[Eecs_phd] EECS Research Seminar-Breaking the Memory Bottleneck: Essential for High-Performance, Reliable and Secure AI Processors

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Title: Breaking the Memory Bottleneck:  Essential for High-Performance, Reliable and Secure AI Processors
Abstract:
As artificial intelligence (AI) grows in sophistication and demands ever-increasing computational power, traditional memory architectures are proving to be a significant bottleneck.This seminar aims to talk about possible solutions to overcome the memory limitations that has been the bottleneck to enable the full potential of future AI processors. Furthermore, it examines emerging memory technologies that hold the promise of revolutionizing AI processor designs. The seminar aims to spark discussion on how memory innovations can pave the path to the next generation AI processors.
Bio:
Dr. Xiaowei Chen  is an Associate Professor in the Department of Electrical and Computer Engineering at Cedarville University. His research focuses on developing innovative memory solutions and hardware-level security mechanisms to advance the performance, efficiency, and trustworthiness of AI processors.  Dr. Xiaowei Chen is particularly interested in addressing memory bottlenecks in emerging AI applications and exploring novel ways to empower future AI processors.

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