Richard Vuduc

6.2k citations

132 papers · 3.7k indexed · 1 hit paper · h-index 32

Impact in

Computational Mathematics top 0.2%
- Tensor decomposition and applications
Hardware and Architecture top 0.1%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques

Papers in

Computational Mathematics 12
- Tensor decomposition and applications 12
Hardware and Architecture 80
- Parallel Computing and Optimization Techniques 80
- Embedded Systems Design Techniques 9

Co-authors: James Demmel Katherine Yelick Jee Choi Amik Singh Eun-Jin Im Aparna Chandramowlishwaran Hyesoon Kim Mary Jean Harrold
Journals: ACM SIGPLAN Notices (3 papers)The International Journal of High Performance Computing Applications (2 papers)IEEE Transactions on Parallel and Distributed Systems (2 papers)Journal of Manufacturing Science and Engineering (2 papers)Journal of Parallel and Distributed Computing (2 papers)
Partner nations: United States China Norway

In The Last Decade

Richard Vuduc

123 papers receiving 3.5k citations

Hit Papers

align trajectories log scale

Model-driven autotuning of sparse matrix-vector multiply on GPUs 2010 · 279 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2010 Model-driven autotuning of sparse matrix-vector multiply on GPUs

Peers

Countries citing papers authored by Richard Vuduc

Since Specialization

Citations

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

Fields of papers citing papers by Richard Vuduc

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Richard Vuduc, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Richard Vuduc Line = papers co-authored together Richard Vuduc links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	FAIR Sharing of Data in Autotuning Research (Vision Paper) Leiden Repository (Leiden University) ·Jana Hozzová, Jacob O. Tørring, Ben van Werkhoven, David Střelák, Richard Vuduc	2024	0
2	A Workflow for the Synthesis of Irregular Memory Access Microbenchmarks Kevin J. Sheridan, Jered Dominguez-Trujillo, Galen Shipman, Patrick Lavin, Christopher Scott, Agustin Vaca Valverde, Richard Vuduc, Jeffrey Young	2024	0
3	Calculon: a methodology and tool for high-level co-design of systems and large language models Mikhail Isaev, Nic McDonald, Larry Dennison, Richard Vuduc	2023	14
4	Distributed-Memory Parallel JointNMF OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) ·Srinivas Eswar, Benjamin Cobb, Koby Hayashi, Ramakrishnan Kannan, Grey Ballard, Richard Vuduc, Haesun Park	2023	1
5	Multifidelity Memory System Simulation in SST Patrick Lavin, Jeffrey Young, Richard Vuduc	2023	1
6	Jack, The Autotuner Computing in Science & Engineering ·Richard Vuduc	2022	1
7	ParaGraph: An application-simulator interface and toolkit for hardware-software co-design Mikhail Isaev, Nic McDonald, Jeffrey Young, Richard Vuduc	2022	1
8	Load-Balanced Sparse MTTKRP on GPUs Israt Nisa, Jiajia Li, Aravind Sukumaran-Rajam, Richard Vuduc, P. Sadayappan	2019	31
9	Spatter: A Benchmark Suite for Evaluating Sparse Access Patterns arXiv (Cornell University) ·Patrick Lavin, Jason Riedy, Richard Vuduc, Jeffrey S. Young	2018	3
10	A Sparse Direct Solver for Distributed Memory Xeon Phi-Accelerated Systems Piyush Sao, Xing Liu, Richard Vuduc, Xiaoye Li	2015	12
11	Optimizing the computation of n-point correlations on large-scale astronomical data IEEE International Conference on High Performance Computing, Data, and Analytics ·William B. March, Kenneth Czechowski, Marat Dukhan, Thomas Benson, Dongryeol Lee, Andrew J. Connolly, Richard Vuduc, Edmond Chow, Alexander Gray	2012	6
12	Balance principles for algorithm-architecture co-design Kent Czechowski, Casey Battaglino, Chris McClanahan, Aparna Chandramowlishwaran, Richard Vuduc	2011	18
13	The Backstroke framework for source level reverse computation applied to parallel discrete event simulation Winter Simulation Conference ·George Vulov, Cong Hou, Richard Vuduc, Richard Fujimoto, Daniel J. Quinlan, David Jefferson	2011	10
14	Characterizing Application Runtime Behavior from System Logs and Metrics Talanta ·Raghul Gunasekaran, David Dillow, Galen Shipman, Richard Vuduc, Edmond Chow	2011	1
15	On the limits of GPU acceleration Richard Vuduc, Aparna Chandramowlishwaran, Jee Choi, Murat Efe Guney, Aashay Shringarpure	2010	80
16	Model-driven autotuning of sparse matrix-vector multiply on GPUs Jee Choi, Amik Singh, Richard Vuduc Hit paper breakdown →	2010	279
17	Performance models for evaluation and automatic tuning of symmetric sparse matrix-vector multiply Proceedings of the International Conference on Parallel Processing ·B.C. Lee, Richard Vuduc, James Demmel, Katherine Yelick	2004	39
18	Performance Optimizations and Bounds for Sparse Matrix-Vector Multiply Conference on High Performance Computing (Supercomputing) ·Richard Vuduc, James Demmel, Katherine Yelick, Shoaib Kamil, Rajesh Nishtala, Benjamin Lee	2002	82
19	SWAMI: a framework for collaborative filtering algorithm development and evaluation. International ACM SIGIR Conference on Research and Development in Information Retrieval ·Danyel Fisher, Kris Hildrum, Jason Hong, Mark Newman, Megan Thomas, Richard Vuduc	2000	26
20	Code Generators for Automatic Tuning of Numerical Kernels: Experiences with FFTW Richard Vuduc, James Demmel	2000	7

About Richard Vuduc

Richard Vuduc is a scholar working on Computational Mathematics, Hardware and Architecture, Computer Networks and Communications, Computer Graphics and Computer-Aided Design and Software, having authored 132 papers that have together received 3.7k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (80 papers), Advanced Data Storage Technologies (31 papers), Interconnection Networks and Systems (23 papers), Distributed and Parallel Computing Systems (13 papers), Tensor decomposition and applications (12 papers), Electromagnetic Scattering and Analysis (9 papers), Embedded Systems Design Techniques (9 papers) and Algorithms and Data Compression (9 papers). The work is most often cited by research in Computational Mathematics (320 citations), Hardware and Architecture (2.5k citations), Computer Networks and Communications (2.0k citations), Software (157 citations) and Computational Theory and Mathematics (514 citations). Richard Vuduc has collaborated with scholars based in United States, China and Norway. Frequent co-authors include James Demmel, Katherine Yelick, Jee Choi, Amik Singh, Eun-Jin Im, Aparna Chandramowlishwaran, Hyesoon Kim, Mary Jean Harrold, Sangmin Park and Jiajia Li. Their work appears in journals such as ACM SIGPLAN Notices, The International Journal of High Performance Computing Applications, IEEE Transactions on Parallel and Distributed Systems, Journal of Manufacturing Science and Engineering and Journal of Parallel and Distributed Computing.

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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