The Chimera General Purpose Neural Processing Unit, or GPNPU, offers a transformative approach to AI computing. By integrating high-performance machine learning inference with the execution of scalar and vector operations in a single pipeline, it simplifies the SoC design, enhancing both flexibility and processing capability. The architecture is designed to handle diverse workloads across multiple application domains efficiently.
Engineered for flexibility, the Chimera GPNPU synthesizes the capabilities of NPUs and DSPs into a unified processor. This amalgamation facilitates seamless handling of machine learning tasks along with traditional signal processing functions within a single hardware entity. As a licensable IP core, it empowers developers to integrate advanced AI functions into diverse products, from consumer electronics to automotive systems.
Uniquely, the GPNPU architecture supports a broad spectrum of AI workloads, allowing it to adapt to the continuously evolving landscape of machine learning models. This is achieved through an innovative pipeline that supports modeless handling of matrix, vector, and scalar instructions, providing the ability to respond dynamically to changing ML graph processing needs.
The Chimera family is also characterized by its future-proof design, offering scalable performance that enables users to implement it across various process technologies, adapting effortlessly to specific application needs. This adaptability, combined with robust support for developers through its SDK, makes the GPNPU an optimal choice for organizations looking to future-proof their AI solutions.
