Lawrence Rauchwerger

3.3k total citations
77 papers, 1.7k citations indexed

About

Lawrence Rauchwerger is a scholar working on Hardware and Architecture, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Lawrence Rauchwerger has authored 77 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Hardware and Architecture, 54 papers in Computer Networks and Communications and 13 papers in Artificial Intelligence. Recurrent topics in Lawrence Rauchwerger's work include Parallel Computing and Optimization Techniques (63 papers), Advanced Data Storage Technologies (34 papers) and Distributed and Parallel Computing Systems (23 papers). Lawrence Rauchwerger is often cited by papers focused on Parallel Computing and Optimization Techniques (63 papers), Advanced Data Storage Technologies (34 papers) and Distributed and Parallel Computing Systems (23 papers). Lawrence Rauchwerger collaborates with scholars based in United States, Spain and Denmark. Lawrence Rauchwerger's co-authors include David Padua, Nancy M. Amato, Josep Torrellas, Hao Yu, Silvius Rus, Jay Hoeflinger, María Jesús Garzarán, Milos Prvulović, Gabriel Tanase and Steven J. Plimpton and has published in prestigious journals such as Journal of Computational Physics, IEEE Transactions on Parallel and Distributed Systems and ACM SIGPLAN Notices.

In The Last Decade

Lawrence Rauchwerger

75 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lawrence Rauchwerger United States 25 1.4k 1.2k 284 247 138 77 1.7k
Hans Zima Austria 18 1.7k 1.3× 1.6k 1.3× 264 0.9× 300 1.2× 44 0.3× 66 2.0k
Louis-Noël Pouchet United States 23 1.3k 1.0× 977 0.8× 361 1.3× 382 1.5× 172 1.2× 74 1.8k
Uday Bondhugula India 23 1.9k 1.4× 1.4k 1.2× 467 1.6× 249 1.0× 367 2.7× 58 2.4k
Rudolf Eigenmann United States 27 2.3k 1.7× 2.0k 1.7× 470 1.7× 688 2.8× 132 1.0× 127 2.8k
Christophe Dubach United Kingdom 17 1.2k 0.9× 897 0.8× 242 0.9× 302 1.2× 151 1.1× 70 1.4k
Ras Bodik United States 4 931 0.7× 875 0.7× 154 0.5× 208 0.8× 113 0.8× 6 1.3k
Joseph A. Fisher United States 20 1.9k 1.4× 1.2k 1.0× 247 0.9× 135 0.5× 74 0.5× 41 2.1k
María Jesús Garzarán United States 18 932 0.7× 800 0.7× 235 0.8× 220 0.9× 109 0.8× 58 1.1k
Anthony Danalis United States 13 983 0.7× 923 0.8× 107 0.4× 350 1.4× 70 0.5× 35 1.2k
Charles Koelbel United States 19 1.1k 0.8× 1.2k 1.0× 204 0.7× 352 1.4× 32 0.2× 42 1.5k

Countries citing papers authored by Lawrence Rauchwerger

Since Specialization
Citations

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

Fields of papers citing papers by Lawrence Rauchwerger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lawrence Rauchwerger

This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence Rauchwerger. A scholar is included among the top collaborators of Lawrence Rauchwerger 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 Lawrence Rauchwerger. Lawrence Rauchwerger 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.
Adams, Michael P., Marvin L. Adams, Marvin L. Adams, et al.. (2020). Provably optimal parallel transport sweeps on semi-structured grids. Journal of Computational Physics. 407. 109234–109234. 19 indexed citations
2.
Oancea, Cosmin E. & Lawrence Rauchwerger. (2015). Scalable conditional induction variables (CIV) analysis. 213–224. 6 indexed citations
3.
Amato, Nancy M., et al.. (2015). An Algorithmic Approach to Communication Reduction in Parallel Graph Algorithms. 201–212. 2 indexed citations
4.
Amato, Nancy M., et al.. (2014). SCCMulti. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 393–394. 2 indexed citations
5.
Jacobs, Sam Adé, et al.. (2014). Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 573–582. 2 indexed citations
6.
Yu, Hao & Lawrence Rauchwerger. (2014). Adaptive reduction parallelization techniques. 311–322. 9 indexed citations
7.
Adams, Michael P., et al.. (2012). Efficient Massively Parallel Transport Sweeps. Transactions of the American Nuclear Society. 107(1). 477–481. 12 indexed citations
8.
Rauchwerger, Lawrence, et al.. (2008). Improving locality with dynamic memory allocation. 1 indexed citations
9.
Rus, Silvius, Marinus Pennings, & Lawrence Rauchwerger. (2007). Sensitivity analysis for automatic parallelization on multi-cores. 263–273. 31 indexed citations
10.
Rus, Silvius & Lawrence Rauchwerger. (2006). Compiler technology for migrating sequential code to multi-threaded Architectures. 2 indexed citations
11.
Yu, Hao & Lawrence Rauchwerger. (2006). An Adaptive Algorithm Selection Framework for Reduction Parallelization. IEEE Transactions on Parallel and Distributed Systems. 17(10). 1084–1096. 17 indexed citations
12.
Rus, Silvius & Lawrence Rauchwerger. (2005). Hybrid dependence analysis for automatic parallelization. 2 indexed citations
13.
Rus, Silvius, Dongmin Zhang, & Lawrence Rauchwerger. (2004). The Value Evolution Graph and its Use in Memory Reference Analysis. International Conference on Parallel Architectures and Compilation Techniques. 243–254. 8 indexed citations
14.
Yu, Hao, Dongmin Zhang, & Lawrence Rauchwerger. (2004). An Adaptive Algorithm Selection Framework. International Conference on Parallel Architectures and Compilation Techniques. 278–289. 14 indexed citations
15.
Rauchwerger, Lawrence. (2004). Languages and compilers for parallel computing : 16th International Workshop, LCPC 2003, College Station, TX, USA, October 2-4, 2003 : revised papers. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 3 indexed citations
16.
Rus, Silvius, Dongmin Zhang, & Lawrence Rauchwerger. (2004). The value evolution graph and its use in memory reference analysis. 243–254. 2 indexed citations
17.
Garzarán, María Jesús, et al.. (2001). Architectural Support for Parallel Reductions in Scalable Shared-Memory Multiprocessors. International Conference on Parallel Architectures and Compilation Techniques. 243–254. 16 indexed citations
18.
Hendrickson, Bruce, et al.. (2001). Identifying Strongly Connected Components in Parallel.. PPSC. 2 indexed citations
19.
Rauchwerger, Lawrence, et al.. (1998). A Unified Approach to Speculative Parallelization of Loops in DSM Multiprocessors. 2 indexed citations
20.
Eigenmann, Rudolf, et al.. (1994). Polaris: The Next Generation in Parallelizing Compilers. 35 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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