| Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization | 0 | 0.34 | 2020 |
| Vector Forward Mode Automatic Differentiation on SIMD/SIMT architectures. | 0 | 0.34 | 2020 |
| Automatic Differentiation for Adjoint Stencil Loops | 0 | 0.34 | 2019 |
| Training on the Edge: The why and the how | 0 | 0.34 | 2019 |
| Combining Checkpointing and Data Compression to Accelerate Adjoint-Based Optimization Problems. | 0 | 0.34 | 2019 |
| Reverse-mode algorithmic differentiation of an OpenMP-parallel compressible flow solver | 1 | 0.35 | 2019 |
| Vectorised Computation Of Diverging Ensembles | 0 | 0.34 | 2018 |
| Parallelizable adjoint stencil computations using transposed forward-mode algorithmic differentiation. | 1 | 0.35 | 2018 |
| Combining checkpointing and data compression for large scale seismic inversion. | 0 | 0.34 | 2018 |
| Verifying Properties of Differentiable Programs. | 0 | 0.34 | 2018 |
| Report of the HPC Correctness Summit, Jan 25-26, 2017, Washington, DC. | 0 | 0.34 | 2017 |
| Towards Self-Verification in Finite Difference Code Generation. | 0 | 0.34 | 2017 |
| Edge Pushing is Equivalent to Vertex Elimination for Computing Hessians. | 0 | 0.34 | 2016 |
| Generating Efficient Tensor Contractions for GPUs. | 6 | 0.51 | 2015 |
| Autotuning FPGA Design Parameters for Performance and Power | 10 | 0.67 | 2015 |
| Collective I/O Tuning Using Analytical and Machine Learning Models | 11 | 0.59 | 2015 |
| Energy-performance tradeoffs in multilevel checkpoint strategies. | 0 | 0.34 | 2014 |
| Analysis Of The Tradeoffs Between Energy And Run Time For Multilevel Checkpointing | 3 | 0.42 | 2014 |
| Software Abstractions and Methodologies for HPC Simulation Codes on Future Architectures. | 5 | 0.48 | 2013 |
| Empirical performance modeling of GPU kernels using active learning. | 3 | 0.39 | 2013 |
| Poster: An Exascale Workload Study | 1 | 0.36 | 2012 |
| An Experimental Study Of Global And Local Search Algorithms In Empirical Performance Tuning | 4 | 0.58 | 2012 |
| Can Search Algorithms Save Large-Scale Automatic Performance Tuning? | 10 | 0.67 | 2011 |
| Speeding up Nek5000 with autotuning and specialization | 22 | 0.98 | 2010 |
| Generating Performance Bounds from Source Code | 13 | 0.77 | 2010 |
| Evaluation of Hierarchical Mesh Reorderings | 1 | 0.36 | 2009 |
| Improving Random Walk Performance | 1 | 0.36 | 2009 |
| Improving the Performance of Graph Coloring Algorithms through Backtracking | 2 | 0.41 | 2008 |
| On the implementation of automatic differentiation tools | 14 | 1.03 | 2008 |
| Term Graphs for Computing Derivatives in Imperative Languages | 0 | 0.34 | 2007 |
| Comparison of two activity analyses for automatic differentiation: context-sensitive flow-insensitive vs. context-insensitive flow-sensitive | 1 | 0.38 | 2007 |
| Data-Flow Analysis for MPI Programs | 33 | 1.69 | 2006 |
| Making Automatic Differentiation Truly Automatic: Coupling PETSc with ADIC | 6 | 0.85 | 2005 |
| Metrics and models for reordering transformations | 25 | 1.32 | 2004 |
| A Distributed Application Server for Automatic Differentiation | 0 | 0.34 | 2001 |
| Parallel simulation of compressible flow using automatic differentiation and PETSc | 11 | 0.98 | 2001 |
| On Combining Computational Differentiation and Toolkits for Parallel Scientific Computing | 2 | 0.45 | 2000 |
| Solving Nonlinear PDEs Using PETSc and Automatic Differentiation | 0 | 0.34 | 1999 |
| Automatic Differentiation for Message-Passing Parallel Programs | 8 | 1.03 | 1998 |
| Automatic Differentiation of a Parallel Molecular Dynamics Application | 0 | 0.34 | 1997 |
| Efficient Derivative Codes through Automatic Differentiation and Interface Contraction: An Application in Biostatistics | 11 | 2.40 | 1997 |
| A Model for Automatic Data Partitioning | 7 | 0.63 | 1993 |
| Further Research on Feature Selection and Classification Using Genetic Algorithms | 121 | 19.29 | 1993 |
