Suvinay Subramanian

1.4k total citations · 1 hit paper
23 papers, 939 citations indexed

About

Suvinay Subramanian is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Suvinay Subramanian has authored 23 papers receiving a total of 939 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 14 papers in Hardware and Architecture and 7 papers in Information Systems. Recurrent topics in Suvinay Subramanian's work include Parallel Computing and Optimization Techniques (14 papers), Interconnection Networks and Systems (9 papers) and Cloud Computing and Resource Management (6 papers). Suvinay Subramanian is often cited by papers focused on Parallel Computing and Optimization Techniques (14 papers), Interconnection Networks and Systems (9 papers) and Cloud Computing and Resource Management (6 papers). Suvinay Subramanian collaborates with scholars based in United States, United Kingdom and Switzerland. Suvinay Subramanian's co-authors include Tushar Krishna, Chia-Hsin Owen Chen, Li-Shiuan Peh, Anantha P. Chandrakasan, Anirudh Sivaraman, Hari Balakrishnan, Sunghyun Park, Joel Emer, Daniel Sánchez and Tom Edsall and has published in prestigious journals such as Computer, IEEE Micro and DSpace@MIT (Massachusetts Institute of Technology).

In The Last Decade

Suvinay Subramanian

22 papers receiving 909 citations

Hit Papers

TPU v4: An Optically Reco... 2023 2026 2024 2023 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings
    2023 215 citations Norman P. Jouppi, George Thomas Kurian et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Suvinay Subramanian United States 15 694 431 342 180 122 23 939
Pejman Lotfi-Kamran Iran 17 850 1.2× 821 1.9× 495 1.4× 183 1.0× 106 0.9× 48 1.2k
Jae W. Lee South Korea 16 645 0.9× 639 1.5× 328 1.0× 158 0.9× 180 1.5× 54 953
Doug Carmean United States 11 782 1.1× 878 2.0× 294 0.9× 132 0.7× 103 0.8× 17 1.2k
Özcan Öztürk United States 17 818 1.2× 860 2.0× 404 1.2× 181 1.0× 128 1.0× 138 1.2k
Ed Grochowski United States 8 909 1.3× 1.0k 2.4× 304 0.9× 202 1.1× 90 0.7× 15 1.3k
Dezun Dong China 15 665 1.0× 189 0.4× 296 0.9× 168 0.9× 161 1.3× 121 891
Jerónimo Castrillón Germany 17 478 0.7× 575 1.3× 264 0.8× 99 0.6× 86 0.7× 103 876
Midia Reshadi Iran 14 417 0.6× 167 0.4× 342 1.0× 94 0.5× 99 0.8× 96 675
Eric Sprangle United States 10 851 1.2× 976 2.3× 302 0.9× 137 0.8× 123 1.0× 11 1.2k
Ali Bakhoda Canada 5 1.2k 1.8× 1.3k 3.1× 355 1.0× 236 1.3× 94 0.8× 9 1.5k

Countries citing papers authored by Suvinay Subramanian

Since Specialization
Citations

This map shows the geographic impact of Suvinay Subramanian's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Suvinay Subramanian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suvinay Subramanian more than expected).

Fields of papers citing papers by Suvinay Subramanian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Suvinay Subramanian. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Suvinay Subramanian. The network helps show where Suvinay Subramanian may publish in the future.

Co-authorship network of co-authors of Suvinay Subramanian

This figure shows the co-authorship network connecting the top 25 collaborators of Suvinay Subramanian. A scholar is included among the top collaborators of Suvinay Subramanian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Suvinay Subramanian. Suvinay Subramanian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Subramanian, Suvinay, et al.. (2025). RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving. 974–989. 2 indexed citations
2.
Jouppi, Norman P., George Thomas Kurian, Sheng Li, et al.. (2023). TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings. 1–14. 215 indexed citations breakdown →
3.
Kao, Sheng-Chun, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, & Tushar Krishna. (2023). FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks. 295–310. 35 indexed citations
4.
Ying, Victor A., et al.. (2018). Harmonizing Speculative and Non-Speculative Execution in Architectures for Ordered Parallelism. 217–230. 8 indexed citations
5.
Subramanian, Suvinay, et al.. (2017). Fractal. 587–599. 15 indexed citations
6.
Abeydeera, Maleen, et al.. (2017). SAM: Optimizing Multithreaded Cores for Speculative Parallelism. 64–78. 8 indexed citations
7.
Subramanian, Suvinay, et al.. (2017). Fractal. ACM SIGARCH Computer Architecture News. 45(2). 587–599. 5 indexed citations
8.
Subramanian, Suvinay, et al.. (2016). Application of fuzzy soft matrices in medical diagnosis. International Journal of Statistics and Applied Mathematics. 1(1). 52–57. 1 indexed citations
9.
Subramanian, Suvinay, et al.. (2016). Data-centric execution of speculative parallel programs. 1–13. 22 indexed citations
10.
Sivaraman, Anirudh, Suvinay Subramanian, Mohammad Alizadeh, et al.. (2016). Programmable Packet Scheduling at Line Rate. DSpace@MIT (Massachusetts Institute of Technology). 44–57. 199 indexed citations
11.
Subramanian, Suvinay, et al.. (2016). Unlocking Ordered Parallelism with the Swarm Architecture. IEEE Micro. 36(3). 105–117. 16 indexed citations
12.
Subramanian, Suvinay, et al.. (2015). A scalable architecture for ordered parallelism. 228–241. 63 indexed citations
13.
Sivaraman, Anirudh, Suvinay Subramanian, Shang-Tse Chuang, et al.. (2015). Towards Programmable Packet Scheduling. 1–7. 24 indexed citations
14.
Chen, Chia-Hsin Owen, Suvinay Subramanian, Woo-Cheol Kwon, et al.. (2014). SCORPIO: A 36-core research chip demonstrating snoopy coherence on a scalable mesh NoC with in-network ordering. 25–36. 46 indexed citations
15.
Chen, Chia-Hsin Owen, Sunghyun Park, Suvinay Subramanian, et al.. (2014). SCORPIO: 36-core shared memory processor demonstrating snoopy coherence on a mesh interconnect. 1–20. 1 indexed citations
16.
Chen, Chia-Hsin Owen, Suvinay Subramanian, Woo-Cheol Kwon, et al.. (2014). SCORPIO. ACM SIGARCH Computer Architecture News. 42(3). 25–36. 89 indexed citations
17.
Chen, Chia-Hsin Owen, Sunghyun Park, Tushar Krishna, et al.. (2013). SMART: a single-cycle reconfigurable NoC for SoC applications. Design, Automation, and Test in Europe. 338–343. 51 indexed citations
18.
Sivaraman, Anirudh, Keith Winstein, Suvinay Subramanian, & Hari Balakrishnan. (2013). No silver bullet. 1–7. 48 indexed citations
19.
Subramanian, Suvinay, et al.. (2012). AN ADAPTIVE ALGORITHM FOR DYNAMIC PRIORITY BASED VIRTUAL MACHINE SCHEDULING IN CLOUD. 15 indexed citations
20.
Subramanian, Suvinay, Rahul Simha, & Bhagirath Narahari. (1998). Placement of Storage Nodes in a Network. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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