Researchers from Tsinghua University Unveil ‘Gemini’: A New AI Approach to Boost Performance and Energy Efficiency in Chiplet-Based Deep Neural Network Accelerators

Researchers from multiple universities have addressed the challenge of designing large-scale DNN chiplet accelerators, focusing on optimizing monetary cost (MC), performance, and energy efficiency. The complexity arises from the interplay of various parameters, including network-on-chip (NoC) communication, core positions, and different DNN attributes. It is crucial to explore a vast design space for effective solutions. […]

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