Ganesh Venkatesh

3.2k total citations · 1 hit paper
24 papers, 1.5k citations indexed

About

Ganesh Venkatesh is a scholar working on Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Ganesh Venkatesh has authored 24 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Hardware and Architecture, 11 papers in Computer Networks and Communications and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Ganesh Venkatesh's work include Parallel Computing and Optimization Techniques (15 papers), Low-power high-performance VLSI design (6 papers) and Interconnection Networks and Systems (6 papers). Ganesh Venkatesh is often cited by papers focused on Parallel Computing and Optimization Techniques (15 papers), Low-power high-performance VLSI design (6 papers) and Interconnection Networks and Systems (6 papers). Ganesh Venkatesh collaborates with scholars based in United States, Israel and Czechia. Ganesh Venkatesh's co-authors include Jack Sampson, Steven Swanson, Michael Taylor, Eriko Nurvitadhi, Debbie Marr, Saturnino Garcia, Jose Lugo-Martinez, Jaewoong Sim, Asit Mishra and David Sheffield and has published in prestigious journals such as IEEE Access, ACM SIGPLAN Notices and ACM SIGOPS Operating Systems Review.

In The Last Decade

Ganesh Venkatesh

22 papers receiving 1.5k citations

Hit Papers

Can FPGAs Beat GPUs in Ac... 2017 2026 2020 2023 2017 50 100 150 200 250
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. Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?
    2017 287 citations Eriko Nurvitadhi, Ganesh Venkatesh 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
Ganesh Venkatesh United States 13 834 664 645 422 290 24 1.5k
Jaewoong Sim United States 18 802 1.0× 631 1.0× 655 1.0× 532 1.3× 378 1.3× 33 1.6k
Brandon Reagen United States 14 705 0.8× 844 1.3× 462 0.7× 496 1.2× 529 1.8× 36 1.6k
Yakun Sophia Shao United States 19 1.2k 1.4× 1.1k 1.6× 705 1.1× 587 1.4× 401 1.4× 50 2.1k
Jeremy Fowers United States 10 620 0.7× 499 0.8× 550 0.9× 430 1.0× 350 1.2× 17 1.3k
Eric S. Chung United States 16 971 1.2× 537 0.8× 867 1.3× 390 0.9× 342 1.2× 31 1.7k
Ninghui Sun China 15 665 0.8× 711 1.1× 528 0.8× 804 1.9× 485 1.7× 63 1.7k
Srihari Cadambi United States 21 1.3k 1.5× 823 1.2× 964 1.5× 642 1.5× 424 1.5× 39 2.0k
Cody Hao Yu United States 15 492 0.6× 422 0.6× 326 0.5× 379 0.9× 364 1.3× 29 1.2k
Jongse Park United States 18 539 0.6× 835 1.3× 351 0.5× 581 1.4× 516 1.8× 43 1.5k
Eriko Nurvitadhi United States 20 698 0.8× 695 1.0× 486 0.8× 677 1.6× 492 1.7× 75 1.7k

Countries citing papers authored by Ganesh Venkatesh

Since Specialization
Citations

This map shows the geographic impact of Ganesh Venkatesh'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 Ganesh Venkatesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ganesh Venkatesh more than expected).

Fields of papers citing papers by Ganesh Venkatesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ganesh Venkatesh. 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 Ganesh Venkatesh. The network helps show where Ganesh Venkatesh may publish in the future.

Co-authorship network of co-authors of Ganesh Venkatesh

This figure shows the co-authorship network connecting the top 25 collaborators of Ganesh Venkatesh. A scholar is included among the top collaborators of Ganesh Venkatesh 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 Ganesh Venkatesh. Ganesh Venkatesh 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.
Li, Zhaoshuo, Wei Ye, Dilin Wang, et al.. (2023). Temporally Consistent Online Depth Estimation in Dynamic Scenes. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3017–3026. 8 indexed citations
2.
Yang, Haichuan, Yuan Shangguan, Dilin Wang, et al.. (2022). Omni-Sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR Via Supernet. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8197–8201. 7 indexed citations
3.
Park, Hyojin, et al.. (2021). Adaptive Template and Transition Map for Real-Time Video Object Segmentation. IEEE Access. 9. 116914–116926. 3 indexed citations
4.
Park, Hyojin, et al.. (2021). Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation. Seoul National University Open Repository (Seoul National University). 8401–8410. 29 indexed citations
5.
Venkatesh, Ganesh, et al.. (2018). Vehicle Tracking System Over Google Maps. International Journal of Scientific Research in Science Engineering and Technology. 4(4). 676–681. 1 indexed citations
6.
Micikevicius, Paulius, Sharan Narang, Gregory Diamos, et al.. (2017). Mixed Precision Training. arXiv (Cornell University). 62 indexed citations
7.
Nurvitadhi, Eriko, Ganesh Venkatesh, Jaewoong Sim, et al.. (2017). Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?. 5–14. 287 indexed citations breakdown →
8.
Venkatesh, Ganesh, Eriko Nurvitadhi, & Debbie Marr. (2017). Accelerating Deep Convolutional Networks using low-precision and sparsity. 2861–2865. 76 indexed citations
9.
Mishra, Asit, Eriko Nurvitadhi, Ganesh Venkatesh, Jonathan P. Pearce, & Debbie Marr. (2017). Fine-grained accelerators for sparse machine learning workloads. 635–640. 17 indexed citations
10.
Nurvitadhi, Eriko, David Sheffield, Jaewoong Sim, et al.. (2016). Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC. 77–84. 223 indexed citations
11.
Nurvitadhi, Eriko, Asit Mishra, Yu Wang, Ganesh Venkatesh, & Debbie Marr. (2016). Hardware Accelerator for Analytics of Sparse Data. 1616–1621. 12 indexed citations
12.
Venkatesh, Ganesh. (2013). APE. 1–10. 2 indexed citations
13.
Venkatesh, Ganesh, et al.. (2011). Quasi-ASICs: Trading Area for Energy by Exploiting Similarity in Synthesized Cores for Irregular Code. eScholarship (California Digital Library).
14.
Venkatesh, Ganesh, et al.. (2011). QsCores. 163–174. 99 indexed citations
15.
Sampson, Jack, et al.. (2011). Efficient complex operators for irregular codes. 491–502. 31 indexed citations
16.
Arora, Manish, Jack Sampson, Jonathan Babb, et al.. (2011). Reducing the Energy Cost of Irregular Code Bases in Soft Processor Systems. 210–213. 3 indexed citations
17.
Venkatesh, Ganesh, Jack Sampson, Saturnino Garcia, et al.. (2010). Conservation cores. ACM SIGARCH Computer Architecture News. 38(1). 205–218. 48 indexed citations
18.
Narayanasamy, Satish, Ganesh Venkatesh, Jack Sampson, et al.. (2006). Unbounded page-based transactional memory. 347–358. 81 indexed citations
19.
Narayanasamy, Satish, Ganesh Venkatesh, Jack Sampson, et al.. (2006). Unbounded page-based transactional memory. ACM SIGOPS Operating Systems Review. 40(5). 347–358. 2 indexed citations
20.
Narayanasamy, Satish, Ganesh Venkatesh, Jack Sampson, et al.. (2006). Unbounded page-based transactional memory. ACM SIGPLAN Notices. 41(11). 347–358. 9 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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