Webinar: The Convergence of Edge Accelerators

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ABSTRACT

Neural rendering. Offloading overloaded NPUs. Protection against evolving AI models. Developer-friendly programming. Reduced system complexity. There are many reasons why edge AI systems benefit from a GPU that delivers fast, efficient and fully programmable AI acceleration.

In this session, we’ll explore a new approach to processor design: a single architecture capable of accelerating graphics, compute and AI workloads on the same silicon, through a common software stack. Discover how hardware and software designed around data locality can minimise bandwidth movement, maximise efficiency and simplify system integration, while giving developers the flexibility to adapt as AI workloads continue to evolve.

And while AI is transforming edge devices, graphics performance still matters. Learn how a converged architecture can deliver the best of both worlds: cutting-edge AI acceleration without compromising the visual experiences users expect.

SPEAKER

Nick Mariette is Product Director for E-Series and future GPU platforms at Imagination Technologies, responsible for product strategy and roadmap execution, with over 20 years’ experience bringing complex networking, audio, and video technologies to market.

*This Webinar is in Partnership with SemiWiki and Imagination Technologies*

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