Wen-mei Hwu  

 



  ![](/sites/default/files/person/Wen-Mei%20Hwu%20Department%20Head%206%20%282%29.jpg)

  

 Wen-mei Hwu joined NVIDIA in February 2020 as Senior Distinguished Research Scientist, after spending 32 years at the University of Illinois at Urbana-Champaign, where he was a Professor, Sanders-AMD Endowed Chair, Acting Department Head and Chief Scientist of the Parallel Computing Institute. Hwu and his Illinois team developed the superblock compiler scheduling and optimization framework that has been adopted by virtually all modern vendor and open-source compilers today. In 2008, Hwu became the director of NVIDIA's first CUDA Center of Excellence. In 2010, Hwu co-authored the popular textbook "Programming Massively Parallel Processors - a Hands-on Approach" with the then NVIDIA Chief Scientist David Kirk. Through his highly cited publications, Hwu and his Illinois team set the foundation for programming and compiler techniques for modern GPU computing. For his research contributions, Hwu received the ACM SigArch Maurice Wilkes Award, the ACM Grace Murray Hopper Award, the IEEE Computer Society Charles Babbage Award, the ISCA Influential Paper Award, the MICRO Test-of-Time Award, the IEEE Computer Society B. R. Rau Award, the CGO Test-of-Time Award and the Distinguished Alumni Award in CS of the University of California, Berkeley. He has also won numerous best paper awards for major conferences. For his achievements as an educator, Hwu received the National-level HKN Holmes MacDonald Outstanding Teaching Award, ECE Department Outstanding Teacher Award, College of Engineering Collins Award of Innovative Teaching and the College of Engineering Rose Award for Teaching Excellence. He is a Fellow of IEEE and ACM.



   Research Area(s)

[Artificial Intelligence and Machine Learning ](/index.php/research-area/machine-learning-artificial-intelligence)

[Computer Architecture](/index.php/research-area/computer-architecture)

[High Performance Computing](/index.php/research-area/high-performance-computing)

[Storage and Systems](/index.php/research-area/storage-and-systems)

 

 

  

 Main Field of Interest

[Storage and Systems](/index.php/research-area/storage-and-systems)

 

  

 Google Scholar

[https://scholar.google.com/citations?user=ohjQPx8AAAAJ&hl=en](https://scholar.google.com/citations?user=ohjQPx8AAAAJ&hl=en)

 

  

 

 

 



 ### Publications

 

### 2023 

[IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research](/index.php/publication/2023-08_igb-addressing-gaps-labeling-features-heterogeneity-and-size-public-graph)

Arpandeep Khatua, [Vikram Sharma Mailthody](/index.php/person/vikram-sharma-mailthody-0), Bhagyashree Taleka, Tengfei Ma, Xiang Song, [Wen-mei Hwu](/index.php/person/wen-mei-hwu)



[KDD'23](https://kdd.org/kdd2023)









### 2021 

[Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture](/publication/2021-08_large-graph-convolutional-network-training-gpu-oriented-data-communication)

Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, [Wen-mei Hwu](/person/wen-mei-hwu)



[Proceedings of the VLDB Endowment (VLDB)](https://dl.acm.org/doi/10.14778/3476249.3476264)









[Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture](/publication/2021-03_large-graph-convolutional-network-training-gpu-oriented-data-communication)

Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoglu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, [Wen-mei Hwu](/person/wen-mei-hwu)



[ArXiv](https://arxiv.org/abs/2103.03330)