Pierre‐André Wacrenier

1.8k total citations · 1 hit paper
9 papers, 767 citations indexed

About

Pierre‐André Wacrenier is a scholar working on Computer Networks and Communications, Hardware and Architecture and Information Systems. According to data from OpenAlex, Pierre‐André Wacrenier has authored 9 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Networks and Communications, 7 papers in Hardware and Architecture and 4 papers in Information Systems. Recurrent topics in Pierre‐André Wacrenier's work include Parallel Computing and Optimization Techniques (7 papers), Distributed and Parallel Computing Systems (7 papers) and Cloud Computing and Resource Management (4 papers). Pierre‐André Wacrenier is often cited by papers focused on Parallel Computing and Optimization Techniques (7 papers), Distributed and Parallel Computing Systems (7 papers) and Cloud Computing and Resource Management (4 papers). Pierre‐André Wacrenier collaborates with scholars based in France, Germany and United Kingdom. Pierre‐André Wacrenier's co-authors include Raymond Namyst, Samuel Thibault, Cédric Augonnet, François Broquedis, Brice Goglin, Nathalie Furmento, Abdou Guermouche, Terry Cojean, Thomas L. Morin and H. Martin Bücker and has published in prestigious journals such as Journal of Parallel and Distributed Computing, Parallel Computing and The International Journal of High Performance Computing Applications.

In The Last Decade

Pierre‐André Wacrenier

7 papers receiving 728 citations

Hit Papers

StarPU: a unified platform for task scheduling on heterog... 2010 2026 2015 2020 2010 200 400 600

Peers

Pierre‐André Wacrenier
James Dinan United States
Jeremy S. Meredith United States
Sanjeev Krishnan United States
Tom Scogland United States
Asim YarKhan United States
Sean Treichler United States
Anthony Danalis United States
Ian Karlin United States
Pierre‐André Wacrenier
Citations per year, relative to Pierre‐André Wacrenier Pierre‐André Wacrenier (= 1×) peers Cédric Augonnet

Countries citing papers authored by Pierre‐André Wacrenier

Since Specialization
Citations

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

Fields of papers citing papers by Pierre‐André Wacrenier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pierre‐André Wacrenier. 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 Pierre‐André Wacrenier. The network helps show where Pierre‐André Wacrenier may publish in the future.

Co-authorship network of co-authors of Pierre‐André Wacrenier

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

All Works

9 of 9 papers shown
1.
Furmento, Nathalie, et al.. (2025). Optimizing parallel heterogeneous system efficiency: Dynamic task graph adaptation with recursive tasks. Journal of Parallel and Distributed Computing. 205. 105157–105157.
2.
Faverge, Mathieu, Nathalie Furmento, Abdou Guermouche, et al.. (2023). Programming heterogeneous architectures using hierarchical tasks. Concurrency and Computation Practice and Experience. 35(25). 3 indexed citations
3.
Bücker, H. Martin, Henri Casanova, Rafael Ferreira da Silva, et al.. (2022). Peachy Parallel Assignments (EduPar 2022). HAL (Le Centre pour la Communication Scientifique Directe). 361–368. 1 indexed citations
4.
Namyst, Raymond, et al.. (2021). EasyPAP: A framework for learning parallel programming. Journal of Parallel and Distributed Computing. 158. 94–114. 3 indexed citations
5.
Cojean, Terry, et al.. (2018). Resource aggregation for task-based Cholesky Factorization on top of modern architectures. Parallel Computing. 83. 73–92. 6 indexed citations
6.
Guermouche, Abdou, et al.. (2014). Composing multiple StarPU applications over heterogeneous machines: A supervised approach. The International Journal of High Performance Computing Applications. 28(3). 285–300. 3 indexed citations
7.
Augonnet, Cédric, Samuel Thibault, Raymond Namyst, & Pierre‐André Wacrenier. (2010). StarPU: a unified platform for task scheduling on heterogeneous multicore architectures. Concurrency and Computation Practice and Experience. 23(2). 187–198. 710 indexed citations breakdown →
8.
Broquedis, François, Nathalie Furmento, Brice Goglin, Pierre‐André Wacrenier, & Raymond Namyst. (2010). ForestGOMP: An Efficient OpenMP Environment for NUMA Architectures. International Journal of Parallel Programming. 38(5-6). 418–439. 40 indexed citations
9.
Métivier, Yves, Pierre‐André Wacrenier, Mohamed Mosbah, & Stefan Grüner. (2001). A Distributed Algorithm for Computing a Spanning Tree in Anonymous T-Prime Graphs. ePrints Soton (University of Southampton). 141–158. 1 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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