Tom Henretty

405 total citations
15 papers, 187 citations indexed

About

Tom Henretty is a scholar working on Hardware and Architecture, Computational Mathematics and Computer Networks and Communications. According to data from OpenAlex, Tom Henretty has authored 15 papers receiving a total of 187 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hardware and Architecture, 7 papers in Computational Mathematics and 6 papers in Computer Networks and Communications. Recurrent topics in Tom Henretty's work include Parallel Computing and Optimization Techniques (9 papers), Tensor decomposition and applications (7 papers) and Algorithms and Data Compression (4 papers). Tom Henretty is often cited by papers focused on Parallel Computing and Optimization Techniques (9 papers), Tensor decomposition and applications (7 papers) and Algorithms and Data Compression (4 papers). Tom Henretty collaborates with scholars based in United States. Tom Henretty's co-authors include P. Sadayappan, J. Ramanujam, Louis-Noël Pouchet, Richard Veras, Franz Franchetti, Muthu Manikandan Baskaran, Richard Lethin, Kevin Stock, Justin Holewinski and Atanas Rountev and has published in prestigious journals such as Civil War Book Review and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

In The Last Decade

Tom Henretty

15 papers receiving 180 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom Henretty United States 8 120 88 64 60 19 15 187
Kevin Stock United States 8 163 1.4× 110 1.3× 41 0.6× 22 0.4× 16 0.8× 9 197
Tyler Smith United States 6 189 1.6× 133 1.5× 74 1.2× 21 0.3× 48 2.5× 13 260
Philippe Tillet United States 5 84 0.7× 53 0.6× 55 0.9× 17 0.3× 46 2.4× 5 190
Kadir Akbudak Saudi Arabia 9 102 0.8× 94 1.1× 36 0.6× 7 0.1× 34 1.8× 15 177
Benoît Meister United States 10 269 2.2× 191 2.2× 76 1.2× 84 1.4× 13 0.7× 29 344
Protonu Basu United States 8 170 1.4× 141 1.6× 34 0.5× 7 0.1× 13 0.7× 13 199
Kartik Hegde United States 3 147 1.2× 89 1.0× 77 1.2× 32 0.5× 80 4.2× 5 234
Joël Falcou France 8 107 0.9× 84 1.0× 35 0.5× 11 0.2× 14 0.7× 22 165
Martin Kong United States 9 196 1.6× 133 1.5× 59 0.9× 8 0.1× 27 1.4× 23 240
William S. Moses United States 8 139 1.2× 89 1.0× 43 0.7× 5 0.1× 23 1.2× 17 192

Countries citing papers authored by Tom Henretty

Since Specialization
Citations

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

Fields of papers citing papers by Tom Henretty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Henretty

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

All Works

15 of 15 papers shown
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3.
Henretty, Tom, et al.. (2018). All-at-once Decomposition of Coupled Billion-scale Tensors in Apache Spark. 1. 1–8. 4 indexed citations
4.
Henretty, Tom, et al.. (2017). A quantitative and qualitative analysis of tensor decompositions on spatiotemporal data. 1–7. 13 indexed citations
5.
Baskaran, Muthu Manikandan, et al.. (2017). Memory-efficient parallel tensor decompositions. 1–7. 19 indexed citations
6.
Baskaran, Muthu Manikandan, et al.. (2016). Accelerated low-rank updates to tensor decompositions. 37. 1–7. 6 indexed citations
7.
Baskaran, Muthu Manikandan, et al.. (2016). Polyhedral compilation for energy efficiency. 1–7. 1 indexed citations
8.
Baskaran, Muthu Manikandan, et al.. (2016). Cyber Security through Multidimensional Data Decompositions. 59–67. 11 indexed citations
9.
Henretty, Tom, et al.. (2015). Embedded second-order cone programming with radar applications. 51. 1–7. 1 indexed citations
10.
Kong, Martin, Tom Henretty, Justin Holewinski, et al.. (2015). SDSLc. Civil War Book Review. 1–10. 16 indexed citations
11.
Baskaran, Muthu Manikandan, Tom Henretty, Taku Izubuchi, et al.. (2015). Polyhedral user mapping and assistant visualizer tool for the r-stream auto-parallelizing compiler. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 180–184. 2 indexed citations
12.
Henretty, Tom, et al.. (2014). Extreme SAT-based Constraint solving with R-Solve. 1. 1–6. 2 indexed citations
13.
Henretty, Tom, Justin Holewinski, Richard Veras, et al.. (2013). A Domain-Specific Language and Compiler for Stencil Computations on Short-Vector SIMD and GPU Architectures. 1 indexed citations
14.
Henretty, Tom, Richard Veras, Franz Franchetti, et al.. (2013). A stencil compiler for short-vector SIMD architectures. Civil War Book Review. 13–24. 89 indexed citations
15.
Stock, Kevin, et al.. (2011). Model-Driven SIMD Code Generation for a Multi-resolution Tensor Kernel. 1058–1067. 7 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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