Publications
- Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization, arxiv preprint arXiv:2306.00357 (Link)
- Detecting resonance of radio-frequency cavities using fast direct integral equation solvers and augmented Bayesian optimization, arxiv preprint arXiv:2305.05918 (Link)
- Harnessing the Crowd for Autotuning HPC Applications, IEEE IPDPS 2023 (Link)
- Hybrid Models for Mixed Variables in Bayesian Optimization, arXiv preprint arXiv:2206.01409 (Link)
- GPTuneBand: Multi-task and Multi-fidelity Autotuning for Large-scale High Performance Computing Applications, 2022 SIAM Conference on Parallel Processing for Scientific Computing (Link)
- Non-smooth Bayesian Optimization in Tuning Problems, arXiv preprint arXiv:2109.07563 (Link)
- Enhancing Autotuning Capability with a History Database, MCSoC-2021, Special Session: Autotuning for Multicore & GPU (Link)
- GPTune: multitask learning for autotuning exascale applications, PPoPP 2021 (Link)
- Multitask and transfer learning for autotuning exascale applications, arXiv preprint arXiv:1908.05792 (Link)
Talks/Media
- Performance Autotuning of ECP Applications with Gaussian Process Based and Cloud Database Enhanced, Tutorial at ECP Annual Meeting 2022 (Link)
- Enhancing Autotuning Capability with a History Database, MCSoC-2021, Special Session: Autotuning for Multicore & GPU, December 22, 2021 (Link)
- GPTune: Multitask Learning for Autotuning Exascale Applications, PPoPP 2021, February 27, 2021 (Link)
- Autotuning exascale applications with Gaussian Process Regression, E-NLA Seminar, October 14, 2020 (Link)
Tutorials
White papers
- Crowd-tuning with GPTune History Database: Design Overview, Data-sharing Policy, and Plan to Maintain Security (Link)