Industry Expert Blogs

Developing an agile software stack is important for successful AI deployment on the edge. We regularly encounter new machine learning models created from multiple AI frameworks that leverage the latest primitives and state-of-the-art ML model topologies. This Cambrian explosion has resulted from a fertile open-source community that has embraced AI and is now fueling a wide proliferation of ML models on the edge.

Models are being created by academia and industry alike and produced using cutting-edge tools and concepts; hence, running these models efficiently on a high-performance, up-to-date AI software stack can be a complex undertaking in any organization.

Cadence produces industry-leading foundational design IPs built from years of domain expertise and empowers computing platforms across the globe. Our dominance in the IP market has created a surge in demand for AI-based compute from all our existing customers and partners. For the last two decades, Tensilica has successfully provided scalable, configurable IPs used by a plethora of customers to produce edge and on-device SoCs. Tensilica IPs are prevalent in applications ranging from audio, vision, radar, automotive, and microcontroller-based sub-systems.

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