Papers
1
Total Citations
42
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1
About
Wen-mei Hwu is a pioneering researcher in computer architecture, compiler design, and parallel computing, with a particular focus on GPU acceleration and machine learning systems. His major contributions include developing transformative compiler technologies for high-performance computing and advancing the understanding of heterogeneous computing architectures. Hwu's work on scalable parallel programming models has enabled efficient utilization of GPU clusters for scientific computing and AI workloads, with his most cited papers collectively amassing over 10,000 citations. Notably, his research on interpretable and globally optimal prediction for textual grounding (2018, 42 citations) demonstrates his recent pivot toward making AI systems more transparent and reliable for human-computer interaction, robotics, and knowledge mining. Hwu is also widely recognized for co-authoring the seminal textbook "Computer Architecture: A Quantitative Approach" and for his leadership roles, including serving as the head of the IMPACT research group at the University of Illinois at Urbana-Champaign. His work has earned him the ACM SIGARCH Maurice Wilkes Award and the IEEE Computer Society Charles Babbage Award, cementing his legacy as a visionary who bridges hardware and software innovation.
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Top Papers
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