Prasanna Balaprakash

Jong Youl Choi

J. Supercomput., March, 2025

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning.

[BibT_eX]

[DOI]

Randy Michael Churchill

Rory Conlin

Gareth Roberg-Clark

CoRR, February, 2025

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales.

[BibT_eX]

[DOI]

Concurr. Comput. Pract. Exp., January, 2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling.

[BibT_eX]

[DOI]

Reliab. Eng. Syst. Saf., 2025

Revisiting the problem of learning long-term dependencies in recurrent neural networks.

[BibT_eX]

[DOI]

Neural Networks, 2025

Integrating ytopt and libEnsemble to autotune OpenMC.

[BibT_eX]

[DOI]

Int. J. High Perform. Comput. Appl., 2025

SWARM: Reimagining scientific workflow management systems in a distributed world.

[BibT_eX]

[DOI]

Int. J. High Perform. Comput. Appl., 2025

Advancing anomaly detection in computational workflows with active learning.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2025

Is In-Context Learning Feasible for HPC Performance Autotuning?

[BibT_eX]

[DOI]

Proceedings of the 2025 IEEE International Parallel and Distributed Processing Symposium, 2025

PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows.

[BibT_eX]

[DOI]

Rafael Ferreira da Silva

Proceedings of the IEEE International Conference on eScience, 2025

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling.

[BibT_eX]

[DOI]

Chaojian Li

Zhifan Ye

Jong Youl Choi

Cheng Wan

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

2024

A Gradient-Aware Search Algorithm for Constrained Markov Decision Processes.

[BibT_eX]

[DOI]

Sami Khairy

Subramanian Sankaranarayanan

Lin X. Cai

IEEE Trans. Neural Networks Learn. Syst., December, 2024

Automated defect identification in coherent diffraction imaging with smart continual learning.

[BibT_eX]

[DOI]

Tom Peterka

Neural Comput. Appl., December, 2024

Large language model evaluation for high-performance computing software development.

[BibT_eX]

[DOI]

Concurr. Comput. Pract. Exp., November, 2024

Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks.

[BibT_eX]

[DOI]

Tanwi Mallick

Jane MacFarlane

IEEE Trans. Intell. Transp. Syst., August, 2024

Efficient Mapping Between Void Shapes and Stress Fields Using Deep Convolutional Neural Networks With Sparse Data.

[BibT_eX]

[DOI]

Anindya Bhaduri

Nesar Ramachandra

Sandipp Krishnan Ravi

J. Comput. Inf. Sci. Eng., April, 2024

The unreasonable effectiveness of early discarding after one epoch in neural network hyperparameter optimization.

[BibT_eX]

[DOI]

Neurocomputing, 2024

Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations.

[BibT_eX]

[DOI]

Future Gener. Comput. Syst., 2024

Generalizable Prediction Model of Molten Salt Mixture Density with Chemistry-Informed Transfer Learning.

[BibT_eX]

[DOI]

Muhammad Nouman Anwar

Tyler Starkus

Stephen Lam

CoRR, 2024

Scalable Training of Graph Foundation Models for Atomistic Materials Modeling: A Case Study with HydraGNN.

[BibT_eX]

[DOI]

Júlio C. S. Jacques Júnior

CoRR, 2024

Sequence Length Scaling in Vision Transformers for Scientific Images on Frontier.

[BibT_eX]

[DOI]

CoRR, 2024

Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement.

[BibT_eX]

[DOI]

Aditi S. Krishnapriyan

Adam Mate

Arthur K. Barnes

Russell Bent

CoRR, 2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.

[BibT_eX]

[DOI]

CoRR, 2024

Network architecture search of X-ray based scientific applications.

[BibT_eX]

[DOI]

CoRR, 2024

AI Competitions and Benchmarks: Dataset Development.

[BibT_eX]

[DOI]

Romain Egele

CoRR, 2024

Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach.

[BibT_eX]

[DOI]

Yixuan Sun

Olaperi Yeside Sowunmi

Romain Egele

Luke Van Roekel

CoRR, 2024

Optimizing Distributed Training on Frontier for Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the ISC High Performance 2024 Research Paper Proceedings (39th International Conference), 2024

ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2024

ChatBLAS: The First AI-Generated and Portable BLAS Library.

[BibT_eX]

[DOI]

Proceedings of the SC24-W: Workshops of the International Conference for High Performance Computing, 2024

Large Language Models for Anomaly Detection in Computational Workflows: From Supervised Fine-Tuning to In-Context Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2024

Enhancing Power Distribution System Resilience with Fusion-GNN: A Dynamic Graph Representation Learning Approach.

[BibT_eX]

[DOI]

Proceedings of the 50th Annual Conference of the IEEE Industrial Electronics Society, 2024

2023

Graph neural networks for detecting anomalies in scientific workflows.

[BibT_eX]

[DOI]

Int. J. High Perform. Comput. Appl., July, 2023

Multi-fidelity reinforcement learning framework for shape optimization.

[BibT_eX]

[DOI]

J. Comput. Phys., June, 2023

Stabilized neural ordinary differential equations for long-time forecasting of dynamical systems.

[BibT_eX]

[DOI]

J. Comput. Phys., February, 2023

Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics.

[BibT_eX]

[DOI]

Jongeun Kim

Sven Leyffer

INFORMS J. Comput., 2023

Optimizing Distributed Training on Frontier for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

[BibT_eX]

[DOI]

Cindy Orozco Bohorquez

CoRR, 2023

Self-supervised Learning for Anomaly Detection in Computational Workflows.

[BibT_eX]

[DOI]

CoRR, 2023

Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives.

[BibT_eX]

[DOI]

CoRR, 2023

Comparing Llama-2 and GPT-3 LLMs for HPC kernels generation.

[BibT_eX]

[DOI]

CoRR, 2023

Uncertainty Quantification for Molecular Property Predictions with Graph Neural Architecture Search.

[BibT_eX]

[DOI]

CoRR, 2023

Flow-Bench: A Dataset for Computational Workflow Anomaly Detection.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Continually on a Sequence of Graphs - The Dynamical System Way.

[BibT_eX]

[DOI]

Krishnan Raghavan

CoRR, 2023

Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field.

[BibT_eX]

[DOI]

Lele Luan

Nesar Ramachandra

Sandipp Krishnan Ravi

CoRR, 2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles.

[BibT_eX]

[DOI]

CoRR, 2023

Analyzing the impact of climate change on critical infrastructure from the scientific literature: A weakly supervised NLP approach.

[BibT_eX]

[DOI]

Tanwi Mallick

Joshua David Bergerson

CoRR, 2023

Scalable Automated Design and Development of Deep Neural Networks for Scientific and Engineering Applications.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

iWAPT2023 Invited Speaker Optimizing HPC Systems for Scientific Applications: Machine Learning Approaches to Performance Tuning and Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Transfer-learning-based Autotuning using Gaussian Copula.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Supercomputing, 2023

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation.

[BibT_eX]

[DOI]

Proceedings of the 52nd International Conference on Parallel Processing Workshops, 2023

Graph Pyramid Autoformer for Long- Term Traffic Forecasting.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning and Applications, 2023

Application - Hardware Co-Optimization of Crossbar-Based Neuromorphic Systems.

[BibT_eX]

[DOI]

Adarsha Balaji

Proceedings of the International Conference on Machine Learning and Applications, 2023

Multi-Fidelity Reinforcement Learning with Control Variates.

[BibT_eX]

[DOI]

Sami Khairy

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?

[BibT_eX]

[DOI]

Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Asynchronous Decentralized Bayesian Optimization for Large Scale Hyperparameter Optimization.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on e-Science, 2023

Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures.

[BibT_eX]

[DOI]

Angel Yanguas-Gil

Proceedings of the Conference on Lifelong Learning Agents, 2023

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck.

[BibT_eX]

[DOI]

Gustavo de los Campos

Ian Fischer

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., December, 2022

Data-Driven Random Access Optimization in Multi-Cell IoT Networks Using NOMA.

[BibT_eX]

[DOI]

IEEE Trans. Wirel. Commun., 2022

Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness.

[BibT_eX]

[DOI]

CoRR, 2022

Explainable Graph Pyramid Autoformer for Long-Term Traffic Forecasting.

[BibT_eX]

[DOI]

CoRR, 2022

Asynchronous Distributed Bayesian Optimization at HPC Scale.

[BibT_eX]

[DOI]

CoRR, 2022

Multifidelity Reinforcement Learning with Control Variates.

[BibT_eX]

[DOI]

Sami Khairy

CoRR, 2022

Sequential Bayesian Neural Subnetwork Ensembles.

[BibT_eX]

[DOI]

Sanket R. Jantre

Shrijita Bhattacharya

Tapabrata Maiti

CoRR, 2022

Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting.

[BibT_eX]

[DOI]

Tanwi Mallick

Jane MacFarlane

CoRR, 2022

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck.

[BibT_eX]

[DOI]

Anirban Samaddar

CoRR, 2022

Modeling design and control problems involving neural network surrogates.

[BibT_eX]

[DOI]

Dominic Yang

Subramanian Sankaranarayanan

Sven Leyffer

Comput. Optim. Appl., 2022

A cross-study analysis of drug response prediction in cancer cell lines.

[BibT_eX]

[DOI]

Briefings Bioinform., 2022

Workflow Anomaly Detection with Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE/ACM Workshop on Workflows in Support of Large-Scale Science, 2022

Automated Continual Learning of Defect Identification in Coherent Diffraction Imaging.

[BibT_eX]

[DOI]

Tom Peterka

Proceedings of the IEEE/ACM International Workshop on Artificial Intelligence and Machine Learning for Scientific Applications, 2022

A Taxonomy of Error Sources in HPC I/O Machine Learning Models.

[BibT_eX]

[DOI]

Proceedings of the SC22: International Conference for High Performance Computing, 2022

Continual Learning via Dynamic Programming.

[BibT_eX]

[DOI]

R. Krishnan

Subramanian Sankaranarayanan

Proceedings of the 26th International Conference on Pattern Recognition, 2022

AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification.

[BibT_eX]

[DOI]

Proceedings of the 26th International Conference on Pattern Recognition, 2022

HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Cluster Computing, 2022

2021

irace.

[BibT_eX]

[DOI]

Manuel López-Ibáñez

Leslie Pérez Cáceres

Jérémie Dubois-Lacoste

Dataset, June, 2021

In situ compression artifact removal in scientific data using deep transfer learning and experience replay.

[BibT_eX]

[DOI]

Mach. Learn. Sci. Technol., 2021

Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV Based Random Access IoT Networks With NOMA.

[BibT_eX]

[DOI]

IEEE J. Sel. Areas Commun., 2021

A data-centric weak supervised learning for highway traffic incident detection.

[BibT_eX]

[DOI]

CoRR, 2021

AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification.

[BibT_eX]

[DOI]

CoRR, 2021

AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Coherent Imaging.

[BibT_eX]

[DOI]

Yudong Yao

Henry Chan

Ross J. Harder

Mathew J. Cherukara

CoRR, 2021

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version).

[BibT_eX]

[DOI]

CoRR, 2021

Learning-Based Distributed Random Access for Multi-Cell IoT Networks with NOMA.

[BibT_eX]

[DOI]

CoRR, 2021

AgEBO-tabular: joint neural architecture and hyperparameter search with autotuned data-parallel training for tabular data.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2021

Customized Monte Carlo Tree Search for LLVM/Polly's Composable Loop Optimization Transformations.

[BibT_eX]

[DOI]

Proceedings of the 2021 International Workshop on Performance Modeling, 2021

Formalizing the Generalization-Forgetting Trade-off in Continual Learning.

[BibT_eX]

[DOI]

Krishnan Raghavan

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning to Switch Optimizers for Quadratic Programming.

[BibT_eX]

[DOI]

Grant Getzelman

Proceedings of the Asian Conference on Machine Learning, 2021

2020

AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data.

[BibT_eX]

[DOI]

CoRR, 2020

Dynamic Graph Neural Network for Traffic Forecasting in Wide Area Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Meta Continual Learning via Dynamic Programming.

[BibT_eX]

[DOI]

R. Krishnan

CoRR, 2020

Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning.

[BibT_eX]

[DOI]

Angel Yanguas-Gil

CoRR, 2020

Towards On-Chip Bayesian Neuromorphic Learning.

[BibT_eX]

[DOI]

Nathan Wycoff

Fangfang Xia

CoRR, 2020

Site-specific graph neural network for predicting protonation energy of oxygenate molecules.

[BibT_eX]

[DOI]

Romit Maulik

Rajeev Surendran Array

CoRR, 2020

Gauge: An Interactive Data-Driven Visualization Tool for HPC Application I/O Performance Analysis.

[BibT_eX]

[DOI]

Proceedings of the Fifth IEEE/ACM International Parallel Data Systems Workshop, 2020

Recurrent neural network architecture search for geophysical emulation.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2020

HPC I/O throughput bottleneck analysis with explainable local models.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2020

Toward Generalizable Models of I/O Throughput.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers, 2020

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/ACM Performance Modeling, 2020

FIdelity: Efficient Resilience Analysis Framework for Deep Learning Accelerators.

[BibT_eX]

[DOI]

Yi He

Yanjing Li

Proceedings of the 53rd Annual IEEE/ACM International Symposium on Microarchitecture, 2020

Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting.

[BibT_eX]

[DOI]

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Graph Neural Network Architecture Search for Molecular Property Prediction.

[BibT_eX]

[DOI]

Shengli Jiang

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Value-Added Chemical Discovery Using Reinforcement Learning.

[BibT_eX]

[DOI]

Peihong Jiang

Hieu Doan

Rajeev Surendran Assary

CoRR, 2019

Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems.

[BibT_eX]

[DOI]

CoRR, 2019

Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images.

[BibT_eX]

[DOI]

CoRR, 2019

Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting.

[BibT_eX]

[DOI]

CoRR, 2019

Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models.

[BibT_eX]

[DOI]

CoRR, 2019

Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows.

[BibT_eX]

[DOI]

CoRR, 2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles.

[BibT_eX]

[DOI]

Shashi M. Aithal

Proceedings of the High Performance Computing - 34th International Conference, 2019

Scalable reinforcement-learning-based neural architecture search for cancer deep learning research.

[BibT_eX]

[DOI]

Proceedings of the International Conference for High Performance Computing, 2019

A Framework for Enabling OpenMP Autotuning.

[BibT_eX]

[DOI]

Thomas R. W. Scogland

Bronis R. de Supinski

Proceedings of the OpenMP: Conquering the Full Hardware Spectrum, 2019

Adaptive Learning for Concept Drift in Application Performance Modeling.

[BibT_eX]

[DOI]

Proceedings of the 48th International Conference on Parallel Processing, 2019

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.

[BibT_eX]

[DOI]

Nathan Wycoff

Fangfang Xia

Proceedings of the International Conference on Neuromorphic Systems, 2019

Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning.

[BibT_eX]

[DOI]

Angel Yanguas-Gil

Proceedings of the International Conference on Neuromorphic Systems, 2019

Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Exploring the capabilities of support vector machines in detecting silent data corruptions.

[BibT_eX]

[DOI]

Omer Subasi

Sheng Di

Leonardo Bautista-Gomez

Sriram Krishnamoorthy

Sustain. Comput. Informatics Syst., 2018

Autotuning in High-Performance Computing Applications.

[BibT_eX]

[DOI]

Jeffrey K. Hollingsworth

Richard W. Vuduc

Proc. IEEE, 2018

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research.

[BibT_eX]

[DOI]

Cristina Garcia-Cardona

Brian Van Essen

Matthew Baughman

BMC Bioinform., 2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing - 33rd International Conference, 2018

Benchmarking Machine Learning Methods for Performance Modeling of Scientific Applications.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE/ACM Performance Modeling, 2018

Building a Wide-Area File Transfer Performance Predictor: An Empirical Study.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Networking - First International Conference, 2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

Modeling I/O Performance Variability Using Conditional Variational Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Cluster Computing, 2018

2017

Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity.

[BibT_eX]

[DOI]

Proceedings of the 2017 International Conference on Networking, Architecture, and Storage, 2017

Explaining Wide Area Data Transfer Performance.

[BibT_eX]

[DOI]

Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing, 2017

MACORD: Online Adaptive Machine Learning Framework for Silent Error Detection.

[BibT_eX]

[DOI]

Sriram Krishnamoorthy

Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

Analytical Performance Modeling and Validation of Intel's Xeon Phi Architecture.

[BibT_eX]

[DOI]

Proceedings of the Computing Frontiers Conference, 2017

2016

AutoMOMML: Automatic Multi-objective Modeling with Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing - 31st International Conference, 2016

Exploiting Performance Portability in Search Algorithms for Autotuning.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Improving Data Transfer Throughput with Direct Search Optimization.

[BibT_eX]

[DOI]

Proceedings of the 45th International Conference on Parallel Processing, 2016

Spatial Support Vector Regression to Detect Silent Errors in the Exascale Era.

[BibT_eX]

[DOI]

Omer Subasi

Sheng Di

Leonardo Bautista-Gomez

Proceedings of the IEEE/ACM 16th International Symposium on Cluster, 2016

2015

Estimation-based metaheuristics for the single vehicle routing problem with stochastic demands and customers.

[BibT_eX]

[DOI]

Comput. Optim. Appl., 2015

Generating Efficient Tensor Contractions for GPUs.

[BibT_eX]

[DOI]

Proceedings of the 44th International Conference on Parallel Processing, 2015

Autotuning FPGA Design Parameters for Performance and Power.

[BibT_eX]

[DOI]

Proceedings of the 23rd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2015

Collective I/O Tuning Using Analytical and Machine Learning Models.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

2014

Machine-Learning-Based Load Balancing for Community Ice Code Component in CESM.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing for Computational Science - VECPAR 2014 - 11th International Conference, Eugene, OR, USA, June 30, 2014

Analysis of the Tradeoffs Between Energy and Run Time for Multilevel Checkpointing.

[BibT_eX]

[DOI]

Leonardo Arturo Bautista-Gomez

Mohamed-Slim Bouguerra

Leonardo Arturo Bautista-Gomez

Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2014

Energy-performance tradeoffs in multilevel checkpoint strategies.

[BibT_eX]

[DOI]

Mohamed-Slim Bouguerra

Proceedings of the 2014 IEEE International Conference on Cluster Computing, 2014

2013

Multi Objective Optimization of HPC Kernels for Performance, Power, and Energy.

[BibT_eX]

[DOI]

Ananta Tiwari

Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation, 2013

Empirical performance modeling of GPU kernels using active learning.

[BibT_eX]

[DOI]

Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Exascale workload characterization and architecture implications.

[BibT_eX]

[DOI]

Andrew A. Chien

Proceedings of the 2012 IEEE International Symposium on Performance Analysis of Systems & Software, 2013

Active-learning-based surrogate models for empirical performance tuning.

[BibT_eX]

[DOI]

Robert B. Gramacy

Proceedings of the 2013 IEEE International Conference on Cluster Computing, 2013

2012

SPAPT: Search Problems in Automatic Performance Tuning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computational Science, 2012

An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning.

[BibT_eX]

[DOI]

Proceedings of the High Performance Computing for Computational Science, 2012

Poster: An Exascale Workload Study.

[BibT_eX]

[DOI]

Andrew A. Chien

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: An Exascale Workload Study.

[BibT_eX]

[DOI]

Andrew A. Chien

Proceedings of the 2012 SC Companion: High Performance Computing, 2012

2011

Can search algorithms save large-scale automatic performance tuning?

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computational Science, 2011

2010

Estimation-based metaheuristics for the probabilistic traveling salesman problem.

[BibT_eX]

[DOI]

Comput. Oper. Res., 2010

F-Race and Iterated F-Race: An Overview.

[BibT_eX]

[DOI]

Proceedings of the Experimental Methods for the Analysis of Optimization Algorithms., 2010

2009

Estimation-based ant colony optimization and local search for the probabilistic traveling salesman problem.

[BibT_eX]

[DOI]

Swarm Intell., 2009

Adaptive sample size and importance sampling in estimation-based local search for the probabilistic traveling salesman problem.

[BibT_eX]

[DOI]

Eur. J. Oper. Res., 2009

2008

Engineering Stochastic Local Search Algorithms: A Case Study in Estimation-Based Local Search for the Probabilistic Travelling Salesman Problem.

[BibT_eX]

[DOI]