--- title: "Yangzihao Wang · Tencent — author profile and papers" description: "Yangzihao Wang, Tencent: 2 papers on Elamur Research (2015–2018), h-index 11 — affiliations, topics, co-authors and who cites them in…" canonical: "https://research.elamur.ai/free/en/authors/yangzihao-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yangzihao-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yangzihao Wang # Yangzihao Wang Yangzihao Wang has 2 papers in our library, in 2015–2018, most of them on [GPU & parallel computing](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/); often with [Wei He](https://md.research.elamur.ai/free/en/authors/wei-he/). 2 papers in our library · 2015–2018 [OpenAlex](https://openalex.org/A5053236964) · [**h-index 11**](https://openalex.org/authors/A5053236964) · [22 works](https://openalex.org/works?filter=author.id:A5053236964) · [1,359 citations](https://openalex.org/works?filter=author.id:A5053236964&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/yangzihao-wang/#papers) · [🔗 Cited 148 times in our library](https://md.research.elamur.ai/free/en/authors/yangzihao-wang/cited-by/) · [⭐ Paper Stars ranking: #3231](https://md.research.elamur.ai/free/en/paper-stars/page/33/#star-3231) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yangzihao+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yangzihao+Wang) · [dblp](https://dblp.org/search?q=Yangzihao+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Yangzihao+Wang) ## Affiliations [🏢**Tencent** Shenzhen · China 2020 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/tencent/) · [🎓**University of California, Davis** Davis · United States 2014–2017 · 12 papers](https://md.research.elamur.ai/free/en/universities/university-of-california-davis/) 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 5 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Hardware and Architecture · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Computer Graphics and Computer-Aided Design · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-graphics-and-computer-aided-design/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) 🧭 Topics 1 Research subjects and languages the work is about.[GPU & parallel computing · 1 work](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/) ## Works by year ### 2010s [**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/yangzihao-wang/year/2018/) · [**2015** 1 paper](https://md.research.elamur.ai/free/en/authors/yangzihao-wang/year/2015/) ## Papers The most cited first (OpenAlex and our library). 1. **[Gunrock: A High-Performance Graph Processing Library on the GPU](https://md.research.elamur.ai/free/en/papers/wang-2015-gunrock-high-performance-graph-processing/)** *(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](https://md.research.elamur.ai/free/en/papers/jia-2018-highly-scalable-deep-learning-training/)** *(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. - [Wei He](https://md.research.elamur.ai/free/en/authors/wei-he/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - PPoPP 2016 ## 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 →](https://md.research.elamur.ai/free/en/authors/yangzihao-wang/cited-by/). Updated 2 November 2026