15 citations · 23 across the 6 of their papers we have counts for
7 papers
Transfer-Learning-Based Autotuning Using Gaussian Copula
Thomas Randall, Jaehoon Koo, Brice Videau +6
As diverse high-performance computing (HPC) systems are built, many opportunities arise for applications to solve larger problems than ever before. Given the significantly increase…
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales
Xingfu Wu, Prasanna Balaprakash, Michael Kruse +7
As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical…
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization
Matthieu Dorier, Romain Egele, Prasanna Balaprakash +5
Distributed data storage services tailored to specific applications have grown popular in the high-performance computing (HPC) community as a way to address I/O and storage challen…
Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations
Jaehoon Koo, Prasanna Balaprakash, Michael Kruse +3
Polly is the LLVM project's polyhedral loop nest optimizer. Recently, user-directed loop transformation pragmas were proposed based on LLVM/Clang and Polly. The search space expose…
Inverse Classification with Limited Budget and Maximum Number of Perturbed Samples
Jaehoon Koo, Diego Klabjan, Jean Utke
Most recent machine learning research focuses on developing new classifiers for the sake of improving classification accuracy. With many well-performing state-of-the-art classifier…
Combined convolutional and recurrent neural networks for hierarchical classification of images
Jaehoon Koo, Diego Klabjan, Jean Utke
Deep learning models based on CNNs are predominantly used in image classification tasks. Such approaches, assuming independence of object categories, normally use a CNN as a featur…