Optimization-Based Mappers and Lower Bounds for Tensor Problems
Grace Dinh [2023]

Fast and Accurate Machine Learning on Distributed Systems and Supercomputers
Yang You [2020]

Evaluation of Methods for Data-Driven Tools that Empower Mental Health Professionals
Orianna DeMasi [2019]

Measuring Generalization and Overfitting in Machine Learning
Rebecca Roelofs [2019]

Avoiding Communication in First Order Methods for Optimization
Aditya Devarakonda [2018]

Understanding Latency Hiding on GPUs
Vasily Volkov [2016]

Communication-Avoiding Krylov Subspace Methods in Theory and Practice
Erin Carson [2015]

Communication-Optimal Loop Nests
Nick Knight [2015]

Bounds on the Energy Consumption of Computational Kernels
Andrew Gearhart [2014]

Provably Efficient Algorithms for Numerical Tensor Algebra
Edgar Solomonik [2014]

Avoiding Communication in Dense Linear Algebra
Grey Ballard [2013]

Communication-avoiding Krylov subspace methods
Mark Frederick Hoemmen [2010]

Making Static Pivoting Scalable and Dependable
Jason Riedy [2010]

PERCU: A Holistic Method for Evaluating High Performance Computing Systems
William TC Kramer [2008]

Methods and Devices for Optical and Electrical Metrology with Application to Phase-Shifting Interferometers, Torsional Microstructures, and Levitated Accelerometers
David G Garmire [2007]

Structured and Parameter-Dependent Eigensolvers for Simulation-Based Design of Resonant MEMS
David Samuel Bindel [2006]

Automatic Performance Tuning of Sparse Matrix Kernels
Richard W. Vuduc [2003]

Preconditioning Sparse Matrices for Computing Eigenvalues and Solving Linear Systems of Equations
Tzu-Yi Chen [2001]

Pbody: A parallel N-Body Library
David T. Blackston [2000]

A New O(n^2) Algorithm for the Symmetric Tridiagonal Eigenvalue/Eigenvector Problem
Inderjit Singh Dhillon [1997]

Execution Time of Symmetric Eigensolvers
Kendall Swenson Stanley [1997]

Sparse Gaussian Elimination on High Performance Computers
Xiaoye S. Li [1996]