Richard W. Vuduc

Richard W. Vuduc, Jeffrey S. Vetter, Dhairya Malhotra, 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.

Direct N-body Kernels for Multicore Platforms

Richard W. Vuduc, Nitin Arora, Aashay Shringarpure, 2009, 2009 International Conference on Parallel Processing.

Faster parallel collision detection at high resolution for CNC milling applications

Richard W. Vuduc, Dmytro Konobrytskyi, Thomas R. Kurfess, 2019, ICPP.

Communication-Optimal Parallel N-body Solvers

Richard W. Vuduc, Aparna Chandramowlishwaran, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

Memory Hierarchy Optimizations and Performance ounds for Sparse A

James Demmel, Richard W. Vuduc, Katherine A. Yelick, 2003, International Conference on Computational Science.

On the communication complexity of 3D FFTs and its implications for Exascale

Richard W. Vuduc, Kenneth Czechowski, Chris McClanahan, 2012, ICS '12.

A Roofline Model of Energy

Richard W. Vuduc, Robert J. Fowler, Daniel Bedard, 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.

Analyzing the Energy Efficiency of the Fast Multipole Method Using a DVFS-Aware Energy Model

Richard W. Vuduc, JeeWhan Choi, R. Vuduc, 2016, 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

Polyadic Regression and its Application to Chemogenomics

Ping Zhang, Fei Wang, Jimeng Sun, 2017, SDM.

Performance Optimizations and Bounds for Sparse Matrix-Vector Multiply

James Demmel, Richard W. Vuduc, Katherine A. Yelick, 2002, ACM/IEEE SC 2002 Conference (SC'02).

Synthesizing Loops for Program Inversion

Richard W. Vuduc, David R. Jefferson, Richard M. Fujimoto, 2012, RC.

Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU)

Richard W. Vuduc, Wen-mei W. Hwu, Hyesoon Kim, 2012, Synthesis Lectures on Computer Architecture.

Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems

James Demmel, Richard W. Vuduc, Cho-Jui Hsieh, 2018, ICS.

A Unified Approach for Localizing Non-deadlock Concurrency Bugs

Richard W. Vuduc, Mary Jean Harrold, Sangmin Park, 2012, 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation.

An Energy-Efficient Single-Source Shortest Path Algorithm

Richard W. Vuduc, Jeffrey S. Young, Sara Karamati, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Balance Principles for Algorithm-Architecture Co-Design

Richard W. Vuduc, Aparna Chandramowlishwaran, Kenneth Czechowski, 2011, HotPar.

Modeling the Power Variability of Core Speed Scaling on Homogeneous Multicore Systems

David A. Bader, Richard W. Vuduc, Rong Ge, 2017, Sci. Program..

Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure

Hyun Jin Moon, Richard W. Vuduc, R. Vuduc, 2005, HPCC.

Efficient Communications in Training Large Scale Neural Networks

Zenglin Xu, George Bosilca, Richard W. Vuduc, 2017, ACM Multimedia.

CA-SVM: Communication-Avoiding Support Vector Machines on Distributed Systems

Le Song, James Demmel, Richard W. Vuduc, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium.

An Initial Characterization of the Emu Chick

Richard W. Vuduc, E. Jason Riedy, Jiajia Li, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW).

Optimizing and tuning the fast multipole method for state-of-the-art multicore architectures

Samuel Williams, Leonid Oliker, Richard W. Vuduc, 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS).

Performance evaluation of concurrent collections on high-performance multicore computing systems

Richard W. Vuduc, Aparna Chandramowlishwaran, Kathleen Knobe, 2010, 2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS).

Griffin: grouping suspicious memory-access patterns to improve understanding of concurrency bugs

Richard W. Vuduc, Mary Jean Harrold, Sangmin Park, 2013, ISSTA.

What GPU Computing Means for High-End Systems

Richard W. Vuduc, Kenneth Czechowski, 2011, IEEE Micro.

Falcon: fault localization in concurrent programs

Richard W. Vuduc, Mary Jean Harrold, Sangmin Park, 2010, 2010 ACM/IEEE 32nd International Conference on Software Engineering.

When Prefetching Works, When It Doesn’t, and Why

Richard W. Vuduc, Hyesoon Kim, Jaekyu Lee, 2012, TACO.

Programming Strategies for Irregular Algorithms on the Emu Chick

Richard W. Vuduc, Bora Uçar, Ümit V. Çatalyürek, 2018, ACM Trans. Parallel Comput..

A Sparse Direct Solver for Distributed Memory Xeon Phi-Accelerated Systems

Richard W. Vuduc, Xiaoye S. Li, Piyush Sao, 2015, 2015 IEEE International Parallel and Distributed Processing Symposium.

Performance models for evaluation and automatic tuning of symmetric sparse matrix-vector multiply

James Demmel, Richard W. Vuduc, Katherine A. Yelick, 2004, International Conference on Parallel Processing, 2004. ICPP 2004..

Applying the concurrent collections programming model to asynchronous parallel dense linear algebra

Richard W. Vuduc, Aparna Chandramowlishwaran, Kathleen Knobe, 2010, PPoPP '10.

Unconventional wisdom in multicore computing

Richard W. Vuduc, 2010, IPDPS.

A Microbenchmark Characterization of the Emu Chick pdf

Richard W. Vuduc, E. Jason Riedy, Jiajia Li, 2018, Parallel Comput..

The Backstroke framework for source level reverse computation applied to parallel discrete event simulation

Richard W. Vuduc, David R. Jefferson, Richard M. Fujimoto, 2011, Proceedings of the 2011 Winter Simulation Conference (WSC).

A Self-Correcting Connected Components Algorithm

Chirag Jain, Richard W. Vuduc, Piyush Sao, 2016, FTXS@HPDC.

Algorithmic Time, Energy, and Power on Candidate HPC Compute Building Blocks

Richard W. Vuduc, Xing Liu, Jee W. Choi, 2014, 2014 IEEE 28th International Parallel and Distributed Processing Symposium.

Branch-Avoiding Graph Algorithms

Richard W. Vuduc, Oded Green, Marat Dukhan, 2014, SPAA.

Sparsity: Optimization Framework for Sparse Matrix Kernels

Richard W. Vuduc, Katherine A. Yelick, Eun-Jin Im, 2004, Int. J. High Perform. Comput. Appl..

Optimizing the computation of n-point correlations on large-scale astronomical data

William B. March, Alexander G. Gray, Richard W. Vuduc, 2012, 2012 International Conference for High Performance Computing, Networking, Storage and Analysis.

Many-Thread Aware Prefetching Mechanisms for GPGPU Applications

Richard W. Vuduc, Hyesoon Kim, Jaekyu Lee, 2010, 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture.

Spatter: A Benchmark Suite for Evaluating Sparse Access Patterns pdf

Richard W. Vuduc, E. Jason Riedy, Jeffrey S. Young, 2018, ArXiv.

Diagnosis, Tuning, and Redesign for Multicore Performance: A Case Study of the Fast Multipole Method

Richard W. Vuduc, Aparna Chandramowlishwaran, Kamesh Madduri, 2010, 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis.

HiCOO: Hierarchical Storage of Sparse Tensors

Jimeng Sun, Richard W. Vuduc, Jiajia Li, 2018, SC18: International Conference for High Performance Computing, Networking, Storage and Analysis.

A Simple Methodology for Computing Families of Algorithms pdf

Robert A. van de Geijn, Richard W. Vuduc, Devangi N. Parikh, 2018, ArXiv.

Communicating Software Architecture using a Unified Single-View Visualization

Richard W. Vuduc, Daniel J. Quinlan, Andreas Sæbjørnsen, 2007, 12th IEEE International Conference on Engineering Complex Computer Systems (ICECCS 2007).

A New Method for Program Inversion

Richard W. Vuduc, David R. Jefferson, Richard M. Fujimoto, 2012, CC.

Optimization of sparse matrix-vector multiplication on emerging multicore platforms

Samuel Williams, Leonid Oliker, John Shalf, 2007, Proceedings of the 2007 ACM/IEEE Conference on Supercomputing (SC '07).

A Distributed Kernel Summation Framework for General-Dimension Machine Learning

Alexander G. Gray, Richard W. Vuduc, Dongryeol Lee, 2012, SDM.

Modeling and Analysis for Performance and Power

Richard W. Vuduc, JeeWhan Choi, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

Wanted: Floating-Point Add Round-off Error instruction pdf

Richard W. Vuduc, E. Jason Riedy, Marat Dukhan, 2016, ArXiv.

A CPU: GPU Hybrid Implementation and Model-Driven Scheduling of the Fast Multipole Method

Richard W. Vuduc, Aparna Chandramowlishwaran, Kamesh Madduri, 2014, GPGPU@ASPLOS.

A Unified Approach for Localizing Non-deadlock Concurrency Bugs

Richard W. Vuduc, Mary Jean Harrold, Sangmin Park, 2012, ICST.

An input-adaptive and in-place approach to dense tensor-times-matrix multiply

Jimeng Sun, Richard W. Vuduc, Jiajia Li, 2015, SC15: International Conference for High Performance Computing, Networking, Storage and Analysis.

Toward interactive statistical modeling

Alexander G. Gray, Richard W. Vuduc, Ashish Agarwal, 2010, ICCS.

Algorithms and software with turnable parallelism

Richard W. Vuduc, 2010 .

A Distributed CPU-GPU Sparse Direct Solver

Richard W. Vuduc, Xiaoye S. Li, Piyush Sao, 2014, Euro-Par.

Optimizing Sparse Tensor Times Matrix on Multi-core and Many-Core Architectures

Richard W. Vuduc, Chenggang Clarence Yan, Jiajia Li, 2016, 2016 6th Workshop on Irregular Applications: Architecture and Algorithms (IA3).

A distributed kernel summation framework for general‐dimension machine learning

Alexander G. Gray, Richard W. Vuduc, Dongryeol Lee, 2014, Stat. Anal. Data Min..

Introduction for Special Issue on Autotuning

Leonid Oliker, Richard W. Vuduc, 2013, Int. J. High Perform. Comput. Appl..

A type theory for probability density functions

Alexander G. Gray, Richard W. Vuduc, Ashish Agarwal, 2012, POPL '12.

POET: Parameterized Optimizations for Empirical Tuning

Richard W. Vuduc, Qing Yi, Haihang You, 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

Hybrid Dynamic Trees for Extreme-Resolution 3D Sparse Data Modeling

Richard W. Vuduc, Thomas R. Kurfess, Thomas M. Tucker, 2016, 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Sparse Hierarchical Tucker Factorization and Its Application to Healthcare

Jimeng Sun, Richard W. Vuduc, Robert Chen, 2015, 2015 IEEE International Conference on Data Mining.

Improving the energy efficiency of Big Cores

Richard W. Vuduc, Pradeep Dubey, Victor W. Lee, 2014, 2014 ACM/IEEE 41st International Symposium on Computer Architecture (ISCA).

Techniques for specifying bug patterns

Richard W. Vuduc, Daniel J. Quinlan, Ghassan Misherghi, 2007, PADTAD '07.

An Extensible Open-Source Compiler Infrastructure for Testing

Richard W. Vuduc, Daniel J. Quinlan, Shmuel Ur, 2005, Haifa Verification Conference.

Methods for High-Throughput Computation of Elementary Functions

Richard W. Vuduc, Marat Dukhan, R. Vuduc, 2013, PPAM.

A Theoretical Framework for Algorithm-Architecture Co-design

Richard W. Vuduc, Kenneth Czechowski, R. Vuduc, 2013, 2013 IEEE 27th International Symposium on Parallel and Distributed Processing.

The Sixth International Workshop on Automatic Performance Tuning (iWAPT2011)

Richard W. Vuduc, Takahiro Katagiri, 2011, ICCS.

A performance analysis framework for identifying potential benefits in GPGPU applications

Richard W. Vuduc, Hyesoon Kim, Jaewoong Sim, 2012, PPoPP '12.

Courses in High-performance Computing for Scientists and Engineers

Richard W. Vuduc, Aparna Chandramowlishwaran, Kenneth Czechowski, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

Temporal phenotyping of medically complex children via PARAFAC2 tensor factorization

Richard W. Vuduc, Elizabeth Searles, Evangelos E. Papalexakis, 2019, J. Biomed. Informatics.

Annotating user-defined abstractions for optimization

Richard W. Vuduc, Qing Yi, Markus Schordan, 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

A massively parallel adaptive fast-multipole method on heterogeneous architectures

Richard W. Vuduc, Lexing Ying, Tuan-Anh Nguyen, 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

Toward a Theory of Algorithm-Architecture Co-design

Richard W. Vuduc, Kenneth Czechowski, R. Vuduc, 2012, VECPAR.

Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization

Richard W. Vuduc, Daniel J. Quinlan, Chunhua Liao, 2009, LCPC.

Statistical Models for Automatic Performance Tuning

James Demmel, Richard W. Vuduc, Jeff A. Bilmes, 2001, International Conference on Computational Science.

A Communication-Avoiding 3D LU Factorization Algorithm for Sparse Matrices

Richard W. Vuduc, Xiaoye S. Li, Piyush Sao, 2018, 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Sustainable Software Development for Next-Gen Sequencing (NGS) Bioinformatics on Emerging Platforms pdf

Yogesh L. Simmhan, Viktor K. Prasanna, David A. Bader, 2013, ArXiv.

Brief announcement: towards a communication optimal fast multipole method and its implications at exascale

Richard W. Vuduc, Aparna Chandramowlishwaran, Kamesh Madduri, 2012, SPAA '12.

When cache blocking of sparse matrix vector multiply works and why

James Demmel, Richard W. Vuduc, Katherine A. Yelick, 2007, Applicable Algebra in Engineering, Communication and Computing.

Code Generators for Automatic Tuning of Numerical Kernels: Experiences with FFTW

James Demmel, Richard W. Vuduc, J. Demmel, 2000, SAIG.

Statistical Models for Empirical Search-Based Performance Tuning

James Demmel, Richard W. Vuduc, Jeff A. Bilmes, 2004, Int. J. High Perform. Comput. Appl..

SPARTan: Scalable PARAFAC2 for Large & Sparse Data

Fei Wang, Jimeng Sun, Richard W. Vuduc, 2017, KDD.

Improving distributed memory applications testing by message perturbation

Richard W. Vuduc, Bronis R. de Supinski, Daniel J. Quinlan, 2006, PADTAD '06.

An interface for multidimensional arrays in Arkouda

Richard W. Vuduc, Mitesh Kothari, 2021, 2021 IEEE High Performance Extreme Computing Conference (HPEC).

Scalable All-pairs Shortest Paths for Huge Graphs on Multi-GPU Clusters

Richard W. Vuduc, Thomas E. Potok, Ramakrishnan Kannan, 2021, HPDC.

Communication-avoiding kernel ridge regression on parallel and distributed systems

James Demmel, Richard W. Vuduc, Cho-Jui Hsieh, 2021, CCF Transactions on High Performance Computing.