Purdue University Proposes Brain-Inspired AI Algorithm: Aiming to Break Through the Memory Wall and Significantly Reduce Energy Consumption
A research team from Purdue University and the Georgia Institute of Technology published a study in "Frontiers in Science," pointing out that the traditional Von Neumann architecture causes a 'memory wall' problem due to the separation of memory and processor, consuming a significant amount of time and energy. To address this bottleneck, they proposed building a new computer architecture using brain-inspired algorithms, aiming to significantly reduce the energy consumption of artificial intelligence models.
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