Akira Nukada
- Hardware and Architecture top 1%
- Computer Networks and Communications top 2%
- Electrical and Electronic Engineering
- Information Systems top 5%
- Artificial Intelligence top 10%
- Co-authors
- Satoshi MatsuokaToshio EndoNaoya MaruyamaTakayuki AokiTakashi ShimokawabeTomohiro TakakiAkinori YamanakaHiroyuki Takizawa
- Topics
- Parallel Computing and Optimization Techniques (25 papers)Advanced Data Storage Technologies (15 papers)Distributed and Parallel Computing Systems (7 papers)
- Journals
- Parallel ComputingThe International Journal of High Performance Computing ApplicationsComputer Science - Research and Development
- Partner nations
- JapanChinaUnited States
In The Last Decade
Akira Nukada
33 papers receiving 916 citations
Peers
Comparison fields: 5 of 69
- Hardware and Architecture 584
- Computer Networks and Communications 523
- Electrical and Electronic Engineering 155
- Information Systems 134
- Artificial Intelligence 104
Countries citing papers authored by Akira Nukada
This map shows the geographic impact of Akira Nukada'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 Akira Nukada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akira Nukada more than expected).
Fields of papers citing papers by Akira Nukada
This network shows the impact of papers produced by Akira Nukada. 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 Akira Nukada. The network helps show where Akira Nukada may publish in the future.
Co-authorship network of co-authors of Akira Nukada
This figure shows the co-authorship network connecting the top 25 collaborators of Akira Nukada. A scholar is included among the top collaborators of Akira Nukada 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 Akira Nukada. Akira Nukada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 52 | |
| 5 | 14 | |
| 6 | 17 | |
| 7 | 4 | |
| 8 | 12 | |
| 9 | Efficient PageRank on GPU Clusters | 2 |
| 10 | 32 | |
| 11 | 15 | |
| 12 | 129 | |
| 13 | 46 | |
| 14 | CG on GPU-enhanced Clusters | 0 |
| 15 | Performance Evaluation of Software-Based ECC for GPUs | 1 |
| 16 | 13 | |
| 17 | 12 | |
| 18 | 25 | |
| 19 | 1 | |
| 20 | 1 |
About Akira Nukada
Akira Nukada is a scholar working on Hardware and Architecture, Computational Mathematics and Computer Networks and Communications, having authored 35 papers that have together received 957 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (25 papers), Advanced Data Storage Technologies (15 papers) and Distributed and Parallel Computing Systems (7 papers). The work is most often cited by research in Hardware and Architecture (584 citations), Computer Networks and Communications (523 citations) and Computational Mathematics (10 citations). Akira Nukada has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Satoshi Matsuoka, Toshio Endo, Naoya Maruyama, Takayuki Aoki, Satoshi Matsuoka, Satoshi Matsuoka, Takashi Shimokawabe, Tomohiro Takaki, Akinori Yamanaka and Hiroyuki Takizawa. Their work appears in journals such as Parallel Computing, The International Journal of High Performance Computing Applications and Computer Science - Research and Development.
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.