Machine Learning Inference IP 

Quadric's Chimera General Purpose Neural Processing Unit (GPNPU)

Faster Porting - For ANY Machine Learning Model
Faster Time to Market
Runs Classic ML Models, Runs LLMs, Runs Transformers - Runs Everything!
porting time in weeks

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 16 TOPs.  Chimera GPNPUs run all types ML networks - including classical backbones, vision transformers, and large language models.

Design your Soc faster with Chimera GPNPU

Traditional Design

Quadric GPNPU Design

One architecture for ML inference plus pre-and-post processing simplifies SoC hardware design and software 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
Scales from 1 to 16 TOPs in a single core, and multicore scales to >100 TOPs
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 Insights

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It Will Make for a Much Better NPU Vendor Evaluation. We’ve written before about the ways benchmarks for NPUs can be manipulated to the point where you just can’t trust them. There are two common […]

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Llama2, YOLO Family and MediaPipe family of networks now available October 31, 2023 Quadric today delivered a Halloween treat for all registered users of the Quadric Developers’ Studio. (Link).   This latest update of the industry’s […]

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Is the Transformer Era Over?

Wait! Didn’t That Era Just Begin? The idea of transformer networks has existed since the seminal publication of the Attention is All You Need paper by Google researchers in June 2017.  And while transformers quickly […]

Read More
Why You Should Create Your Own NPU Benchmarks

It Will Make for a Much Better NPU Vendor Evaluation. We’ve written before about the ways benchmarks for NPUs can be manipulated to the point where you just can’t trust them. There are two common […]

Read More
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