Journal Papers (Top)
Thicket: Seeing the Performance Experiment Forest for the Individual Run Trees
@article{brink2023thicket,
title={Thicket: Seeing the Performance Experiment Forest for the Individual Run Trees},
author={Brink, Stephanie and McKinsey, Michael and Boehme, David and Scully-Allison, Connor and
Lumsden, Ian and Hawkins, Daryl and Burgess, Treece and Lama, Vanessa and Luettgau, Jakob and
Isaacs, Katherine E and others},
journal={High-Performance Parallel and Distributed Computing (HPDC 2023)},
volume={6},
number={7},
pages={23},
year={2023}
}
Reproducibility of the first image of a black hole in the galaxy M87 from the event horizon telescope (EHT) collaboration
@article{patel2023reproducibility,
title={Reproducibility of the first image of a black hole in the galaxy M87 from the event
horizon telescope (EHT) collaboration},
author={Patel, Ria and Roachell, Brandan and Caino-Lores, Silvina and Ketron, Ross and Leonard,
Jacob and Tan, Nigel and Vahi, Karan and Brown, Duncan A and Deelman, Ewa and Taufer,
Michela},
journal={Computing in Science \& Engineering},
year={2023},
publisher=IEEE
}
Reproducing the results for NICER observation of PSR J0030+ 0451
@article{afle2023reproducing,
title={Reproducing the results for NICER observation of PSR J0030+ 0451},
author={Afle, Chaitanya and Miles, Patrick R and Caino-Lores, Silvina and Capano, Collin D and
Tews, Ingo and Vahi, Karan and Deelman, Ewa and Taufer, Michela and Brown, Duncan A},
journal={arXiv preprint arXiv:2304.01035},
year=2023
}
A Survey of Graph Comparison Methods with Applications to Nondeterminism in High-Performance Computing
@article{bhowmick2023survey,
title={A Survey of Graph Comparison Methods with Applications to Nondeterminism in
High-Performance Computing},
author={Bhowmick, Sanjukta and Bell, Patrick and Taufer, Michela},
journal={The International Journal of High Performance Computing Applications},
pages={10943420231166610},
year={2023},
publisher={SAGE Publications Sage UK: London, England}
}
Orchestration of materials science workflows for heterogeneous resources at large scale
@article{zhou2023orchestration,
title={Orchestration of materials science workflows for heterogeneous resources at large
scale},
author={Zhou, Naweiluo and Scorzelli, Giorgio and Luettgau, Jakob and Kancharla, Rahul R and
Kane, Joshua J and Wheeler, Robert and Croom, Brendan P and Newell, Pania and Pascucci, Valerio
and Taufer, Michela},
journal={The International Journal of High Performance Computing Applications},
pages={10943420231167800},
year={2023},
publisher={SAGE Publications Sage UK: London, England}
}
Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and Annotation of Collective Variables
@inproceedings{caino2023runtime,
title={Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and
Annotation of Collective Variables},
author={Caino-Lores, Silvina and Cuendet, Michel and Marquez, Jack and Kots, Ekaterina and
Estrada, Trilce and Deelman, Ewa and Weinstein, Harel and Taufer, Michela},
booktitle={Proceedings of the Platform for Advanced Scientific Computing Conference},
pages={1--11},
year={2023}
}
Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use Case
@inproceedings{olaya2023enabling,
title={Enabling Scalability in the Cloud for Scientific Workflows: An Earth Science Use
Case},
author={Olaya, Paula and Luettgau, Jakob and Roa, Camila and Llamas, Ricardo and Vargas, Rodrigo
and Wen, Sophia and Chung, I-Hsin and Seelam, Seetharami and Park, Yoonho and Lofstead, Jay and
others},
booktitle={2023 IEEE 16th International Conference on Cloud Computing (CLOUD)},
pages={383--393},
year={2023},
organization={IEEE}
}
Development of Large-Scale Scientific Cyberinfrastructure and the Growing Opportunity to Democratize Access to Platforms and Data
@inproceedings{luettgau2023development,
title={Development of Large-Scale Scientific Cyberinfrastructure and the Growing Opportunity to
Democratize Access to Platforms and Data},
author={Luettgau, Jakob and Scorzelli, Giorgio and Pascucci, Valerio and Taufer, Michela},
booktitle={International Conference on Human-Computer Interaction},
pages={378--389},
year={2023},
organization={Springer}
}
Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication
@inproceedings{tan2023scalable,
title={Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication},
author={Tan, Nigel and Luettgau, Jakob and Marquez, Jack and Teranishi, Keita and Morales,
Nicolas and Bhowmick, Sanjukta and Cappello, Franck and Taufer, Michela and Nicolae,
Bogdan},
booktitle={Proceedings of the 52nd International Conference on Parallel Processing},
pages={665--674},
year={2023}
}
GEOtiled: A Scalable Workflow for Generating Large Datasets of High-Resolution Terrain Parameters
@inproceedings{roa2023geotiled,
title={GEOtiled: A Scalable Workflow for Generating Large Datasets of High-Resolution Terrain
Parameters},
author={Roa, Camila and Olaya, Paula and Llamas, Ricardo and Vargas, Rodrigo and Taufer,
Michela},
booktitle={Proceedings of the 32nd International Symposium on High-Performance Parallel and
Distributed Computing},
pages={311--312},
year={2023}
}
Studying Latency and Throughput Constraints for Geo-Distributed Data in the National Science Data Fabric
@inproceedings{luettgau2023studying,
title={Studying Latency and Throughput Constraints for Geo-Distributed Data in the National
Science Data Fabric},
author={Luettgau, Jakob and Martinez, Heberth and Tarcea, Glenn and Scorzelli, Giorgio and
Pascucci, Valerio and Taufer, Michela},
booktitle={Proceedings of the 32nd International Symposium on High-Performance Parallel and
Distributed Computing},
pages={325--326},
year={2023}
}
Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification
@inproceedings{channing2023composable,
title={Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics
for Protein Classification},
author={Channing, Georgia and Patel, Ria and Olaya, Paula and Rorabaugh, Ariel and Miyashita,
Osamu and Caino-Lores, Silvina and Schuman, Catherine and Tama, Florence and Taufer,
Michela},
booktitle={Proceedings of the 52nd International Conference on Parallel Processing},
pages={1--1},
year={2023}
}
Performance assessment of ensembles of in situ workflows under resource constraints
@article{do2023performance,
title={Performance assessment of ensembles of in situ workflows under resource constraints},
author={Do, Tu Mai Anh and Pottier, Lo{\"\i}c and Ferreira da Silva, Rafael and
Ca{\'\i}no-Lores, Silvina and Taufer, Michela and Deelman, Ewa},
journal={Concurrency and Computation: Practice and Experience},
volume={35},
number={20},
pages={e7111},
year={2023},
publisher={Wiley Online Library}
}
Online Boosted Gaussian Learners for In-Situ Detection and Characterization of Protein Folding States in Molecular Dynamics Simulations
@inproceedings{sahni2023online,
title={Online Boosted Gaussian Learners for In-Situ Detection and Characterization of Protein
Folding States in Molecular Dynamics Simulations},
author={Sahni, Harshita and Carrillo-Cabada, Hector and Kots, Ekaterina and Caino-Lores, Silvina
and Marquez, Jack and Deelman, Ewa and Cuendet, Michel and Weinstein, Harel and Taufer, Michela
and Estrada, Trilce},
booktitle={2023 IEEE 19th International Conference on e-Science (e-Science)},
pages={1--10},
year={2023},
organization={IEEE}
}
Recognition of Outstanding Future Generation Computer Systems Reviewers for 2022
@misc{taufer2023recognition,
title={Recognition of Outstanding Future Generation Computer Systems Reviewers for 2022},
author={Taufer, Michela},
year={2023}
}
Building Trust in Earth Science Findings through Data Traceability and Results Explainability
@article{olaya2022building,
title={Building trust in earth science findings through data traceability and results
explainability},
author={Olaya, Paula and Kennedy, Dominic and Llamas, Ricardo and Valera, Leobardo and Vargas,
Rodrigo and Lofstead, Jay and Taufer, Michela},
journal={IEEE Transactions on Parallel and Distributed Systems},
volume={34},
number={2},
pages={704--717},
year={2022},
publisher={IEEE}
}
Performance Assessment of Ensembles of In Situ Workflows under Resource Constraints
@ARTICLE{elsevier-ccpe-tu-2022,
author = {Tu Mai Anh Do, Loïc Pottier, Rafael Ferreira da Silva, Silvina Caíno-Lores, and
Michela Taufer and Ewa Deelman},
journal = {{Journal of Concurrency and Computation: Practice and Experience (CCPE)}},
title = {{Performance Assessment of Ensembles of In Situ Workflows under Resource
Constraints}},
year = {2022},
volume = {},
number = {},
pages = {},
note = {{\it (Accepted)}},
}
Apex Predator Nematodes and Meso-Predator Bacteria Consume Their Basal Insect Prey through Discrete Stages of Chemical Transformations (open access)
@article{doi:10.1128/msystems.00312-22,
author = {Nicholas C. Mucci and Katarina A. Jones and Mengyi Cao and Michael R. Wyatt and Shane
Foye and Sarah J. Kauffman and Gregory R. Richards and Michela Taufer and Yoshito Chikaraishi
and Shawn A. Steffan and Shawn R. Campagna and Heidi Goodrich-Blair and Christopher R. Anderton
},
title = {{Apex Predator Nematodes and Meso-Predator Bacteria Consume Their Basal Insect Prey
through Discrete Stages of Chemical Transformations}},
journal = {{mSystems}},
volume = {0},
number = {0},
pages = {e00312-22},
year = {2022},
doi = {10.1128/msystems.00312-22},
}
AI4IO: A Suite of AI-Based Tools for IO-Aware Scheduling
@ARTICLE{sage-ijhpca-wyatt-2022,
author = {Michael R. Wyatt II+, and Stephen Herbein, and Todd Gamblin, and Michela Taufer},
journal = {{International Journal of High Performance Computing Applications (IJHPCA)}},
title = {{AI4IO: A Suite of AI-Based Tools for IO-Aware Scheduling}},
year = {2022},
volume = {36},
number = {3},
pages = {370-387},
doi = {10.1177/10943420221079765},
}
High Frequency Accuracy and Loss Data of Random Neural Networks Trained on Image Datasets (open access)
@article{rorabaugh2022highfrequency,
author = {Ariel Keller Rorabaugh and Silvina Caíno-Lores and Travis Johnston and Michela
Taufer},
title = {{High frequency accuracy and loss data of random neural networks trained on image
datasets}},
journal = {Data in Brief},
volume = {40},
pages = {107780},
year = {2022},
issn = {2352-3409},
doi = {10.1016/j.dib.2021.107780},
url = {https://doi.org/10.1016/j.dib.2021.107780},
}
Building High-throughput Neural Architecture Search Workflows via a Decoupled Fitness Prediction Engine (open access)
@ARTICLE{9674227,
author={Keller Rorabaugh, Ariel and Caíno-Lores, Silvina and Johnston, Travis and Taufer,
Michela},
journal={{IEEE Transactions on Parallel and Distributed Systems}},
title={{Building High-Throughput Neural Architecture Search Workflows via a Decoupled Fitness
Prediction Engine}},
year={2022},
volume={33},
number={11},
pages={2913-2926},
doi={10.1109/TPDS.2022.3140681}}
An Analytical Performance Model of Generalized Multi-Level Scheduling
@ARTICLE{sage-ijhpca-herbein-2022,
author = {S. Herbein and T. Patki and D. H. Ahn and S. Mobo and C. Hathaway and S. Caíno-Lores
and J. Corbett and D. Domyancic and T. R. W. Scogland and B. R. de Supinski and M. Taufer},
journal = {{International Journal of High Performance Computing Applications (IJHPCA)}},
title = {{An Analytical Performance Model of Generalized Multi-Level Scheduling}},
year = {2022},
volume = {36},
number = {3},
pages = {289-306},
doi = {10.1177/10943420211051039},
}
VPIC 2.0: Next Generation Particle-in-Cell Simulations (open access)
@ARTICLE {bird2022vpic,
author = {R. Bird and N. Tan and S. V. Luedtke and S. Harrell and M. Taufer and B.
Albright},
journal = {{IEEE Transactions on Parallel & Distributed Systems}},
title = {{VPIC 2.0: Next Generation Particle-in-Cell Simulations}},
year = {2022},
volume = {33},
number = {04},
issn = {1558-2183},
pages = {952-963},
doi = {10.1109/TPDS.2021.3084795},
publisher = {IEEE Computer Society},
month = {apr}
}
ANACIN-X: A Software Framework for Studying Non-Determinism in MPI Applications (open access)
@article{bell2021anacinx,
author = {Patrick Bell and Kae Suarez and Dylan Chapp and Nigel Tan and Sanjukta Bhowmick and
Michela Taufer},
title = {{ANACIN-X: A software framework for studying non-determinism in MPI applications}},
journal = {Software Impacts},
volume = {10},
pages = {100151},
year = {2021},
issn = {2665-9638},
doi = {10.1016/j.simpa.2021.100151},
url = {https://doi.org/10.1016/j.simpa.2021.100151},
}
Reproducing GW150914: The First Observation of Gravitational Waves From a Binary Black Hole Merger
@ARTICLE {brown2021reproducing,
author = {D. A. Brown and K. Vahi and M. Taufer and V. Welch and E. Deelman},
journal = {{Computing in Science & Engineering}},
title = {{Reproducing GW150914: The First Observation of Gravitational Waves From a Binary Black
Hole Merger}},
year = {2021},
volume = {23},
number = {02},
issn = {1558-366X},
pages = {73-82},
doi = {10.1109/MCSE.2021.3059232},
publisher = {IEEE Computer Society},
month = {mar}
}
A Lightweight Method for Evaluating in situ Workflow Efficiency
@article{do2021lightweight,
title={{A lightweight method for evaluating in situ workflow efficiency}},
author={Tu Mai Anh Do and Lo{\"i}c Pottier and Silvina Ca{\'i}no-Lores and Rafael Ferreira da
Silva and Michel A. Cuendet and Harel Weinstein and Trilce Estrada and Michela Taufer and Ewa
Deelman},
journal={{J. Comput. Sci.}},
year={2021},
volume={48},
pages={101259}
}
A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes
@ARTICLE {carrillocabada2021graphic,
author = {H. Carrillo-Cabada and J. Benson and A. M. Razavi and B. Mulligan and M. A. Cuendet
and H. Weinstein and M. Taufer and T. Estrada},
journal = {{IEEE/ACM Transactions on Computational Biology and Bioinformatics}},
title = {{A Graphic Encoding Method for Quantitative Classification of Protein Structure and
Representation of Conformational Changes}},
year = {2021},
volume = {18},
number = {04},
issn = {1557-9964},
pages = {1336-1349},
doi = {10.1109/TCBB.2019.2945291},
publisher = {IEEE Computer Society},
month = {jul}
}
Identifying Degree and Sources of Non-Determinism in MPI Applications Via Graph Kernels (open access)
Gap-Free Global Annual Soil Moisture: 15km Grids for 1991-2018 (open access)
Flux: Overcoming Scheduling Challenges for Exascale Workflows
Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture Based on Geostatistical Techniques and Multiple Regression
@article{llamas2020spatial,
title={{Spatial gap-filling of ESA CCI satellite-derived soil moisture based on geostatistical
techniques and multiple regression}},
author={Llamas, Ricardo M and Guevara, Mario and Rorabaugh, Danny and Taufer, Michela and
Vargas, Rodrigo},
journal={Remote Sensing},
volume={12},
number={4},
pages={665},
year={2020},
publisher={Multidisciplinary Digital Publishing Institute}
}
Memory-Efficient and Skew-Tolerant MapReduce over MPI for Supercomputing Systems
A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes
Building a Vision for Reproducibility in the Cyberinfrastructure Ecosystem: Leveraging Community Efforts
A Survey of Algorithms for Transforming Molecular Dynamics Data into Metadata for In Situ Analytics based on Machine Learning Methods
A Three-phase Workflow for General and Expressive Representations of Nondeterminism in HPC Applications
Creating a Portable, High-Level Graph Analytics Framework for Compute and Data-Intensive Applications
Spatial Gap-Filling of ESA CCI Satellite-Derived Soil Moisture based on Linear Geostatistics
The Future of Scientific Workflows
Record-and-Replay Techniques for HPC Systems: A survey
In-Situ Data Analytics and Indexing of Protein Trajectories
Enabling Scalable and Accurate Clustering of Distributed Ligand Geometries on Supercomputers
The Future of Scientific Workflows
Creating a Portable, High-Level Graph Analytics Framework For Compute and Data-Intensive Applications
Enhancing Reproducibility for Computational Methods - Data, code and workflows should be available and cited
Performance Characterization of Irregular I/O at the Extreme Scale
It-Situ Data Analysis of Protein Folding Trajectories
Scheduling DAG-based Workflows on Single Cloud Instances: High- performance and Cost Effectiveness with a Static Scheduler
Free Energetics of Carbon Nanotube Association in Aqueous Inorganic NaI Salt Solutions: Temperature Effects using All-Atom Molecular Dynamics Simulations and High-Performance Graphical Processing Unit Based Resources
Pursuing Resource Utilization and Coordinated Progression in GPU-enabled Molecular Simulations
MEMS Accelerometers and Distributed Sensing for Rapid Earthquake Characterization
On the Powerful Use of Simulations in the Quake-Catcher Network to Efficiently Position Low-cost Earthquake Sensors
Enhancement of Accuracy and Efficiency for RNA Secondary Structure Prediction by Sequence Segmentation and MapReduce
GPU enabled Macromolecular Simulation: Challenges and Opportunities
A Scalable and Accurate Method for Classifying Protein-Ligand Binding Geometries using a MapReduce Approach
Hierarchical Fractional-step Approximations and Parallel Kinetic Monte Carlo Algorithms
Structural, Dynamic, and Electrostatic Properties of Fully Hydrated DMPC Bilayers from Molecular Dynamics Simulations Accelerated with Graphical Processing Units (GPUs)
Evaluation of Several Two-Step Scoring Functions Based on Linear Interaction Energy, Effective Ligand Size, and Empirical Pair Potentials for Prediction of Protein-Ligand Binding Geometry and Free Energy
Molecular Dynamics Simulations of Aqueous Ions at the Liquid-Vapor Interface Accelerated Using Graphics Processors
A 3 Terminal Stem-loop Structure in Nodamura Virus RNA2 Forms an Essential Cis-acting Signal for RNA replication
Performance Prediction and Analysis of BOINC Projects: An Empirical Study with EmBOINC
Computational Multi-Scale Modeling in Protein-Ligand Docking
PseudoBase++: An Extension of PseudoBase for Easy Searching, Formatting, and Visualization of Pseudoknots
RNAVLab: A Virtual Laboratory for Studying RNA Secondary Structures based on Grid Computing Technology. Journal of Parallel Computing
A Distributed Evolutionary Method to Design Scheduling Policies for Volunteer Computing
Integrate GridFTP into Firefox - Build grid protocols into Mozilla-based tools
Predictor@Home: A Protein Structure Prediction Supercomputer Based on Global Computing
Study of an Accurate and Fast Protein-Ligand Docking Algorithm based on Molecular Dynamics
a Performance Monitoring Tool for Sandbox-based Desktop Grid Platforms
The Computational Chemistry Prototyping Environment
Book Chapters (Top)
Data Movement in Data-Intensive High Performance Computing
Scheduling on Large Scale Volatile Desktop Grids, from Greedy and Naive to Intelligent and Adaptive Policies
Protein Docking
A Protein Structure Prediction Supercomputer Based on Volunteer Computing
Research Papers in Refereed Conferences, Symposiums, and Workshops (Top)
Enabling Call Path Querying in Hatchet to Identify Performance Bottlenecks in Scientific Applications
@inproceedings{ian_escience22,
author = {Ian Lumsden and
Jakob Luettgau and
Vanessa Lama and
Connor Scully-Allison and
Stephanie Brink and
Katherine E. Isaacs and
Olga Pearce and
{\bf Michela Taufer}},
title = {{Enabling Call Path Querying in Hatchet to Identify Performance Bottlenecks in
Scientific Applications}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--10},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {{IEEE} Computer Society},
}
Identifying Structural Properties of Proteins from X-ray Free Electron Laser Diffraction Patterns
@inproceedings{polaya_escience22,
author = {Paula Olaya and
Silvina Caino-Lores and
Vanessa Lama and
Ria Patel and
Ariel Keller Rorabaugh and
Osamu Miyashita and
Florence Tama and
{\bf Michela Taufer}},
title = {{Identifying Structural Properties of Proteins from X-ray Free Electron Laser
Diffraction Patterns}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--10},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {{IEEE} Computer Society},
}
Augmenting Singularity to Generate Fine-grained Workflows, Record Trails, and Data Provenance
@inproceedings{domenic_escience22,
author = {Kennedy, Dominic and Olaya, Paula and Lofstead, Jay and Vargas, Rodrigo and Taufer,
Michela},
title = {{Augmenting Singularity to Generate Fine-grained Workflows, Record Trails, and Data
Provenance}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--2},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {IEEE Computer Society},
note = {{\it (Short paper)}},
}
Ubique: A New Model for Untangling Inter-task Data Dependence in Complex HPC Workflows
@inproceedings{yeom_escience22,
author = {Yeom, Jae-Seung and Ahn, Dong H. and Lumsden, Ian and Luettgau, Jakob and Caino-Lores,
Silvina and Taufer, Michela},
title = {{Ubique: A New Model for Untangling Inter-task Data Dependence in Complex HPC
Workflows}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--2},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {IEEE Computer Society},
note = {{\it (Short paper)}},
}
The Materials Commons Data Repository
@inproceedings{glenn_escience22,
author = {Tarcea, Glenn and Puchala, Brian and Berman, Tracy and Scorzelli, Giorgio and
Pascucci, Valerio and Taufer, Michela and Allison, John},
title = {{The Materials Commons Data Repository}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--2},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {IEEE Computer Society},
note = {{\it (Short paper)}},
}
A Methodology to Generate Efficient Neural Networks for Classification of Scientific Datasets
@inproceedings{ria_escience22,
author = {Patel, Ria and Rorabaugh, Ariel Keller and Olaya, Paula and Caino-Lores, Silvina and
Channing, Georgia and Schuman, Catherine and Miyashita, Osamu and Tama, Florence and Taufer,
Michela},
title = {{A Methodology to Generate Efficient Neural Networks for Classification of Scientific
Datasets}},
booktitle = {Proceedings of the 18th IEEE International Conference on e-Science (eScience)},
pages = {1--2},
address = {Salt Lake City, Utah, USA},
date = {October 10-14, 2022},
year = {2022},
publisher = {IEEE Computer Society},
note = {{\it (Short paper)}},
}
NSDF-FUSE: A Testbed for Studying Object Storage via FUSE File Systems
@inproceedings{DBLP:conf/cluster/OlayaHPDC22,
author = { Paula Olaya and Jakob Luettgau and Naweiluo Zhou and Giorgio Scorzelli and Jay
Lofstead and Valerio Pascucci and {\bf Michela Taufer} },
title = {{NSDF-FUSE: A Testbed for Studying Object Storage via FUSE File Systems}},
booktitle = {Proceedings of the 31st International ACM Symposium on High-Performance Parallel
and Distributed Computing (HPDC)},
publisher = {{IEEE} Computer Society},
pages = {1--2},
address = {Minneapolis, Minnesota},
month = {June},
year = {2022},
note = {{\it (Short paper)}},
}
NSDF-Cloud: Enabling Ad-Hoc Compute Clusters Across Academic and Commercial Clouds
@inproceedings{DBLP:conf/cluster/LuettgauHPDC22,
author = { Jakob Luettgau and Paula Olaya and Naweiluo Zhou and Giorgio Scorzelli and Valerio
Pascucci and Michela Taufer},
title = {{NSDF-Cloud: Enabling Ad-Hoc Compute Clusters Across Academic and Commercial
Clouds}},
booktitle = {Proceedings of the 31st International ACM Symposium on High-Performance Parallel
and Distributed Computing (HPDC)},
publisher = {{ACM}},
pages = {1--2},
address = {Minneapolis, Minnesota},
month = {June},
year = {2022},
note = {{\it (Short paper)}},
}
A Roadmap to Robust Science for High-throughput Applications: The Developers’ Perspective
@INPROCEEDINGS {taufer2021roadmapdevelopers,
author = {M. Taufer and E. Deelman and R. Silva and T. Estrada and M. Hall and M. Livny},
booktitle = {{2021 IEEE International Conference on Cluster Computing (CLUSTER)}},
title = {{A Roadmap to Robust Science for High-throughput Applications: The Developers'
Perspective}},
year = {2021},
pages = {807-808},
doi = {10.1109/Cluster48925.2021.00068},
url = {https://doi.ieeecomputersociety.org/10.1109/Cluster48925.2021.00068},
publisher = {{IEEE} Computer Society},
month = {sep}
}
A Case Study in Scientific Reproducibility from the Event Horizon Telescope (EHT)
@INPROCEEDINGS{ketron2021casestudy,
author={Ketron, R. and Leonard, J. and Roachell, B. and Patel, R. and White, R. and Caíno-Lores,
S. and Tan, N. and Miles, P. and Vahi, K. and Deelman, E. and Brown, D. and Taufer, M.},
booktitle={{2021 IEEE 17th International Conference on eScience (eScience)}},
title={{A Case Study in Scientific Reproducibility from the Event Horizon Telescope (EHT)}}
,
year={2021},
pages={249-250},
doi={10.1109/eScience51609.2021.00045}
}
A Roadmap to Robust Science for High-throughput Applications: The Scientists’ Perspective
@INPROCEEDINGS{taufer2021roadmapscientists,
author={Taufer, M. and Deelman, E. and da Silva, R. Ferreira and Estrada, T. and Hall, M.},
booktitle={{2021 IEEE 17th International Conference on eScience (eScience)}},
title={{A Roadmap to Robust Science for High-throughput Applications: The Scientists’
Perspective}},
year={2021},
pages={247-248},
doi={10.1109/eScience51609.2021.00044}
}
Assessing Resource Provisioning and Allocation of Ensembles of In Situ Workflows
@inproceedings{do2021assessing,
author = {Do, Tu Mai Anh and Pottier, Lo\"{\i}c and Ferreira da Silva, Rafael and
Ca\'{\i}no-Lores, Silvina and Taufer, Michela and Deelman, Ewa},
title = {{Assessing Resource Provisioning and Allocation of Ensembles of In Situ
Workflows}},
year = {2021},
isbn = {9781450384414},
publisher = {Association for Computing Machinery},
url = {https://doi.org/10.1145/3458744.3474051},
doi = {10.1145/3458744.3474051},
booktitle = {{50th International Conference on Parallel Processing Workshop}},
articleno = {38},
numpages = {10},
}
Optimize Memory Usage in Vector Particle-In-Cell (VPIC) to Break the 10 Trillion Particle Barrier in Plasma Simulations
@inproceedings{Tan2021OptimizeMU,
title={{Optimize Memory Usage in Vector Particle-In-Cell (VPIC) to Break the 10 Trillion
Particle Barrier in Plasma Simulations}},
author={Nigel Tan and Robert Francis Bird and Guangye Chen and Michela Taufer},
booktitle={{ICCS}},
year={2021}
}