Daniel M. Lavery

1.1k total citations · 1 hit paper
12 papers, 780 citations indexed

About

Daniel M. Lavery is a scholar working on Hardware and Architecture, Computer Networks and Communications and Cognitive Neuroscience. According to data from OpenAlex, Daniel M. Lavery has authored 12 papers receiving a total of 780 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Hardware and Architecture, 6 papers in Computer Networks and Communications and 1 paper in Cognitive Neuroscience. Recurrent topics in Daniel M. Lavery's work include Parallel Computing and Optimization Techniques (10 papers), Distributed and Parallel Computing Systems (6 papers) and Embedded Systems Design Techniques (5 papers). Daniel M. Lavery is often cited by papers focused on Parallel Computing and Optimization Techniques (10 papers), Distributed and Parallel Computing Systems (6 papers) and Embedded Systems Design Techniques (5 papers). Daniel M. Lavery collaborates with scholars based in United States and United Kingdom. Daniel M. Lavery's co-authors include Wen‐mei Hwu, Scott Mahlke, Grant Haab, Richard E. Hank, Nancy J. Warter, Wen mei Hwu, Pohua P. Chang, John G. Holm, Roger A. Bringmann and Tokuzo Kiyohara and has published in prestigious journals such as Proceedings of the IEEE, Computer and IEEE Transactions on Computers.

In The Last Decade

Daniel M. Lavery

12 papers receiving 695 citations

Hit Papers

The superblock: An effective technique for VLIW and super... 1993 2026 2004 2015 1993 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel M. Lavery United States 10 639 399 187 147 84 12 780
Giovanni Mariani Switzerland 14 378 0.6× 284 0.7× 193 1.0× 146 1.0× 35 0.4× 38 629
Jon Turner United States 12 863 1.4× 1.0k 2.6× 143 0.8× 353 2.4× 17 0.2× 16 1.2k
Gurudatta M. Parulkar United States 16 459 0.7× 899 2.3× 152 0.8× 198 1.3× 10 0.1× 54 1.0k
Filip Pizlo United States 15 589 0.9× 340 0.9× 22 0.1× 250 1.7× 103 1.2× 29 734
Allan Knies United States 9 387 0.6× 611 1.5× 237 1.3× 102 0.7× 18 0.2× 15 802
Wajahat Qadeer United States 9 435 0.7× 315 0.8× 307 1.6× 79 0.5× 7 0.1× 12 678
D.E. Schimmel United States 12 395 0.6× 378 0.9× 138 0.7× 195 1.3× 15 0.2× 30 525
Yiannakis Sazeides Cyprus 14 973 1.5× 794 2.0× 465 2.5× 114 0.8× 31 0.4× 54 1.2k
Mark Hayden United States 11 178 0.3× 940 2.4× 55 0.3× 208 1.4× 15 0.2× 23 1.0k
Mohammad Ali Ghodrat United States 10 333 0.5× 260 0.7× 131 0.7× 41 0.3× 14 0.2× 22 425

Countries citing papers authored by Daniel M. Lavery

Since Specialization
Citations

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

Fields of papers citing papers by Daniel M. Lavery

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Lavery. 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 Daniel M. Lavery. The network helps show where Daniel M. Lavery may publish in the future.

Co-authorship network of co-authors of Daniel M. Lavery

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

All Works

12 of 12 papers shown
1.
Lin, Chit-Kwan, Andreas Wild, Gautham N. Chinya, et al.. (2018). Programming Spiking Neural Networks on Intel’s Loihi. Computer. 51(3). 52–61. 87 indexed citations
2.
Kejariwal, Arun, et al.. (2007). Comparative characterization of SPEC CPU2000 and CPU2006 on Itanium® architecture. 361–362. 1 indexed citations
3.
Warter, Nancy J., Daniel M. Lavery, & Wen‐mei Hwu. (2002). The benefit of predicated execution for software pipelining. i. 497–506. 16 indexed citations
4.
Lavery, Daniel M. & Wen‐mei Hwu. (2002). Modulo scheduling of loops in control-intensive non-numeric programs. 126–137. 9 indexed citations
5.
Lavery, Daniel M.. (1997). Modulo scheduling for control-intensive general-purpose programs. 6 indexed citations
6.
Lavery, Daniel M. & Wen‐mei Hwu. (1996). Modulo scheduling of loops in control-intensive non-numeric programs. International Symposium on Microarchitecture. 126–137. 29 indexed citations
7.
Lavery, Daniel M. & Wen‐mei Hwu. (1995). Unrolling-based optimizations for modulo scheduling. International Symposium on Microarchitecture. 327–337. 26 indexed citations
8.
Hwu, Wen‐mei, Richard E. Hank, David Gallagher, et al.. (1995). Compiler technology for future microprocessors. Proceedings of the IEEE. 83(12). 1625–1640. 46 indexed citations
9.
Lavery, Daniel M. & Wen‐mei Hwu. (1995). Unrolling-based optimizations for modulo scheduling. 327–337. 20 indexed citations
10.
Chang, Pohua P., et al.. (1995). The importance of prepass code scheduling for superscalar and superpipelined processors. IEEE Transactions on Computers. 44(3). 353–370. 26 indexed citations
11.
Hwu, Wen mei, Scott Mahlke, William Y. Chen, et al.. (1993). The superblock: An effective technique for VLIW and superscalar compilation. The Journal of Supercomputing. 7(1-2). 229–248. 490 indexed citations breakdown →
12.
Veidenbaum, Alexander V., Edward S. Davidson, M. Haney, et al.. (1991). The Organization of the Cedar System.. Proceedings of the International Conference on Parallel Processing. 49–56. 24 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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