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Chiplet approaches to scale up and scale out machine learning computation, Prof. Zhengya Zhang, University of Michigan, Ann Arbor
Chiplet approaches to scale up and scale out machine learning computation, Prof. Zhengya Zhang, University of Michigan, Ann Arbor
Abstract Neural network (NN) models are rapidly increasing in size and complexity, surpassing the pace of NN chip upgrades. The development of monolithic chips to match these evolving models is both expensive and challenging. Alternatively, modular chiplets can be designed and reused to create multi-chip packages (MCPs) capable of addressing diverse NN models and tasks. ... Read more
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