Sandra Wienke

594 total citations
13 papers, 52 citations indexed

About

Sandra Wienke is a scholar working on Computer Networks and Communications, Information Systems and Hardware and Architecture. According to data from OpenAlex, Sandra Wienke has authored 13 papers receiving a total of 52 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Networks and Communications, 6 papers in Information Systems and 5 papers in Hardware and Architecture. Recurrent topics in Sandra Wienke's work include Parallel Computing and Optimization Techniques (5 papers), Cloud Computing and Resource Management (4 papers) and Distributed and Parallel Computing Systems (4 papers). Sandra Wienke is often cited by papers focused on Parallel Computing and Optimization Techniques (5 papers), Cloud Computing and Resource Management (4 papers) and Distributed and Parallel Computing Systems (4 papers). Sandra Wienke collaborates with scholars based in Germany, United States and Switzerland. Sandra Wienke's co-authors include Matthias Müller, Dieter an Mey, Martin Schulz, Guido Juckeland, Robert Henschel, Christian Hopmann, Matthias Meinke, Christian Brecher, Christian Terboven and Verónica Melesse Vergara and has published in prestigious journals such as Lecture notes in computer science, The International Journal of High Performance Computing Applications and Computer Science - Research and Development.

In The Last Decade

Sandra Wienke

13 papers receiving 51 citations

Peers

Sandra Wienke

CNC

HA

IS

PP

AI

G. M. Liu China

Fabien Delalondre Switzerland

Yury Oleynik Germany

J Keasler United States

Hainan Ye China

Matthias Jurenz Germany

Vita Bortnikov Israel

Arash Alavi United States

Liu Tang China

Alessia Milani France

G. M. Liu China

Sandra Wienke

19 ×0.7

CNC

6 ×0.3

HA

9 ×0.5

IS

5 ×0.8

PP

3 ×0.6

AI

Citations per year, relative to Sandra Wienke Sandra Wienke (= 1×) peers G. M. Liu

Countries citing papers authored by Sandra Wienke

Since Specialization

Citations

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

Fields of papers citing papers by Sandra Wienke

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sandra Wienke

This figure shows the co-authorship network connecting the top 25 collaborators of Sandra Wienke. A scholar is included among the top collaborators of Sandra Wienke 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 Sandra Wienke. Sandra Wienke 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.

Brunst, Holger, Sunita Chandrasekaran, Florina M. Ciorba, et al.. (2022). First Experiences in Performance Benchmarking with the New SPEChpc 2021 Suites. 675–684. 9 indexed citations

2.

Wienke, Sandra, et al.. (2021). Accelerator Programming Using Directives. Lecture notes in computer science. 3 indexed citations

3.

Terboven, Christian, et al.. (2020). Self-paced Learning in HPC Lab Courses. 11(1). 61–67. 2 indexed citations

4.

Wienke, Sandra, et al.. (2018). PInT: Pattern Instrumentation Tool for Analyzing and Classifying HPC Applications. 17. 71–80. 1 indexed citations

5.

Wienke, Sandra, et al.. (2018). Applicability of the software cost model COCOMO II to HPC projects. International Journal of Computational Science and Engineering. 17(3). 283–283. 7 indexed citations

6.

Wienke, Sandra. (2017). Produktivität und Software-Entwicklungsaufwand im Hochleistungsrechnen. RWTH Publications (RWTH Aachen). 1 indexed citations

7.

Wienke, Sandra, et al.. (2016). Development Effort Estimation in HPC. 107–118. 7 indexed citations

8.

Ding, Fan, Sandra Wienke, & Ruisheng Zhang. (2015). Dynamic MPI parallel task scheduling based on a master-worker pattern in cloud computing. International Journal of Autonomous and Adaptive Communications Systems. 8(4). 424–424. 3 indexed citations

9.

Wienke, Sandra, et al.. (2013). Towards an accurate simulation of the crystallisation process in injection moulded plastic components by hybrid parallelisation. The International Journal of High Performance Computing Applications. 28(3). 356–367. 8 indexed citations

10.

Ding, Fan, Dieter an Mey, Sandra Wienke, Ruisheng Zhang, & Lian Li. (2013). An HPC Application Deployment Model on Azure Cloud for SMEs. 253–259. 1 indexed citations

11.

Wienke, Sandra, Christian Terboven, Dieter an Mey, & Matthias Müller. (2013). Accelerators, quo vadis? Performance vs. productivity. 7484. 471–473. 1 indexed citations

12.

Wienke, Sandra, et al.. (2011). Simulation of bevel gear cutting with GPGPUs—performance and productivity. Computer Science - Research and Development. 26(3-4). 165–174. 7 indexed citations

13.

Pohlmeier, Andreas, Valentin Couvreur, Jan Vanderborght, et al.. (2010). Root Water Uptake and Tracer Transport in a Lupin Root System: Integration of Magnetic Resonance Images and the Numerical Model RSWMS. DIAL (Catholic University of Leuven). 7217. 2 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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