--- title: "Zhihao Jia — author profile and papers — Elamur Research" description: "Zhihao Jia, Carnegie Mellon University: 5 papers on Elamur Research (2018–2024), h-index 21 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/zhihao-jia/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/zhihao-jia/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Zhihao Jia # Zhihao Jia Zhihao Jia has 5 papers in our library, in 2018–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/); often with [Alex Aiken](https://md.research.elamur.ai/free/en/authors/alex-aiken/), [Matei Zaharia](https://md.research.elamur.ai/free/en/authors/matei-zaharia/), [Xupeng Miao](https://md.research.elamur.ai/free/en/authors/xupeng-miao/). 5 papers in our library · 2018–2024 [OpenAlex](https://openalex.org/A5062437461) · [ORCID](https://orcid.org/0000-0002-1270-5185) · [Wikidata](https://www.wikidata.org/wiki/Q130800474) · [**h-index 21**](https://openalex.org/authors/A5062437461) · [55 works](https://openalex.org/works?filter=author.id:A5062437461) · [1,847 citations](https://openalex.org/works?filter=author.id:A5062437461&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/zhihao-jia/#papers) · [🔗 Cited 415 times in our library](https://md.research.elamur.ai/free/en/authors/zhihao-jia/cited-by/) · [2 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #3523](https://md.research.elamur.ai/free/en/paper-stars/page/36/#star-3523) 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=Zhihao+Jia) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Zhihao+Jia) · [dblp](https://dblp.org/search?q=Zhihao+Jia) · [ACL Anthology](https://aclanthology.org/search/?q=Zhihao+Jia) ## Affiliations [🎓**Carnegie Mellon University** Pittsburgh · United States 2021–2026 · 51 papers*current*](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) · [🎓**Stanford University** Stanford · United States 2015–2024 · 14 papers](https://md.research.elamur.ai/free/en/universities/stanford-university/) · [🎓**Tsinghua University** Beijing · China 2012–2024 · 5 papers](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) · [🎓**Imperial College London** London · United Kingdom 2026 · 2 papers](https://md.research.elamur.ai/free/en/universities/imperial-college-london/) · [🏢**Microsoft** Redmond · United States 2022–2024 · 2 papers](https://md.research.elamur.ai/free/en/companies/microsoft/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 12 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 · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Computer Vision and Pattern Recognition · 3 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/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Networks and Communications · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-networks-and-communications/) 🧭 Topics 1 Research subjects and languages the work is about.[Language models & pretraining · 3 works](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/zhihao-jia/year/2024/) · [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/zhihao-jia/year/2023/) ### 2010s [**2019** 1 paper](https://md.research.elamur.ai/free/en/authors/zhihao-jia/year/2019/) · [**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/zhihao-jia/year/2018/) ## Papers The most cited first (OpenAlex and our library). 1. **[Beyond Data and Model Parallelism for Deep Neural Networks](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)** *(2018 · 280 citations)* Training large DNNs is now routinely spread across many GPUs, yet mainstream frameworks mostly rely on plain data parallelism or model parallelism. 2. **[SpotServe: Serving Generative Large Language Models on Preemptible Instances](https://md.research.elamur.ai/free/en/papers/miao-2023-spotserve-serving-generative-large-language/)** *(2023 · 145 citations)* SpotServe addresses the high cost of serving generative LLMs. It runs inference on preemptible cloud GPUs, such as AWS spot instances, which can be up to 90% cheaper than on-demand machines but can be reclaimed at any time. Earlier spot-based serving systems assumed that a model fits on one instance and handled… 3. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/)** *(2023 · 110 citations)* Generative LLMs are expensive to deploy. Their size and token-by-token generation make low-latency, high-throughput serving difficult, especially for organizations without large compute budgets. This survey by researchers at Purdue and Carnegie Mellon reviews the field from a machine-learning-systems perspective. It… 4. **[TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions](https://md.research.elamur.ai/free/en/papers/jia-2019-taso-optimizing-deep-learning-computation/)** *(2019 · 72 citations)* Deep learning frameworks such as TensorFlow, PyTorch, TensorRT and TVM speed up computation graphs by rewriting subgraphs into faster equivalent forms. 5. **[MagicPIG: LSH Sampling for Efficient LLM Generation](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)** *(2024 · 68 citations)* Serving long-context LLMs is constrained by the KV cache. It consumes GPU memory and makes decoding memory-bound. Many speedups keep only the highest-scoring keys (TopK attention). The authors show this is a biased estimator that breaks down when attention is spread out, as in aggregation tasks like common- or… ## All works 7 works of theirs in our library, the most cited first; 5 with a page here, the others link their original until we summarise them. 1. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/) 2. **[SpotServe: Serving Generative Large Language Models on Preemptible Instances](https://md.research.elamur.ai/free/en/papers/miao-2023-spotserve-serving-generative-large-language/) [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/)**Xupeng Miao, Chunan Shi, Jiangfei Duan, et al.*2023 · 145 citations* 3. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations* 4. [**TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph Substitutions SOSP 2019**Zhihao Jia, Oded Padon, James Thomas, et al.*2019 · 72 citations*](https://md.research.elamur.ai/free/en/papers/jia-2019-taso-optimizing-deep-learning-computation/) 5. [**MagicPIG: LSH Sampling for Efficient LLM Generation arXiv:2410.16179**Zhuoming Chen, Ranajoy Sadhukhan, Zihao Ye, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/) 6. **[PET: Optimizing Tensor Programs with Partially Equivalent Transformations and Automated Corrections ↗](https://www.usenix.org/system/files/osdi21-wang-haojie.pdf) OSDI 2021 · no summary yet**Haojie Wang et al.*2021 · 40 citations* 7. **[Redundancy-Free Computation Graphs for Graph Neural Networks ↗](https://arxiv.org/abs/1906.03707) arXiv (Cornell University) · no summary yet**Zhihao Jia et al.*2019 · 9 citations* ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Alex Aiken](https://md.research.elamur.ai/free/en/authors/alex-aiken/) ×2 - [Matei Zaharia](https://md.research.elamur.ai/free/en/authors/matei-zaharia/) ×2 - [Xupeng Miao](https://md.research.elamur.ai/free/en/authors/xupeng-miao/) ×2 - [Beidi Chen](https://md.research.elamur.ai/free/en/authors/beidi-chen/) - [Bin Cui](https://md.research.elamur.ai/free/en/authors/bin-cui/) - [Dahua Lin](https://md.research.elamur.ai/free/en/authors/dahua-lin/) - [Gabriele Oliaro](https://md.research.elamur.ai/free/en/authors/gabriele-oliaro/) - [Leon Bottou](https://md.research.elamur.ai/free/en/authors/leon-bottou/) - [Matthijs Douze](https://md.research.elamur.ai/free/en/authors/matthijs-douze/) - [Oded Padon](https://md.research.elamur.ai/free/en/authors/oded-padon/) - [Tianqi Chen](https://md.research.elamur.ai/free/en/authors/tianqi-chen/) - [Xinhao Cheng](https://md.research.elamur.ai/free/en/authors/xinhao-cheng/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/): [ACM Computing Surveys 2023](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/2023/) - [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/): [ASPLOS 2023](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/2023/) - OSDI 2021 - SOSP 2019 - SysML 2019 ## Cited by Papers of our library cite their works 415 times (of the 149,439 papers whose bibliographies we read); [31 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/zhihao-jia/cited-by/). Updated 2 November 2026