Bernhard Egger

1.0k total citations
51 papers, 709 citations indexed

About

Bernhard Egger is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Bernhard Egger has authored 51 papers receiving a total of 709 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Computer Networks and Communications, 35 papers in Hardware and Architecture and 17 papers in Information Systems. Recurrent topics in Bernhard Egger's work include Parallel Computing and Optimization Techniques (29 papers), Advanced Data Storage Technologies (20 papers) and Cloud Computing and Resource Management (17 papers). Bernhard Egger is often cited by papers focused on Parallel Computing and Optimization Techniques (29 papers), Advanced Data Storage Technologies (20 papers) and Cloud Computing and Resource Management (17 papers). Bernhard Egger collaborates with scholars based in South Korea, Iran and United States. Bernhard Egger's co-authors include Jaejin Lee, Heonshik Shin, Changyeon Jo, Erik Gustafsson, Jae‐Jin Lee, Scott Mahlke, Hyunchul Park, Younghyun Cho, Hyungmin Cho and Sang Lyul Min and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Computers and Future Generation Computer Systems.

In The Last Decade

Bernhard Egger

50 papers receiving 679 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bernhard Egger South Korea 16 545 439 245 110 65 51 709
Rama Govindaraju United States 10 741 1.4× 392 0.9× 621 2.5× 122 1.1× 82 1.3× 16 906
Matthew J. Thazhuthaveetil India 12 467 0.9× 593 1.4× 186 0.8× 151 1.4× 54 0.8× 28 694
Henry Cook United States 12 412 0.8× 510 1.2× 119 0.5× 153 1.4× 79 1.2× 20 656
Christian Le United States 5 259 0.5× 272 0.6× 208 0.8× 132 1.2× 54 0.8× 8 429
Arrvindh Shriraman Canada 18 864 1.6× 865 2.0× 149 0.6× 200 1.8× 88 1.4× 53 1.0k
Manjunath Kudlur United States 16 686 1.3× 823 1.9× 85 0.3× 129 1.2× 65 1.0× 25 932
Yutao Zhong United States 14 886 1.6× 922 2.1× 307 1.3× 128 1.2× 105 1.6× 29 1.1k
Antonio Carlos Schneider Beck Brazil 15 489 0.9× 623 1.4× 149 0.6× 243 2.2× 74 1.1× 160 785
Sameer G. Kulkarni United States 15 499 0.9× 209 0.5× 264 1.1× 115 1.0× 99 1.5× 45 667
Janghaeng Lee United States 10 282 0.5× 455 1.0× 100 0.4× 246 2.2× 83 1.3× 16 561

Countries citing papers authored by Bernhard Egger

Since Specialization
Citations

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

Fields of papers citing papers by Bernhard Egger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bernhard Egger

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Egger. A scholar is included among the top collaborators of Bernhard Egger 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 Bernhard Egger. Bernhard Egger 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.
Entezari‐Maleki, Reza, et al.. (2024). Deadline-aware task offloading in vehicular networks using deep reinforcement learning. Expert Systems with Applications. 249. 123622–123622. 13 indexed citations
2.
Egger, Bernhard, et al.. (2024). SENNA: Unified Hardware/Software Space Exploration for Parametrizable Neural Network Accelerators. ACM Transactions on Embedded Computing Systems. 24(2). 1–26.
3.
Egger, Bernhard, et al.. (2024). Improving Throughput-oriented LLM Inference with CPU Computations. 233–245. 4 indexed citations
4.
Entezari‐Maleki, Reza, et al.. (2022). Cost-aware Resource Recommendation for DAG-based Big Data Workflows: An Apache Spark Case Study. IEEE Transactions on Services Computing. 1–12. 3 indexed citations
5.
Entezari‐Maleki, Reza, et al.. (2021). Fixed-Point Iteration Approach to Spark Scalable Performance Modeling and Evaluation. IEEE Transactions on Cloud Computing. 11(1). 897–910. 3 indexed citations
6.
Entezari‐Maleki, Reza, et al.. (2021). Modeling and evaluation of dispatching policies in IaaS cloud data centers using SANs. Sustainable Computing Informatics and Systems. 33. 100617–100617. 1 indexed citations
7.
Entezari‐Maleki, Reza, Younghyun Cho, & Bernhard Egger. (2020). Evaluation of memory performance in NUMA architectures using Stochastic Reward Nets. Journal of Parallel and Distributed Computing. 144. 172–188. 4 indexed citations
8.
Egger, Bernhard, et al.. (2019). Performance Modeling of Parallel Loops on Multi-Socket Platforms Using Queueing Systems. IEEE Transactions on Parallel and Distributed Systems. 31(2). 318–331. 9 indexed citations
9.
Egger, Bernhard, et al.. (2018). Architectures and algorithms for on-device user customization of CNNs. Integration. 67. 121–133. 5 indexed citations
10.
Egger, Bernhard, et al.. (2018). Power-aware performance analysis of self-adaptive resource management in IaaS clouds. Future Generation Computer Systems. 86. 134–144. 15 indexed citations
11.
Kim, Euiseok, et al.. (2018). Architectures and algorithms for user customization of CNNs. Asia and South Pacific Design Automation Conference. 540–547. 5 indexed citations
12.
Lee, Hochan, et al.. (2018). Improving Energy Efficiency of Coarse-Grain Reconfigurable Arrays Through Modulo Schedule Compression/Decompression. ACM Transactions on Architecture and Code Optimization. 15(1). 1–26. 5 indexed citations
13.
Egger, Bernhard, et al.. (2018). Auto-Tuning CNNs for Coarse-Grained Reconfigurable Array-Based Accelerators. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 37(11). 2301–2310. 19 indexed citations
14.
Egger, Bernhard, Hochan Lee, Young-Chul Cho, et al.. (2017). A space- and energy-efficient code Compression/Decompression technique for coarse-grained reconfigurable architectures. 197–209. 6 indexed citations
15.
Cho, Younghyun, et al.. (2016). Online Scalability Characterization of Data-Parallel Programs on Many Cores. 191–205. 5 indexed citations
16.
Egger, Bernhard, et al.. (2016). Efficient Checkpointing of Live Virtual Machines. IEEE Transactions on Computers. 65(10). 3041–3054. 8 indexed citations
17.
Kim, Jungwon, et al.. (2014). A Performance Model for GPUs with Caches. IEEE Transactions on Parallel and Distributed Systems. 26(7). 1800–1813. 28 indexed citations
18.
Jo, Changyeon, et al.. (2013). Efficient live migration of virtual machines using shared storage. ACM SIGPLAN Notices. 48(7). 41–50. 22 indexed citations
19.
Egger, Bernhard, et al.. (2009). Recurrence cycle aware modulo scheduling for coarse-grained reconfigurable architectures. 21–30. 37 indexed citations
20.
Egger, Bernhard, et al.. (2006). A dynamic code placement technique for scratchpad memory using postpass optimization. 223–233. 44 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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