Prasanna Balaprakash

According to our database1, Prasanna Balaprakash authored at least 57 papers between 2006 and 2020.

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Bibliography

2020
Constrained Deep Reinforcement Learning for Energy Sustainable Multi-UAV based Random Access IoT Networks with NOMA.
CoRR, 2020

Site-specific graph neural network for predicting protonation energy of oxygenate molecules.
CoRR, 2020

2019
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems.
CoRR, 2019

Value-Added Chemical Discovery Using Reinforcement Learning.
CoRR, 2019

Reinforcement-Learning-Based Variational Quantum Circuits Optimization for Combinatorial Problems.
CoRR, 2019

Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images.
CoRR, 2019

Graph-Partitioning-Based Diffusion Convolution Recurrent Neural Network for Large-Scale Traffic Forecasting.
CoRR, 2019

Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models.
CoRR, 2019

Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows.
CoRR, 2019

MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles.
Proceedings of the High Performance Computing - 34th International Conference, 2019

Scalable reinforcement-learning-based neural architecture search for cancer deep learning research.
Proceedings of the International Conference for High Performance Computing, 2019

A Framework for Enabling OpenMP Autotuning.
Proceedings of the OpenMP: Conquering the Full Hardware Spectrum, 2019

Adaptive Learning for Concept Drift in Application Performance Modeling.
Proceedings of the 48th International Conference on Parallel Processing, 2019

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout.
Proceedings of the International Conference on Neuromorphic Systems, 2019

Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning.
Proceedings of the International Conference on Neuromorphic Systems, 2019

2018
Exploring the capabilities of support vector machines in detecting silent data corruptions.
Sustain. Comput. Informatics Syst., 2018

Autotuning in High-Performance Computing Applications.
Proceedings of the IEEE, 2018

CANDLE/Supervisor: a workflow framework for machine learning applied to cancer research.
BMC Bioinformatics, 2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems.
Proceedings of the High Performance Computing - 33rd International Conference, 2018

Benchmarking Machine Learning Methods for Performance Modeling of Scientific Applications.
Proceedings of the 2018 IEEE/ACM Performance Modeling, 2018

Building a Wide-Area File Transfer Performance Predictor: An Empirical Study.
Proceedings of the Machine Learning for Networking - First International Conference, 2018

DeepHyper: Asynchronous Hyperparameter Search for Deep Neural Networks.
Proceedings of the 25th IEEE International Conference on High Performance Computing, 2018

Modeling I/O Performance Variability Using Conditional Variational Autoencoders.
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.
Proceedings of the 2017 International Conference on Networking, Architecture, and Storage, 2017

Explaining Wide Area Data Transfer Performance.
Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing, 2017

MACORD: Online Adaptive Machine Learning Framework for Silent Error Detection.
Proceedings of the 2017 IEEE International Conference on Cluster Computing, 2017

Analytical Performance Modeling and Validation of Intel's Xeon Phi Architecture.
Proceedings of the Computing Frontiers Conference, 2017

2016
AutoMOMML: Automatic Multi-objective Modeling with Machine Learning.
Proceedings of the High Performance Computing - 31st International Conference, 2016

Exploiting Performance Portability in Search Algorithms for Autotuning.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Improving Data Transfer Throughput with Direct Search Optimization.
Proceedings of the 45th International Conference on Parallel Processing, 2016

Spatial Support Vector Regression to Detect Silent Errors in the Exascale Era.
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.
Comp. Opt. and Appl., 2015

Generating Efficient Tensor Contractions for GPUs.
Proceedings of the 44th International Conference on Parallel Processing, 2015

Autotuning FPGA Design Parameters for Performance and Power.
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.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

2014
Machine-Learning-Based Load Balancing for Community Ice Code Component in CESM.
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.
Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2014

Energy-performance tradeoffs in multilevel checkpoint strategies.
Proceedings of the 2014 IEEE International Conference on Cluster Computing, 2014

2013
Exascale workload characterization and architecture implications.
Proceedings of the 2013 Spring Simulation Multiconference, SpringSim '13, 2013

Multi Objective Optimization of HPC Kernels for Performance, Power, and Energy.
Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking and Simulation, 2013

Empirical performance modeling of GPU kernels using active learning.
Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Active-learning-based surrogate models for empirical performance tuning.
Proceedings of the 2013 IEEE International Conference on Cluster Computing, 2013

2012
SPAPT: Search Problems in Automatic Performance Tuning.
Proceedings of the International Conference on Computational Science, 2012

An Experimental Study of Global and Local Search Algorithms in Empirical Performance Tuning.
Proceedings of the High Performance Computing for Computational Science, 2012

Poster: An Exascale Workload Study.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Abstract: An Exascale Workload Study.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

2011
Can search algorithms save large-scale automatic performance tuning?
Proceedings of the International Conference on Computational Science, 2011

2010
Estimation-based metaheuristics for the probabilistic traveling salesman problem.
Comput. Oper. Res., 2010

F-Race and Iterated F-Race: An Overview.
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.
Swarm Intelligence, 2009

Adaptive sample size and importance sampling in estimation-based local search for the probabilistic traveling salesman problem.
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.
Proceedings of the Recent Advances in Evolutionary Computation for Combinatorial Optimization, 2008

Estimation-Based Local Search for Stochastic Combinatorial Optimization Using Delta Evaluations: A Case Study on the Probabilistic Traveling Salesman Problem.
INFORMS Journal on Computing, 2008

Iterated Greedy Algorithms for a Real-World Cyclic Train Scheduling Problem.
Proceedings of the Hybrid Metaheuristics, 5th International Workshop, 2008

2007
Improvement Strategies for the F-Race Algorithm: Sampling Design and Iterative Refinement.
Proceedings of the Hybrid Metaheuristics, 4th International Workshop, 2007

The ACO/F-Race Algorithm for Combinatorial Optimization Under Uncertainty.
Proceedings of the Metaheuristics, 2007

2006
Incremental Local Search in Ant Colony Optimization: Why It Fails for the Quadratic Assignment Problem.
Proceedings of the Ant Colony Optimization and Swarm Intelligence, 2006


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