Chimera GPNPU is engineered to revolutionize AI/ML computational capabilities on single-core architectures. It efficiently handles matrix, vector, and scalar code, unifying AI inference and traditional C++ processing under one roof. By alleviating the need for partitioning AI workloads between different processors, it streamlines software development and drastically speeds up AI model adaptation and integration. Ideal for SoC designs, the Chimera GPNPU champions an architecture that is both versatile and powerful, handling complex parallel workloads with a single unified binary. This configuration not only boosts software developer productivity but also ensures an enduring flexibility capable of accommodating novel AI model architectures on the horizon. The architectural fabric of the Chimera GPNPU seamlessly blends the high matrix performance of NPUs with C++ programmability found in traditional processors. This core is delivered in a synthesizable RTL form, with scalability options ranging from a single-core to multi-cluster designs to meet various performance benchmarks. As a testament to its adaptability, the Chimera GPNPU can run any AI/ML graph from numerous high-demand application areas such as automotive, mobile, and home digital appliances. Developers seeking optimization in inference performance will find the Chimera GPNPU a pivotal tool in maintaining cutting-edge product offerings. With its focus on simplifying hardware design, optimizing power consumption, and enhancing programmer ease, this processor ensures a sustainable and efficient path for future AI/ML developments.
