Gangwon Jo

517 total citations
13 papers, 363 citations indexed

About

Gangwon Jo is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Gangwon Jo has authored 13 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 13 papers in Hardware and Architecture and 3 papers in Information Systems. Recurrent topics in Gangwon Jo's work include Parallel Computing and Optimization Techniques (13 papers), Advanced Data Storage Technologies (8 papers) and Distributed and Parallel Computing Systems (6 papers). Gangwon Jo is often cited by papers focused on Parallel Computing and Optimization Techniques (13 papers), Advanced Data Storage Technologies (8 papers) and Distributed and Parallel Computing Systems (6 papers). Gangwon Jo collaborates with scholars based in South Korea and United States. Gangwon Jo's co-authors include Jaejin Lee, Sangmin Seo, Jungwon Kim, Jeesoo Lee, Jung-Hyun Kim, Jaehoon Jung, Jung‐Ho Park, Jun Lee, Daeyoung Park and Jung‐Hyun Kim and has published in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems, ACM SIGPLAN Notices and IEEE International Conference on High Performance Computing, Data, and Analytics.

In The Last Decade

Gangwon Jo

12 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gangwon Jo South Korea	8	319	299	130	34	31	13	363
Cedric Nugteren Netherlands	9	220 0.7×	193 0.6×	61 0.5×	28 0.8×	37 1.2×	18	260
Mitesh R. Meswani United States	10	332 1.0×	333 1.1×	124 1.0×	22 0.6×	75 2.4×	18	385
Xiangyong Ouyang United States	11	196 0.6×	436 1.5×	198 1.5×	24 0.7×	29 0.9×	16	460
Ehsan Totoni United States	10	220 0.7×	207 0.7×	95 0.7×	36 1.1×	52 1.7×	21	295
Rakesh Krishnaiyer United States	11	302 0.9×	306 1.0×	56 0.4×	48 1.4×	37 1.2×	17	380
Jun Shirako United States	12	448 1.4×	415 1.4×	103 0.8×	54 1.6×	30 1.0×	35	492
Ahmad Afsahi Canada	13	405 1.3×	496 1.7×	129 1.0×	33 1.0×	76 2.5×	72	561
Antoine Kaufmann United States	9	122 0.4×	351 1.2×	155 1.2×	43 1.3×	60 1.9×	17	378
Jason Poovey United States	7	194 0.6×	159 0.5×	52 0.4×	35 1.0×	60 1.9×	9	279
Milind Chabbi United States	13	417 1.3×	396 1.3×	159 1.2×	60 1.8×	62 2.0×	50	491

Countries citing papers authored by Gangwon Jo

Since Specialization

Citations

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

Fields of papers citing papers by Gangwon Jo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gangwon Jo

This figure shows the co-authorship network connecting the top 25 collaborators of Gangwon Jo. A scholar is included among the top collaborators of Gangwon Jo 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 Gangwon Jo. Gangwon Jo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Jung, Jaehoon, Daeyoung Park, Gangwon Jo, Jung‐Ho Park, & Jaejin Lee. (2021). SnuRHAC. 107–120. 2 indexed citations

2.

Jo, Gangwon, et al.. (2020). SOFF: An OpenCL High-Level Synthesis Framework for FPGAs. 295–308. 15 indexed citations

3.

Kim, Jung-Hyun, Gangwon Jo, Jaehoon Jung, Jungwon Kim, & Jaejin Lee. (2016). A distributed OpenCL framework using redundant computation and data replication. 553–569. 10 indexed citations

4.

Kim, Jung‐Hyun, Gangwon Jo, Jaehoon Jung, Jungwon Kim, & Jaejin Lee. (2016). A distributed OpenCL framework using redundant computation and data replication. ACM SIGPLAN Notices. 51(6). 553–569.

5.

Park, Jung‐Ho, et al.. (2016). PIPSEA. 17. 1255–1267. 7 indexed citations

6.

Jo, Gangwon, et al.. (2014). Accelerating LINPACK with MPI-OpenCL on Clusters of Multi-GPU Nodes. IEEE Transactions on Parallel and Distributed Systems. 26(7). 1814–1825. 23 indexed citations

7.

Jo, Gangwon, et al.. (2014). OpenCL framework for ARM processors with NEON support. 33–40. 16 indexed citations

8.

Seo, Sangmin, Jun Lee, Gangwon Jo, & Jaejin Lee. (2013). Exposing ILP in custom hardware with a dataflow compiler IR. 411–412. 2 indexed citations

9.

Jo, Gangwon, et al.. (2012). A SnuCL implementation of the LINPACK benchmark on clusters with multi-GPU nodes. IEEE International Conference on High Performance Computing, Data, and Analytics. 35. 1 indexed citations

10.

Kim, Jungwon, et al.. (2012). SnuCL. 341–352. 130 indexed citations

11.

Kim, Jungwon, et al.. (2012). OpenCL as a unified programming model for heterogeneous CPU/GPU clusters. 299–300. 10 indexed citations

12.

Kim, Jungwon, et al.. (2012). OpenCL as a unified programming model for heterogeneous CPU/GPU clusters. ACM SIGPLAN Notices. 47(8). 299–300. 4 indexed citations

13.

Seo, Sangmin, Gangwon Jo, & Jaejin Lee. (2011). Performance characterization of the NAS Parallel Benchmarks in OpenCL. 137–148. 143 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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