Dongup Kwon

401 citations
15 papers · 283 · h-index 9

Impact in

Papers in

Dongup Kwon

15 papers receiving 280 citations

Peers

Dongup Kwon
Comparison fields: 5 of 37
  • Hardware and Architecture 113
  • Computational Mathematics 3
  • Computer Networks and Communications 93
  • Software 15
  • Computer Vision and Pattern Recognition 62
Replace Vito Giovanni Castellana with:
Vito Giovanni Castellana United States
Alric Althoff United States
Fabian Schuiki Switzerland
Mark Gottscho United States
Samuel Pagliarini Estonia
Dipanjan Sengupta United States
Germain Haugou Italy
Jin Hyun Kim United States
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Carlos Álvarez Spain
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Citations per field
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Citations per year

Countries citing papers authored by Dongup Kwon

Since Specialization
Citations

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

Fields of papers citing papers by Dongup Kwon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Dongup Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dongup Kwon Line = papers co-authored together Dongup Kwon links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 202068
2 202147
3 201945
4 201823
5 202222
6 201921
7 201515
8 201713
9 20198
10 20185
11 20205
12 20194
13 20223
14
{FVM}: FPGA-assisted Virtual Device Emulation for Fast, Scalable, and Flexible Storage Virtualization
20203
15
A Fast and Flexible Hardware-based Virtualization Mechanism for Computational Storage Devices
20211

About Dongup Kwon

Dongup Kwon is a scholar working on Computer Networks and Communications, Information Systems, Hardware and Architecture, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 15 papers that have together received 283 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (8 papers), Parallel Computing and Optimization Techniques (6 papers), Advanced Neural Network Applications (6 papers), Cloud Computing and Resource Management (5 papers), Advanced Memory and Neural Computing (3 papers), Caching and Content Delivery (3 papers), Ferroelectric and Negative Capacitance Devices (2 papers) and Network Packet Processing and Optimization (2 papers). The work is most often cited by research in Hardware and Architecture (113 citations), Computational Mathematics (3 citations), Computer Networks and Communications (93 citations), Software (15 citations) and Computer Vision and Pattern Recognition (62 citations). Dongup Kwon has collaborated with scholars based in South Korea, United Kingdom and United States. Frequent co-authors include Jangwoo Kim, Eriko Nurvitadhi, Byoungyoung Lee, Andrew Boutros, Youngsok Kim, Dayeol Lee, Ali Jafari, Raghavan Kumar, Jaewon Lee and Bogdan Pasca. Their work appears in journals such as ACM Transactions on Storage, IEEE Computer Architecture Letters, ACM Transactions on Architecture and Code Optimization, USENIX Annual Technical Conference and Seoul National University Open Repository (Seoul National University).

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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