Paul D. Hovland

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 45

Top Topics

Machine Learning

Measurement Errors

Top Venues

IPDPS Workshops

Publications

Paul D. Hovland, Jan Hückelheim
Differentiating Through Linear Solvers. CoRR (2024)
Xingfu Wu, John R. Tramm, Jeffrey Larson, John-Luke Navarro, Prasanna Balaprakash, Brice Videau, Michael Kruse, Paul D. Hovland, Valerie E. Taylor, Mary W. Hall
Integrating ytopt and libEnsemble to Autotune OpenMC. CoRR (2024)
Thomas Randall, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall, Rong Ge, Prasanna Balaprakash
Transfer-Learning-Based Autotuning Using Gaussian Copula. CoRR (2024)
Peiyi Li, Ji Liu, Alvin Gonzales, Zain H. Saleem, Huiyang Zhou, Paul D. Hovland
QuTracer: Mitigating Quantum Gate and Measurement Errors by Tracing Subsets of Qubits. ISCA (2024)
Peiyi Li, Ji Liu, Hrushikesh Pramod Patil, Paul D. Hovland, Huiyang Zhou
Enhancing Virtual Distillation with Circuit Cutting for Quantum Error Mitigation. ICCD (2023)
Ji Liu, Max Bowman, Pranav Gokhale, Siddharth Dangwal, Jeffrey Larson, Frederic T. Chong, Paul D. Hovland
QContext: Context-Aware Decomposition for Quantum Gates. ISCAS (2023)
Thomas Randall, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall, Rong Ge, Prasanna Balaprakash
Transfer-learning-based Autotuning using Gaussian Copula. ICS (2023)
Wenhao Wu, Jan Hückelheim, Paul D. Hovland, Ziqing Luo, Stephen F. Siegel
Model Checking Race-freedom When "Sequential Consistency for Data-race-free Programs" is Guaranteed. CoRR (2023)
Xinpeng Li, Ji Liu, Ethan H. Hansen, Shuai Xu, Paul D. Hovland, Vipin Chaudhary
Accelerating VQE Algorithm via Parameters and Measurement Reuse. ICRC (2023)
Xingfu Wu, Prasanna Balaprakash, Michael Kruse, Jaehoon Koo, Brice Videau, Paul D. Hovland, Valerie E. Taylor, Brad Geltz, Siddhartha Jana, Mary W. Hall
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales. CoRR (2023)
Ji Liu, Max Bowman, Pranav Gokhale, Siddharth Dangwal, Jeffrey Larson, Frederic T. Chong, Paul D. Hovland
QContext: Context-Aware Decomposition for Quantum Gates. CoRR (2023)
Ji Liu, Ed Younis, Mathias Weiden, Paul D. Hovland, John Kubiatowicz, Costin Iancu
Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis. QCE (2023)
Jan Hückelheim, Harshitha Menon, William S. Moses, Bruce Christianson, Paul D. Hovland, Laurent Hascoët
Understanding Automatic Differentiation Pitfalls. CoRR (2023)
Wenhao Wu, Jan Hückelheim, Paul D. Hovland, Ziqing Luo, Stephen F. Siegel
Model Checking Race-Freedom When "Sequential Consistency for Data-Race-Free Programs" is Guaranteed. CAV (2) (2023)
Ji Liu, Ed Younis, Mathias Weiden, Paul D. Hovland, John Kubiatowicz, Costin Iancu
Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis. CoRR (2023)
Robert Jackson, Rebecca Gjini, Sri Hari Krishna Narayanan, Matt Menickelly, Paul D. Hovland, Jan Hückelheim, Scott M. Collis
Improving PyDDA's atmospheric wind retrievals using automatic differentiation and Augmented Lagrangian methods. SciPy (2022)
Richard J. Clancy, Matt Menickelly, Jan Hückelheim, Paul D. Hovland, Prani Nalluri, Rebecca Gjini
TROPHY: Trust Region Optimization Using a Precision Hierarchy. ICCS (1) (2022)
Sri Hari Krishna Narayanan, Thomas Propson, Marcelo Bongarti, Jan Hückelheim, Paul D. Hovland
Reducing Memory Requirements of Quantum Optimal Control. ICCS (4) (2022)
William S. Moses, Sri Hari Krishna Narayanan, Ludger Paehler, Valentin Churavy, Michel Schanen, Jan Hückelheim, Johannes Doerfert, Paul D. Hovland
Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation. SC (2022)
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul D. Hovland, Valerie Taylor, Mary W. Hall
Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization. Concurr. Comput. Pract. Exp. 34 (20) (2022)
Wenhao Wu, Jan Hückelheim, Paul D. Hovland, Stephen F. Siegel
Verifying Fortran Programs with CIVL. TACAS (1) (2022)
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul D. Hovland, Valerie E. Taylor, Mary W. Hall
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version). CoRR (2021)
Paul D. Hovland, Jan Hückelheim
Error Estimation and Correction Using the Forward CENA Method. ICCS (1) (2021)
Jaehoon Koo, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations. PMBS (2021)
Jaehoon Koo, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul D. Hovland, Mary W. Hall
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations. CoRR (2021)
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul D. Hovland, Valerie E. Taylor, Mary W. Hall
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization. PMBS@SC (2020)
Jan Hückelheim, Michel Schanen, Sri Hari Krishna Narayanan, Paul D. Hovland
Vector Forward Mode Automatic Differentiation on SIMD/SIMT architectures. ICPP (2020)
Xingfu Wu, Michael Kruse, Prasanna Balaprakash, Hal Finkel, Paul D. Hovland, Valerie E. Taylor, Mary W. Hall
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization. CoRR (2020)
Jan Hückelheim, Navjot Kukreja, Sri Hari Krishna Narayanan, Fabio Luporini, Gerard Gorman, Paul D. Hovland
Automatic Differentiation for Adjoint Stencil Loops. CoRR (2019)
Joseph G. Wallwork, Paul D. Hovland, Hong Zhang, Oana Marin
Computing Derivatives for PETSc Adjoint Solvers using Algorithmic Differentiation. CoRR (2019)
Jan Hückelheim, Navjot Kukreja, Sri Hari Krishna Narayanan, Fabio Luporini, Gerard Gorman, Paul D. Hovland
Automatic Differentiation for Adjoint Stencil Loops. ICPP (2019)
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, Paul D. Hovland, Gerard Gorman
Combining Checkpointing and Data Compression to Accelerate Adjoint-Based Optimization Problems. Euro-Par (2019)
Navjot Kukreja, Alena Shilova, Olivier Beaumont, Jan Hückelheim, Nicola J. Ferrier, Paul D. Hovland, Gerard Gorman
Training on the Edge: The why and the how. CoRR (2019)
Jan Hückelheim, Paul D. Hovland, Michelle Mills Strout, Jens-Dominik Müller
Reverse-mode algorithmic differentiation of an OpenMP-parallel compressible flow solver. Int. J. High Perform. Comput. Appl. 33 (1) (2019)
Navjot Kukreja, Alena Shilova, Olivier Beaumont, Jan Hückelheim, Nicola J. Ferrier, Paul D. Hovland, Gerard Gorman
Training on the Edge: The why and the how. IPDPS Workshops (2019)
Jan Hückelheim, Ziqing Luo, Sri Hari Krishna Narayanan, Stephen F. Siegel, Paul D. Hovland
Verifying Properties of Differentiable Programs. SAS (2018)
Jan Hückelheim, Paul D. Hovland, Sri Hari Krishna Narayanan, Paulius Velesko
Vectorised Computation of Diverging Ensembles. ICPP (2018)
Jan Christian Hückelheim, Paul D. Hovland, Michelle Mills Strout, Jens-Dominik Müller
Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation. Optim. Methods Softw. 33 (4-6) (2018)
Navjot Kukreja, Jan Hückelheim, Mathias Louboutin, Kaiyuan Hou, Fabio Luporini, Paul D. Hovland, Gerard Gorman
Combining checkpointing and data compression for large scale seismic inversion. CoRR (2018)
Jan Hückelheim, Ziqing Luo, Fabio Luporini, Navjot Kukreja, Michael Lange, Gerard Gorman, Stephen F. Siegel, Matthew B. Dwyer, Paul D. Hovland
Towards Self-Verification in Finite Difference Code Generation. CORRECTNESS@SC (2017)
Ganesh Gopalakrishnan, Paul D. Hovland, Costin Iancu, Sriram Krishnamoorthy, Ignacio Laguna, Richard A. Lethin, Koushik Sen, Stephen F. Siegel, Armando Solar-Lezama
Report of the HPC Correctness Summit, Jan 25-26, 2017, Washington, DC. CoRR (2017)
Guillaume Aupy, Julien Herrmann, Paul D. Hovland, Yves Robert
Optimal Multistage Algorithm for Adjoint Computation. SIAM J. Sci. Comput. 38 (3) (2016)
Amit Roy, Prasanna Balaprakash, Paul D. Hovland, Stefan M. Wild
Exploiting Performance Portability in Search Algorithms for Autotuning. IPDPS Workshops (2016)
Prasanna Balaprakash, Ananta Tiwari, Stefan M. Wild, Laura Carrington, Paul D. Hovland
AutoMOMML: Automatic Multi-objective Modeling with Machine Learning. ISC (2016)
Mu Wang, Alex Pothen, Paul D. Hovland
Edge Pushing is Equivalent to Vertex Elimination for Computing Hessians. CSC (2016)
Azamat Mametjanov, Prasanna Balaprakash, Chekuri Choudary, Paul D. Hovland, Stefan M. Wild, Gerald Sabin
Autotuning FPGA Design Parameters for Performance and Power. FCCM (2015)
Thomas Nelson, Axel Rivera, Prasanna Balaprakash, Mary W. Hall, Paul D. Hovland, Elizabeth R. Jessup, Boyana Norris
Generating Efficient Tensor Contractions for GPUs. ICPP (2015)
Florin Isaila, Prasanna Balaprakash, Stefan M. Wild, Dries Kimpe, Robert Latham, Robert B. Ross, Paul D. Hovland
Collective I/O Tuning Using Analytical and Machine Learning Models. CLUSTER (2015)
Leonardo Arturo Bautista-Gomez, Prasanna Balaprakash, Mohamed-Slim Bouguerra, Stefan M. Wild, Franck Cappello, Paul D. Hovland
Energy-performance tradeoffs in multilevel checkpoint strategies. CLUSTER (2014)
Prasanna Balaprakash, Leonardo Arturo Bautista-Gomez, Mohamed-Slim Bouguerra, Stefan M. Wild, Franck Cappello, Paul D. Hovland
Analysis of the Tradeoffs Between Energy and Run Time for Multilevel Checkpointing. PMBS@SC (2014)
Anshu Dubey, Steven R. Brandt, Richard C. Brower, M. Giles, Paul D. Hovland, Don Q. Lamb, Frank Löffler, Boyana Norris, Brian W. O'Shea, Claudio Rebbi, Marc Snir, Rajeev Thakur
Software Abstractions and Methodologies for HPC Simulation Codes on Future Architectures. CoRR (2013)
Prasanna Balaprakash, Darius Buntinas, Anthony Chan, Apala Guha, Rinku Gupta, Sri Hari Krishna Narayanan, Andrew A. Chien, Paul D. Hovland, Boyana Norris
Exascale workload characterization and architecture implications. SpringSim (HPC) (2013)
Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild
Empirical performance modeling of GPU kernels using active learning. PARCO (2013)
Prasanna Balaprakash, Darius Buntinas, Anthony Chan, Apala Guha, Rinku Gupta, Sri Hari Krishna Narayanan, Andrew A. Chien, Paul D. Hovland, Boyana Norris
Exascale workload characterization and architecture implications. ISPASS (2013)
Prasanna Balaprakash, Darius Buntinas, Anthony Chan, Apala Guha, Rinku Gupta, Sri Hari Krishna Narayanan, Andrew A. Chien, Paul D. Hovland, Boyana Norris
Abstract: An Exascale Workload Study. SC Companion (2012)
Prasanna Balaprakash, Darius Buntinas, Anthony Chan, Apala Guha, Rinku Gupta, Sri Hari Krishna Narayanan, Andrew A. Chien, Paul D. Hovland, Boyana Norris
Poster: An Exascale Workload Study. SC Companion (2012)
Prasanna Balaprakash, Stefan M. Wild, Paul D. Hovland
An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning. VECPAR (2012)
Prasanna Balaprakash, Stefan M. Wild, Paul D. Hovland
Can search algorithms save large-scale automatic performance tuning? ICCS (2011)
Sri Hari Krishna Narayanan, Boyana Norris, Paul D. Hovland, Duc C. Nguyen, Assefaw Hadish Gebremedhin
Sparse Jacobian Computation Using ADIC2 and ColPack. ICCS (2011)
Jaewook Shin, Mary W. Hall, Jacqueline Chame, Chun Chen, Paul F. Fischer, Paul D. Hovland
Speeding up Nek5000 with autotuning and specialization. ICS (2010)
Sri Hari Krishna Narayanan, Boyana Norris, Paul D. Hovland
Generating Performance Bounds from Source Code. ICPP Workshops (2010)
Michelle Mills Strout, Nissa Osheim, Dave Rostron, Paul D. Hovland, Alex Pothen
Evaluation of Hierarchical Mesh Reorderings. ICCS (1) (2009)
Ilya Safro, Paul D. Hovland, Jaewook Shin, Michelle Mills Strout
Improving Random Walk Performance. CSC (2009)
Jean Utke, Laurent Hascoët, Patrick Heimbach, Chris Hill, Paul D. Hovland, Uwe Naumann
Toward adjoinable MPI. IPDPS (2009)
Christian H. Bischof, Paul D. Hovland, Boyana Norris
On the implementation of automatic differentiation tools. High. Order Symb. Comput. 21 (3) (2008)
Sanjukta Bhowmick, Paul D. Hovland
Improving the Performance of Graph Coloring Algorithms through Backtracking. ICCS (1) (2008)
Uwe Naumann, Laurent Hascoët, Chris Hill, Paul D. Hovland, Jan Riehme, Jean Utke
A Framework for Proving Correctness of Adjoint Message-Passing Programs. PVM/MPI (2008)
Paul D. Hovland, Boyana Norris, Michelle Mills Strout, Jean Utke
Term Graphs for Computing Derivatives in Imperative Languages. Electron. Notes Theor. Comput. Sci. 176 (1) (2007)
Jaewook Shin, Paul D. Hovland
Comparison of two activity analyses for automatic differentiation: context-sensitive flow-insensitive vs. context-insensitive flow-sensitive. SAC (2007)
Barbara Kreaseck, Luis Ramos, Scott Easterday, Michelle Mills Strout, Paul D. Hovland
Hybrid Static/Dynamic Activity Analysis. International Conference on Computational Science (4) (2006)
Michelle Mills Strout, Barbara Kreaseck, Paul D. Hovland
Data-Flow Analysis for MPI Programs. ICPP (2006)
Michelle Mills Strout, Paul D. Hovland
Linearity Analysis for Automatic Differentiation. International Conference on Computational Science (4) (2006)
Paul D. Hovland, Boyana Norris, Barry F. Smith
Making automatic differentiation truly automatic: coupling PETSc with ADIC. Future Gener. Comput. Syst. 21 (8) (2005)
Michelle Mills Strout, John M. Mellor-Crummey, Paul D. Hovland
Representation-independent program analysis. PASTE (2005)
Michelle Mills Strout, Paul D. Hovland
Metrics and models for reordering transformations. Memory System Performance (2004)
Paul D. Hovland, Boyana Norris, Barry F. Smith
Making Automatic Differentiation Truly Automatic: Coupling PETSc with ADIC. International Conference on Computational Science (2) (2002)
Boyana Norris, Satish Balay, Steven Benson, Lori A. Freitag, Paul D. Hovland, Lois C. McInnes, Barry F. Smith
Parallel components for PDEs and optimization: some issues and experiences. Parallel Comput. 28 (12) (2002)
Christian H. Bischof, Paul D. Hovland, Boyana Norris
Implementation of automatic differentiation tools. PEPM (2002)
Paul D. Hovland, Lois C. McInnes
Parallel simulation of compressible flow using automatic differentiation and PETSc. Parallel Comput. 27 (4) (2001)
Boyana Norris, Paul D. Hovland
A Distributed Application Server for Automatic Differentiation. IPDPS (2001)
Christian H. Bischof, H. Martin Bücker, Paul D. Hovland
On Combining Computational Differentiation and Toolkits for Parallel Scientific Computing. Euro-Par (2000)
Lori A. Freitag, William Gropp, Paul D. Hovland, Lois C. McInnes, Barry F. Smith
Infrastructure and Interfaces for Large-Scale Numerical Software. PDPTA (1999)
Paul D. Hovland, Lois C. McInnes, Barry F. Smith
Solving Nonlinear PDEs Using PETSc and Automatic Differentiation. PPSC (1999)
Paul D. Hovland, Christian H. Bischof
Automatic Differentiation for Message-Passing Parallel Programs. IPPS/SPDP (1998)
Paul D. Hovland, Christian H. Bischof, Lucas Roh
Automatic Differentiation of a Parallel Molecular Dynamics Application. PPSC (1997)
Paul D. Hovland, Christian H. Bischof, Donna Spiegelman, Mario Casella
Efficient Derivative Codes through Automatic Differentiation and Interface Contraction: An Application in Biostatistics. SIAM J. Sci. Comput. 18 (4) (1997)
Paul D. Hovland, Lionel M. Ni
A Model for Automatic Dta Partitioning. ICPP (2) (1993)
William F. Punch III, Erik D. Goodman, Min Pei, Lai Chia-Shun, Paul D. Hovland, Richard J. Enbody
Further Research on Feature Selection and Classification Using Genetic Algorithms. ICGA (1993)
Christian H. Bischof, Alan Carle, George F. Corliss, Andreas Griewank, Paul D. Hovland
ADIFOR - Generating Derivative Codes form Fortran Programs. Sci. Program. 1 (1) (1992)