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Yangzihao Wang

Yangzihao Wang has 2 papers in our library, in 2015–2018, most of them on GPU & parallel computing; often with Wei He.

2 papers in our library · 2015–2018

OpenAlex · h-index 11 · 22 works · 1,359 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 148 times in our library · ⭐ Paper Stars ranking: #3231

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢TencentShenzhen · China2020 · 1 papercurrent🎓University of California, DavisDavis · United States2014–2017 · 12 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksComputer Vision and Pattern Recognition · 2 worksHardware and Architecture · 2 worksComputer Graphics and Computer-Aided Design · 1 workArtificial Intelligence · 1 work

🧭 Topics 1Research subjects and languages the work is about.GPU & parallel computing · 1 work

 Works by year

2010s

20181 paper20151 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Gunrock: A High-Performance Graph Processing Library on the GPU (2015 · 419 citations)
    Graph analytics maps poorly onto GPUs. Graph data leads to irregular memory access and branching, and fast GPU code usually means writing hand-tuned "hardwired" kernels for each algorithm. Gunrock is an open-source, bulk-synchronous graph library for a single GPU that tries to offer both speed and ease of…
  2. Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes (2018 · 348 citations)
    Training large CNNs on ImageNet can take many hours even on several GPUs. Scaling out with synchronous data-parallel SGD runs into two obstacles: very large mini-batches tend to reduce test accuracy, and gradient exchange becomes a bottleneck as the GPU count grows. The authors, from Tencent and Hong Kong Baptist…

 Co-authors here

1 co-author with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 148 times (of the 149,439 papers whose bibliographies we read); 1 citing paper with a page here →.

Updated

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