--- title: "Ziheng Jiang · Jiangnan University — author profile and papers" description: "Ziheng Jiang, Jiangnan University: 4 papers on Elamur Research (2018–2024), h-index 15 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/ziheng-jiang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ziheng-jiang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ziheng Jiang # Ziheng Jiang Ziheng Jiang has 4 papers in our library, in 2018–2024, most of them on [GPU & parallel computing](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Arvind Krishnamurthy](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/), [Carlos Guestrin](https://md.research.elamur.ai/free/en/authors/carlos-guestrin/), [Eddie Yan](https://md.research.elamur.ai/free/en/authors/eddie-yan/). 4 papers in our library · 2018–2024 [OpenAlex](https://openalex.org/A5008448494) · [ORCID](https://orcid.org/0009-0001-7732-4391) · [Wikidata](https://www.wikidata.org/wiki/Q140835629) · [**h-index 15**](https://openalex.org/authors/A5008448494) · [49 works](https://openalex.org/works?filter=author.id:A5008448494) · [2,162 citations](https://openalex.org/works?filter=author.id:A5008448494&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 4 works in our library](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/#papers) · [🔗 Cited 789 times in our library](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/cited-by/) · [1 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #1696](https://md.research.elamur.ai/free/en/paper-stars/page/17/#star-1696) 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=Ziheng+Jiang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Ziheng+Jiang) · [dblp](https://dblp.org/search?q=Ziheng+Jiang) · [ACL Anthology](https://aclanthology.org/search/?q=Ziheng+Jiang) ## Affiliations [🏢**PowerChina** Beijing · China 2025–2026 · 4 papers*current*](https://ror.org/01varr368) · [🎓**Jiangnan University** Wuxi · China 2026 · 1 paper*current*](https://ror.org/04mkzax54) · [🎓**University of Washington** Seattle · United States 2018–2023 · 10 papers](https://md.research.elamur.ai/free/en/universities/university-of-washington/) · [🎓**Beijing Institute of Technology** Beijing · China 2010–2015 · 8 papers](https://md.research.elamur.ai/free/en/universities/beijing-institute-of-technology/) · [🏢**ByteDance** Beijing · China 2024–2025 · 2 papers](https://md.research.elamur.ai/free/en/companies/bytedance/) · [🎓**Dalian Maritime University** Dalian · China 2022 · 2 papers](https://md.research.elamur.ai/free/en/universities/dalian-maritime-university/) · [🏢**Jingdong** Beijing · China 2018 · 2 papers](https://md.research.elamur.ai/free/en/companies/jingdong/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 8 The field of science this work belongs to (OpenAlex fields).[Computer Science · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Hardware and Architecture · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Arts and Humanities · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) · [Artificial Intelligence · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Language and Linguistics · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) 🧭 Topics 2 Research subjects and languages the work is about.[GPU & parallel computing · 2 works](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 2 papers](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/year/2024/) ### 2010s [**2019** 1 paper](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/year/2019/) · [**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/year/2018/) ## Papers The most cited first (OpenAlex and our library). 1. **[TVM: An Automated End-to-End Optimizing Compiler for Deep Learning](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)** *(2018 · 1,384 citations)* Deep learning models increasingly need to run on very different hardware: server GPUs, phones, embedded boards, and custom accelerators such as FPGAs and TPU-like chips. 2. **[Learning to Optimize Tensor Programs](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)** *(2019 · 269 citations)* Deep learning systems depend on fast tensor operators such as matrix multiplication and convolution. Today these come mostly from hand-tuned vendor libraries like cuDNN, which cover only a narrow set of hardware and make every new device expensive to support. The authors treat operator implementation as a search… 3. **[MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs](https://md.research.elamur.ai/free/en/papers/jiang-2024-megascale-scaling-large-language-model/)** *(2024 · 157 citations)* When an LLM training job takes over a whole cluster of tens of thousands of GPUs, two engineering problems dominate. 4. **[FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/)** *(2024 · 67 citations)* Tensor parallelism splits individual layers of large models across GPUs. This lowers latency, but it adds AllGather and ReduceScatter traffic that can take a large share of runtime. Earlier overlap schemes, such as TransformerEngine, cut a GEMM and its collective into a few chunks, one per device, and schedule them… ## All works 5 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them. 1. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning arXiv:1802.04799**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,384 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/) 2. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/) 3. **[A Hardware–Software Blueprint for Flexible Deep Learning Specialization ↗](https://doi.org/10.1109/mm.2019.2928962) IEEE Micro · no summary yet**Thierry Moreau et al.*2019 · 184 citations* 4. [**MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs arXiv:2402.15627**Ziheng Jiang, Haibin Lin, Yinmin Zhong, et al.*2024 · 157 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-megascale-scaling-large-language-model/) 5. [**FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion arXiv:2406.06858**Li-Wen Chang, Wenlei Bao, Qi Hou, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/) ## Co-authors here 12 of 15 co-authors with a page, the most papers together first. - [Arvind Krishnamurthy](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/) ×2 - [Carlos Guestrin](https://md.research.elamur.ai/free/en/authors/carlos-guestrin/) ×2 - [Eddie Yan](https://md.research.elamur.ai/free/en/authors/eddie-yan/) ×2 - [Haibin Lin](https://md.research.elamur.ai/free/en/authors/haibin-lin/) ×2 - [Lianmin Zheng](https://md.research.elamur.ai/free/en/authors/lianmin-zheng/) ×2 - [Luis Ceze](https://md.research.elamur.ai/free/en/authors/luis-ceze/) ×2 - [Thierry Moreau](https://md.research.elamur.ai/free/en/authors/thierry-moreau/) ×2 - [Tianqi Chen](https://md.research.elamur.ai/free/en/authors/tianqi-chen/) ×2 - [Yinmin Zhong](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/) ×2 - [Chengquan Jiang](https://md.research.elamur.ai/free/en/authors/chengquan-jiang/) - [Xiang Li](https://md.research.elamur.ai/free/en/authors/xiang-li/) - [Xin Jin](https://md.research.elamur.ai/free/en/authors/xin-jin/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - IEEE Micro ## Cited by Papers of our library cite their works 789 times (of the 149,439 papers whose bibliographies we read); [59 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/cited-by/). Updated 2 November 2026