--- title: "Arvind Krishnamurthy — author profile and papers in our library" description: "Arvind Krishnamurthy: 5 papers on Elamur Research (2018–2025) — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/arvind-krishnamurthy/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/arvind-krishnamurthy/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Arvind Krishnamurthy # Arvind Krishnamurthy Arvind Krishnamurthy has 5 papers in our library, in 2018–2025, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Efficient models & compression](https://md.research.elamur.ai/free/en/topics/efficient-models/); often with [Luis Ceze](https://md.research.elamur.ai/free/en/authors/luis-ceze/), [Tianqi Chen](https://md.research.elamur.ai/free/en/authors/tianqi-chen/), [Lequn Chen](https://md.research.elamur.ai/free/en/authors/lequn-chen/). 5 papers in our library · 2018–2025 No OpenAlex profile matched yet. [📄 5 works in our library](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/#papers) · [🔗 Cited 902 times in our library](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/cited-by/) · [⭐ Paper Stars ranking: #1582](https://md.research.elamur.ai/free/en/paper-stars/page/16/#star-1582) 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=Arvind+Krishnamurthy) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Arvind+Krishnamurthy) · [dblp](https://dblp.org/search?q=Arvind+Krishnamurthy) · [ACL Anthology](https://aclanthology.org/search/?q=Arvind+Krishnamurthy) ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 5 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 · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [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/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Computational Theory and Mathematics · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Electrical and Electronic Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/electrical-and-electronic-engineering/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) ## Works by year ### 2020s [**2025** 1 paper](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/year/2025/) · [**2023** 2 papers](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/year/2023/) ### 2010s [**2019** 1 paper](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/year/2019/) · [**2018** 1 paper](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/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. **[FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/)** *(2025 · 177 citations)* FlashInfer is an attention engine for LLM inference serving. It targets two problems: serving workloads keep changing, and attention variants and GPU architectures differ widely. Today each serving system ships its own narrow attention kernels, which is costly to maintain. FlashInfer replaces them with one… 4. **[Atom: Low-bit Quantization for Efficient and Accurate LLM Serving](https://md.research.elamur.ai/free/en/papers/zhao-2023-atom-low-bit-quantization-efficient/)** *(2023 · 156 citations)* LLM serving relies on batching to keep GPUs busy, and quantization can further reduce memory use and compute cost. 5. **[Punica: Multi-Tenant LoRA Serving](https://md.research.elamur.ai/free/en/papers/chen-2023-punica-multi-tenant-lora-serving/)** *(2023 · 81 citations)* Organisations that fine-tune one base LLM with LoRA for many tenants usually end up running each adapter as a separate model. ## Co-authors here 12 of 14 co-authors with a page, the most papers together first. - [Luis Ceze](https://md.research.elamur.ai/free/en/authors/luis-ceze/) ×4 - [Tianqi Chen](https://md.research.elamur.ai/free/en/authors/tianqi-chen/) ×4 - [Lequn Chen](https://md.research.elamur.ai/free/en/authors/lequn-chen/) ×3 - [Zihao Ye](https://md.research.elamur.ai/free/en/authors/zihao-ye/) ×3 - [Baris Kasikci](https://md.research.elamur.ai/free/en/authors/baris-kasikci/) ×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 - [Lianmin Zheng](https://md.research.elamur.ai/free/en/authors/lianmin-zheng/) ×2 - [Thierry Moreau](https://md.research.elamur.ai/free/en/authors/thierry-moreau/) ×2 - [Ziheng Jiang](https://md.research.elamur.ai/free/en/authors/ziheng-jiang/) ×2 - [Danyang Zhuo](https://md.research.elamur.ai/free/en/authors/danyang-zhuo/) - [Kan Zhu](https://md.research.elamur.ai/free/en/authors/kan-zhu/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - MLSys 2024 ×3 ## Cited by Papers of our library cite their works 902 times (of the 149,439 papers whose bibliographies we read); [45 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/arvind-krishnamurthy/cited-by/). Updated 2 November 2026