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How to Unlock the power of Operator Fusion to Accelerate AI

Published by Quadric

The document outlines how operator fusion can significantly enhance AI application performance by combining multiple operations into a single step, minimizing memory movement and computational overhead. It focuses on Quadric's Chimera Graph Compiler, which utilizes operator fusion to optimize deep neural network (DNN) inference, particularly for high-performance edge applications. This approach improves energy efficiency by reducing power consumption and increases processing speed by retaining intermediate data within local memory. The document compares various processing architectures, such as GPUs, NPUs, and GPNPUs, explaining how each supports operator fusion to maximize AI workload efficiency.

 

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Related Categories Artificial Intelligence, GPUs, TPUs, AI Accelerators, AI Servers, AI Infrastructure, AI Processing Units, Computer Vision, Finance, Supply Chain & Manufacturing, Healthcare, Transport & Logistics, Education