Making Intelligent Computing More Efficient: A Redundancy-Centric Approach

Speaker:  Xipeng Shen – Raleigh, NC, United States
Topic(s):  Software Engineering and Programming

Abstract

Modern computing, driven by advances in machine learning and AI, is becoming increasingly intelligent, while also more computationally intensive and efficiency-critical. This talk will present a redundancy-centric approach to maximizing the efficiency of intelligent computing across Deep Neural Networks, Graph Neural Networks, and Data Analytics. The approach focuses on identifying and eliminating redundancy in computations through innovations in online clustering, compression, and binarization. These optimizations result in significant speedups, ranging from several to hundreds of times faster, with minimal or no accuracy loss, on devices ranging from microcontrollers to GPU servers and supercomputers.

About this Lecture

Number of Slides:  70
Duration:  75 minutes
Languages Available:  Chinese (Simplified), English
Last Updated: 

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