How are we going to meet it?  In late April 2024, a novel AI research paper was published by researchers from MIT and CalTech proposing a fundamentally […]

Read More
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