Richard W. Vuduc

JeeWhan Choi, Richard W. Vuduc: How much (execution) time and energy does my algorithm cost? ACM Crossroads 19(3): 49-51 (2013)

Hyesoon Kim, Richard W. Vuduc, Sara S. Baghsorkhi, JeeWhan Choi, Wen-mei W. Hwu: Performance Analysis and Tuning for General Purpose Graphics Processing Units (GPGPU). Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers 2012

Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan-Anh Nguyen, Rahul S. Sampath, Aashay Shringarpure, Richard W. Vuduc, Lexing Ying, Denis Zorin, George Biros: A massively parallel adaptive fast multipole method on heterogeneous architectures. Commun. ACM 55(5): 101-109 (2012)

Jaekyu Lee, Hyesoon Kim, Richard W. Vuduc: When Prefetching Works, When It Doesn't, and Why. TACO 9(1): 2 (2012)

Cong Hou, George Vulov, Daniel J. Quinlan, David Jefferson, Richard Fujimoto, Richard W. Vuduc: A New Method for Program Inversion. CC 2012: 81-100

Kenneth Czechowski, Casey Battaglino, Chris McClanahan, Kartik Iyer, P.-K. Yeung, Richard W. Vuduc: On the communication complexity of 3D FFTs and its implications for Exascale. ICS 2012: 205-214

Sangmin Park, Richard W. Vuduc, Mary Jean Harrold: A Unified Approach for Localizing Non-deadlock Concurrency Bugs. ICST 2012: 51-60

Richard W. Vuduc, Kenneth Czechowski, Aparna Chandramowlishwaran, JeeWhan Choi: Courses in High-performance Computing for Scientists and Engineers. IPDPS Workshops 2012: 1335-1340

Aparna Chandramowlishwaran, Richard W. Vuduc: Communication-Optimal Parallel N-body Solvers. IPDPS Workshops 2012: 2462-2465

JeeWhan Choi, Richard W. Vuduc: Modeling and Analysis for Performance and Power. IPDPS Workshops 2012: 2466-2469

Sooraj Bhat, Ashish Agarwal, Richard W. Vuduc, Alexander G. Gray: A type theory for probability density functions. POPL 2012: 545-556

Jaewoong Sim, Aniruddha Dasgupta, Hyesoon Kim, Richard W. Vuduc: A performance analysis framework for identifying potential benefits in GPGPU applications. PPOPP 2012: 11-22

Cong Hou, Daniel J. Quinlan, David Jefferson, Richard Fujimoto, Richard W. Vuduc: Synthesizing Loops for Program Inversion. RC 2012: 72-84

William B. March, Kenneth Czechowski, Marat Dukhan, Thomas Benson, Dongryeol Lee, Andrew J. Connolly, Richard W. Vuduc, Edmond Chow, Alexander G. Gray: Optimizing the computation of n-point correlations on large-scale astronomical data. SC 2012: 74

Dongryeol Lee, Richard W. Vuduc, Alexander G. Gray: A Distributed Kernel Summation Framework for General-Dimension Machine Learning. SDM 2012: 391-402

Aparna Chandramowlishwaran, JeeWhan Choi, Kamesh Madduri, Richard W. Vuduc: Brief announcement: towards a communication optimal fast multipole method and its implications at exascale. SPAA 2012: 182-184

Richard W. Vuduc, Kent Czechowski: What GPU Computing Means for High-End Systems. IEEE Micro 31(4): 74-78 (2011)

Takahiro Katagiri, Richard W. Vuduc: The Sixth International Workshop on Automatic Performance Tuning (iWAPT2011). Procedia CS 4: 2124-2125 (2011)

George Vulov, Cong Hou, Richard W. Vuduc, Richard Fujimoto, Daniel J. Quinlan, David Jefferson: The Backstroke framework for source level reverse computation applied to parallel discrete event simulation. Winter Simulation Conference 2011: 2965-2979

Richard W. Vuduc: Autotuning. Encyclopedia of Parallel Computing 2011: 102-105

Sooraj Bhat, Ashish Agarwal, Alexander G. Gray, Richard W. Vuduc: Toward interactive statistical modeling. Procedia CS 1(1): 1835-1844 (2010)

Sangmin Park, Richard W. Vuduc, Mary Jean Harrold: Falcon: fault localization in concurrent programs. ICSE (1) 2010: 245-254

Aparna Chandramowlishwaran, Kathleen Knobe, Richard W. Vuduc: Performance evaluation of concurrent collections on high-performance multicore computing systems. IPDPS 2010: 1-12

Aparna Chandramowlishwaran, Samuel Williams, Leonid Oliker, Ilya Lashuk, George Biros, Richard W. Vuduc: Optimizing and tuning the fast multipole method for state-of-the-art multicore architectures. IPDPS 2010: 1-12

Richard W. Vuduc: Unconventional wisdom in multicore computing. IPDPS 2010: 1

Jaekyu Lee, Nagesh B. Lakshminarayana, Hyesoon Kim, Richard W. Vuduc: Many-Thread Aware Prefetching Mechanisms for GPGPU Applications. MICRO 2010: 213-224

JeeWhan Choi, Amik Singh, Richard W. Vuduc: Model-driven autotuning of sparse matrix-vector multiply on GPUs. PPOPP 2010: 115-126

Aparna Chandramowlishwaran, Kathleen Knobe, Richard W. Vuduc: Applying the concurrent collections programming model to asynchronous parallel dense linear algebra. PPOPP 2010: 345-346

Aparna Chandramowlishwaran, Kamesh Madduri, Richard W. Vuduc: Diagnosis, Tuning, and Redesign for Multicore Performance: A Case Study of the Fast Multipole Method. SC 2010: 1-12

Abtin Rahimian, Ilya Lashuk, Shravan K. Veerapaneni, Aparna Chandramowlishwaran, Dhairya Malhotra, Logan Moon, Rahul S. Sampath, Aashay Shringarpure, Jeffrey Vetter, Richard W. Vuduc, Denis Zorin, George Biros: Petascale Direct Numerical Simulation of Blood Flow on 200K Cores and Heterogeneous Architectures. SC 2010: 1-11

Samuel Williams, Leonid Oliker, Richard W. Vuduc, John Shalf, Katherine A. Yelick, James Demmel: Optimization of sparse matrix-vector multiplication on emerging multicore platforms. Parallel Computing 35(3): 178-194 (2009)

Nitin Arora, Aashay Shringarpure, Richard W. Vuduc: Direct N-body Kernels for Multicore Platforms. ICPP 2009: 379-387

Sundaresan Venkatasubramanian, Richard W. Vuduc: Tuned and wildly asynchronous stencil kernels for hybrid CPU/GPU systems. ICS 2009: 244-255

Seunghwa Kang, David A. Bader, Richard W. Vuduc: Understanding the design trade-offs among current multicore systems for numerical computations. IPDPS 2009: 1-12

Chunhua Liao, Daniel J. Quinlan, Richard W. Vuduc, Thomas Panas: Effective Source-to-Source Outlining to Support Whole Program Empirical Optimization. LCPC 2009: 308-322

Ilya Lashuk, Aparna Chandramowlishwaran, Harper Langston, Tuan-Anh Nguyen, Rahul S. Sampath, Aashay Shringarpure, Richard W. Vuduc, Lexing Ying, Denis Zorin, George Biros: A massively parallel adaptive fast-multipole method on heterogeneous architectures. SC 2009

Rajesh Nishtala, Richard W. Vuduc, James Demmel, Katherine A. Yelick: When cache blocking of sparse matrix vector multiply works and why. Appl. Algebra Eng. Commun. Comput. 18(3): 297-311 (2007)

Thomas Panas, Thomas Epperly, Daniel J. Quinlan, Andreas Sæbjørnsen, Richard W. Vuduc: Communicating Software Architecture using a Unified Single-View Visualization. ICECCS 2007: 217-228

Qing Yi, Keith Seymour, Haihang You, Richard W. Vuduc, Daniel J. Quinlan: POET: Parameterized Optimizations for Empirical Tuning. IPDPS 2007: 1-8

Daniel J. Quinlan, Richard W. Vuduc, Ghassan Misherghi: Techniques for specifying bug patterns. PADTAD 2007: 27-35

Samuel Williams, Leonid Oliker, Richard W. Vuduc, John Shalf, Katherine A. Yelick, James Demmel: Optimization of sparse matrix-vector multiplication on emerging multicore platforms. SC 2007: 38

Daniel J. Quinlan, Markus Schordan, Richard W. Vuduc, Qing Yi: Annotating user-defined abstractions for optimization. IPDPS 2006

Richard W. Vuduc, Martin Schulz, Daniel J. Quinlan, Bronis R. de Supinski, Andreas Sæbjørnsen: Improving distributed memory applications testing by message perturbation. PADTAD 2006: 27-36

Richard W. Vuduc, Hyun Jin Moon: Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure. HPCC 2005: 807-816

Daniel J. Quinlan, Shmuel Ur, Richard W. Vuduc: An Extensible Open-Source Compiler Infrastructure for Testing. Haifa Verification Conference 2005: 116-133

Richard W. Vuduc, James Demmel, Jeff A. Bilmes: Statistical Models for Empirical Search-Based Performance Tuning. IJHPCA 18(1): 65-94 (2004)

Eun-Jin Im, Katherine A. Yelick, Richard W. Vuduc: Sparsity: Optimization Framework for Sparse Matrix Kernels. IJHPCA 18(1): 135-158 (2004)

Benjamin C. Lee, Richard W. Vuduc, James Demmel, Katherine A. Yelick: Performance Models for Evaluation and Automatic Tuning of Symmetric Sparse Matrix-Vector Multiply. ICPP 2004: 169-176

Rich Vuduc, Attila Gyulassy, James Demmel, Katherine A. Yelick: Memory Hierarchy Optimizations and Performance ounds for Sparse A. International Conference on Computational Science 2003: 705-714

Rich Vuduc, James Demmel, Katherine A. Yelick, Shoaib Kamil, Rajesh Nishtala, Benjamin C. Lee: Performance optimizations and bounds for sparse matrix-vector multiply. SC 2002: 1-35

Rich Vuduc, James Demmel, Jeff Bilmes: Statistical Models for Automatic Performance Tuning. International Conference on Computational Science (1) 2001: 117-126

Rich Vuduc, James Demmel: Code Generators for Automatic Tuning of Numerical Kernels: Experiences with FFTW. SAIG 2000: 190-211

Danyel Fisher, Kris Hildrum, Jason I. Hong, Mark W. Newman, Megan Thomas, Rich Vuduc: SWAMI: a framework for collaborative filtering algorithm development and evaluation. SIGIR 2000: 366-368