---
title: "Yinmin Zhong · Peking University — author profile and papers"
description: "Yinmin Zhong, Peking University: 6 papers on Elamur Research (2023–2024), h-index 8 — affiliations, topics, co-authors and who cites them…"
canonical: "https://research.elamur.ai/free/en/authors/yinmin-zhong/"
---
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# Yinmin Zhong

Yinmin Zhong has 6 papers in our library, in 2023–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [GPU & parallel computing](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/); often with [Xin Jin](https://md.research.elamur.ai/free/en/authors/xin-jin/), [Shengyu Liu](https://md.research.elamur.ai/free/en/authors/shengyu-liu/), [Xuanzhe Liu](https://md.research.elamur.ai/free/en/authors/xuanzhe-liu/).

6 papers in our library · 2023–2024

[OpenAlex](https://openalex.org/A5000644890) · [ORCID](https://orcid.org/0000-0002-2504-7652) · [**h-index 8**](https://openalex.org/authors/A5000644890) · [26 works](https://openalex.org/works?filter=author.id:A5000644890) · [240 citations](https://openalex.org/works?filter=author.id:A5000644890&sort=cited_by_count:desc) OpenAlex, 2026-10-14

[📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/#papers) · [🔗 Cited 1,379 times in our library](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/cited-by/) · [⭐ Paper Stars ranking: #2609](https://md.research.elamur.ai/free/en/paper-stars/page/27/#star-2609)

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=Yinmin+Zhong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yinmin+Zhong) · [dblp](https://dblp.org/search?q=Yinmin+Zhong) · [ACL Anthology](https://aclanthology.org/search/?q=Yinmin+Zhong)

## Affiliations

[🎓**Peking University** Beijing · China 2023–2026 · 17 papers*current*](https://md.research.elamur.ai/free/en/universities/peking-university/) · [🏢**DeepSeek** Hangzhou · China 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/companies/deepseek/)

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

## Fields, topics and concepts

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

📚 Shelves 7 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Hardware and Architecture · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/hardware-and-architecture/) · [Arts and Humanities · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Information Systems · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Networks and Communications · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) · [Artificial Intelligence · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 3 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/)

🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 4 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [GPU & parallel computing · 2 works](https://md.research.elamur.ai/free/en/topics/gpu-parallel-computing/)

## Works by year

### 2020s

[**2024** 4 papers](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/year/2024/) · [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/year/2023/)

## Papers

The most cited first (OpenAlex and our library).

1. **[DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving](https://md.research.elamur.ai/free/en/papers/zhong-2024-distserve-disaggregating-prefill-decoding-goodput/)** *(2024 · 409 citations)* LLM inference has two phases with different profiles. Prefill processes the whole prompt in one compute-heavy step. Decoding emits one token per step and is bound by memory bandwidth. Mainstream systems batch both phases on the same GPUs. As a result, prefill delays inflate TPOT, decoding work inflates TTFT, and both…
2. **[AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving](https://md.research.elamur.ai/free/en/papers/li-2023-alpaserve-statistical-multiplexing-model-parallelism/)** *(2023 · 170 citations)* AlpaServe asks how to serve many large deep learning models on a shared GPU cluster when request traffic is highly bursty.
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. **[LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism](https://md.research.elamur.ai/free/en/papers/wu-2024-loongserve-efficiently-serving-long-context/)** *(2024 · 131 citations)* Long-context LLMs (Claude-3, Gemini-1.5 and LWM all accept up to 1M tokens) create very uneven resource demands.
5. **[Fast Distributed Inference Serving for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2023-fast-distributed-inference-serving-large/)** *(2023 · 123 citations)* FastServe, from Peking University, is a distributed serving system for large language models that targets the latency of interactive applications.
6. **[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…

## Co-authors here

12 of 19 co-authors with a page, the most papers together first.

- [Xin Jin](https://md.research.elamur.ai/free/en/authors/xin-jin/) ×5
- [Shengyu Liu](https://md.research.elamur.ai/free/en/authors/shengyu-liu/) ×3
- [Xuanzhe Liu](https://md.research.elamur.ai/free/en/authors/xuanzhe-liu/) ×3
- [Bingyang Wu](https://md.research.elamur.ai/free/en/authors/bingyang-wu/) ×2
- [Haibin Lin](https://md.research.elamur.ai/free/en/authors/haibin-lin/) ×2
- [Hao Zhang](https://md.research.elamur.ai/free/en/authors/hao-zhang/) ×2
- [Ziheng Jiang](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/) ×2
- [Chengquan Jiang](https://md.research.elamur.ai/free/en/authors/chengquan-jiang/)
- [Joseph E. Gonzalez](https://md.research.elamur.ai/free/en/authors/joseph-e-gonzalez/)
- [Lianmin Zheng](https://md.research.elamur.ai/free/en/authors/lianmin-zheng/)
- [Peng Sun](https://md.research.elamur.ai/free/en/authors/peng-sun/)
- [Xiang Li](https://md.research.elamur.ai/free/en/authors/xiang-li/)

## Venues

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

- OSDI 2023 ×2
- [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/): [SOSP 2024](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/2024/)

## Cited by

Papers of our library cite their works 1,379 times (of the 149,439 papers whose bibliographies we read); [171 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yinmin-zhong/cited-by/).

Updated 2 November 2026
