What is Quadric?
Quadric offers an advanced processor architecture specifically engineered for on-device artificial intelligence tasks. Its core product, the Chimera GPNPU (General-Purpose Neural Processing Unit), combines high machine learning inference performance with the capability to execute complex C++ code within a single processor. This unified approach eliminates the need for developers to partition code across multiple processor types, simplifying System-on-Chip (SoC) hardware design and accelerating the porting of new ML models.
The Chimera GPNPU architecture is designed for scalability, offering performance ranging from 1 to 864 TOPs (Tera Operations Per Second). It supports a wide array of machine learning networks, encompassing classical backbones, modern vision transformers, and large language models (LLMs). Quadric also provides safety-enhanced versions tailored for automotive applications and supports designers with the Chimera SDK and Quadric DevStudio for development and visualization.
Features
- Unified Architecture: Handles matrix, vector, and scalar (control) code in one execution pipeline, eliminating code partitioning.
- Broad Model Support: Runs diverse ML models including classical backbones, vision transformers, and Large Language Models (LLMs).
- High Scalability: Offers performance options ranging from 1 to 864 TOPs.
- C++ Code Execution: Runs complex C++ code alongside ML inference.
- Automotive Ready: Provides safety-enhanced cores (ASIL-ready) for automotive applications.
- Developer Tools: Includes Chimera SDK and Quadric DevStudio for design and development.
Use Cases
- Developing and deploying AI models on edge devices.
- Designing efficient System-on-Chip (SoC) solutions for AI applications.
- Implementing advanced driver-assistance systems (ADAS) in automotive applications.
- Running complex AI workloads like Vision Language Models (VLMs) on-device.
- Accelerating the porting and deployment of new machine learning models.
- Optimizing performance for applications requiring both ML inference and traditional C++ processing.
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