References

This is a list of publications closely related to the JLESC. Please feel free to add any missing publications through a pull request on GitHub.



If you publish something during your work within JLESC, please acknowledge JLESC support e.g. via “This research is partially supported by the NCSA-Inria-ANL-BSC-JSC-Riken-UTK Joint-Laboratory for Extreme Scale Computing (JLESC, https://jlesc.github.io/).”

BibTeX

  1. Bouvier, Thomas, Bogdan Nicolae, Hugo Chaugier, Alexandru Costan, Ian Foster, and Gabriel Antoniu. 2024. “Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal Buffers.” In CCGrid 2024 - IEEE 24th International Symposium on Cluster, Cloud and Internet Computing, 1–10. Philadelphia (PA), United States. https://doi.org/10.1109/CCGrid59990.2024.00036. 
    @inproceedings{bouvierEtAl2024,  address = {Philadelphia (PA), United States},  author = {Bouvier, Thomas and Nicolae, Bogdan and Chaugier, Hugo and Costan, Alexandru and Foster, Ian and Antoniu, Gabriel},  booktitle = {{CCGrid 2024 - IEEE 24th International Symposium on Cluster, Cloud and Internet      Computing}},  doi = {10.1109/CCGrid59990.2024.00036},  hal_id = {hal-04600107},  hal_version = {v1},  keywords = {continual learning ; data-parallel training ; experience replay ; distributed      rehearsal buffers ; asynchronous data management ; scalability},  month = may,  pages = {1-10},  pdf = {https://inria.hal.science/hal-04600107/file/paper.pdf},  title = {{Efficient Data-Parallel Continual Learning with Asynchronous Distributed Rehearsal      Buffers}},  url = {https://inria.hal.science/hal-04600107},  year = {2024}}
  2. Bouvier, Thomas, Bogdan Nicolae, Alexandru Costan, Tekin Bicer, Ian Foster, and Gabriel Antoniu. 2024. “Efficient Distributed Continual Learning for Steering Experiments in Real-Time.” Future Generation Computer Systems, July. https://doi.org/10.1016/j.future.2024.07.016. 
    @article{bouvierEtAl2024b,  author = {Bouvier, Thomas and Nicolae, Bogdan and Costan, Alexandru and Bicer, Tekin and Foster, Ian and Antoniu, Gabriel},  doi = {10.1016/j.future.2024.07.016},  hal_id = {hal-04664176},  hal_version = {v2},  journal = {{Future Generation Computer Systems}},  keywords = {continual learning ; data-parallel training ; experience replay ; distributed      rehearsal buffers ; asynchronous data management ; scalability ; streaming ; generative AI},  month = jul,  pdf = {https://inria.hal.science/hal-04664176v2/file/paper.pdf},  publisher = {{Elsevier}},  title = {{Efficient Distributed Continual Learning for Steering Experiments in Real-Time}},  url = {https://inria.hal.science/hal-04664176},  year = {2024}}
  3. Rudi, Johann, Youngjun Lee, Aidan H. Chadha, Mohamed Wahib, Klaus Weide, Jared P. O’Neal, and Anshu Dubey. 2024. “CG-Kit: Code Generation Toolkit for Performant and Maintainable Variants of Source Code Applied to Flash-X Hydrodynamics Simulations.” 
    @misc{rudi2024cgkit,  title = {CG-Kit: Code Generation Toolkit for Performant and Maintainable Variants of Source Code Applied to Flash-X Hydrodynamics Simulations},  author = {Rudi, Johann and Lee, Youngjun and Chadha, Aidan H. and Wahib, Mohamed and Weide, Klaus and O'Neal, Jared P. and Dubey, Anshu},  year = {2024},  eprint = {2401.03378},  archiveprefix = {arXiv},  note = {submitted to FGCS},  primaryclass = {cs.DC}}
  4. Gaikwad, Shreyas Sunil, Sri Hari Krishna Narayanan, Laurent Hascoet, Jean-Michel Campin, Helen Pillar, An Nguyen, Jan Hückelheim, Paul Hovland, and Patrick Heimbach. 2024. “MITgcm-AD v2: Open Source Tangent Linear and Adjoint Modeling Framework for the Oceans and Atmosphere Enabled by the Automatic Differentiation Tool Tapenade.” ArXiv e-Prints, January, arXiv:2401.11952. https://doi.org/10.48550/arXiv.2401.11952. 
    @article{GaikwadEtAl2024,  author = {{Gaikwad}, Shreyas Sunil and {Krishna Narayanan}, Sri Hari and {Hascoet}, Laurent and {Campin}, Jean-Michel and {Pillar}, Helen and {Nguyen}, An and {H{\"u}ckelheim}, Jan and {Hovland}, Paul and {Heimbach}, Patrick},  title = {{{MITgcm-AD} v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade}},  journal = {arXiv e-prints},  keywords = {Physics - Atmospheric and Oceanic Physics},  year = {2024},  month = jan,  eid = {arXiv:2401.11952},  pages = {arXiv:2401.11952},  doi = {10.48550/arXiv.2401.11952},  archiveprefix = {arXiv},  eprint = {2401.11952},  primaryclass = {physics.ao-ph}}
  5. 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. 2023. “Scalable Incremental Checkpointing Using GPU-Accelerated De-Duplication.” In Proceedings of the 52nd International Conference on Parallel Processing, 665–74. ICPP ’23. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3605573.3605639. 
    @inproceedings{TanEtAl2023,  address = {New York, NY, USA},  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}},  doi = {10.1145/3605573.3605639},  isbn = {9798400708435},  keywords = {incremental storage, de-duplication, data versioning, GPU parallelization, Checkpointing},  location = {Salt Lake City, UT, USA},  numpages = {10},  pages = {665–674},  publisher = {{Association for Computing Machinery}},  series = {ICPP '23},  title = {{Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication}},  url = {https://doi.org/10.1145/3605573.3605639},  year = {2023}}
  6. 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. 2023. “Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification.” In Proceedings of the 52nd International Conference on Parallel Processing, 1. ICPP ’23. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3605573.3605636. 
    @inproceedings{ChanningEtAl2023,  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}},  title = {{Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification}},  year = {2023},  isbn = {9798400708435},  publisher = {{Association for Computing Machinery}},  address = {New York, NY, USA},  url = {https://doi.org/10.1145/3605573.3605636},  doi = {10.1145/3605573.3605636},  booktitle = {{Proceedings of the 52nd International Conference on Parallel Processing}},  pages = {1},  numpages = {1},  keywords = {Deep learning, Early termination, Neural architecture search, Neural networks, Predictive modeling, Protein diffraction},  location = {Salt Lake City, UT, USA},  series = {ICPP '23}}
  7. Rosendo, Daniel, Kate Keahey, Alexandru Costan, Matthieu Simonin, Patrick Valduriez, and Gabriel Antoniu. 2023. “KheOps: Cost-Effective Repeatability, Reproducibility, and Replicability of Edge-to-Cloud Experiments.” In Proceedings of the 2023 ACM Conference on Reproducibility and Replicability, 62–73. ACM REP ’23. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3589806.3600032. 
    @inproceedings{RosendoEtAl2023,  author = {Rosendo, Daniel and Keahey, Kate and Costan, Alexandru and Simonin, Matthieu and Valduriez, Patrick and Antoniu, Gabriel},  title = {KheOps: Cost-effective Repeatability, Reproducibility, and Replicability of Edge-to-Cloud Experiments},  year = {2023},  isbn = {9798400701764},  publisher = {Association for Computing Machinery},  address = {New York, NY, USA},  url = {https://doi.org/10.1145/3589806.3600032},  doi = {10.1145/3589806.3600032},  booktitle = {Proceedings of the 2023 ACM Conference on Reproducibility and Replicability},  pages = {62–73},  numpages = {12},  keywords = {Workflows, Reproducibility, Replicability, Repeatability, Edge Computing, Computing Continuum, Cloud Computing},  location = {Santa Cruz, CA, USA},  series = {ACM REP '23}}
  8. Barbut, Quentin, Anne Benoit, Thomas Herault, Yves Robert, and Frédéric Vivien. 2023. “When to Checkpoint at the End of a Fixed-Length Reservation?” In Proceedings of Fault Tolerance for HPC at EXtreme Scales (FTXS) Workshop. https://inria.hal.science/hal-04215554. 
    @inproceedings{BarbutEtAl2023,  author = {Barbut, Quentin and Benoit, Anne and Herault, Thomas and Robert, Yves and Vivien, Frédéric},  title = {When to checkpoint at the end of a fixed-length reservation?},  booktitle = {Proceedings of Fault Tolerance for HPC at eXtreme Scales (FTXS) Workshop},  url = {https://inria.hal.science/hal-04215554},  location = {Denver, United States},  date = {2023-11-12},  year = {2023}}
  9. Yoshii, Kazutomo, John Tramm, Bryce Allen, Tomohiro Ueno, Kentaro Sano, Andrew Siegel, and Pete Beckman. 2023. “Hardware Specialization: Estimating Monte Carlo Cross-Section Lookup Kernel Performance and Area.” In Proceedings of the SC’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 1274–78. 
    @inproceedings{yoshii2023hardware,  title = {Hardware specialization: Estimating Monte Carlo cross-section lookup kernel performance and area},  author = {Yoshii, Kazutomo and Tramm, John and Allen, Bryce and Ueno, Tomohiro and Sano, Kentaro and Siegel, Andrew and Beckman, Pete},  booktitle = {Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis},  pages = {1274--1278},  year = {2023}}
  10. Yoshii, Kazutomo, Tomohiro Ueno, Kentaro Sano, Antonino Miceli, and Franck Cappello. 2023. “Streaming Hardware Compressor Generator Framework.” In Proceedings of the SC’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, 289–97. 
    @inproceedings{yoshii2023streaming,  title = {Streaming Hardware Compressor Generator Framework},  author = {Yoshii, Kazutomo and Ueno, Tomohiro and Sano, Kentaro and Miceli, Antonino and Cappello, Franck},  booktitle = {Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis},  pages = {289--297},  year = {2023}}
  11. Mateevitsi, Victor A., Mathis Bode, Nicola Ferrier, Paul Fischer, Jens Henrik Göbbert, Joseph A. Insley, Yu-Hsiang Lan, et al. 2023. “Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS Using SENSEI.” In Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (SC-W 2023). https://doi.org/10.1145/3624062.3624159. 
    @inproceedings{MateevitsiEtAl2023,  author = {Mateevitsi, Victor A. and Bode, Mathis and Ferrier, Nicola and Fischer, Paul and G{\"{o}}bbert, Jens Henrik and Insley, Joseph A. and Lan, Yu-Hsiang and Min, Misun and Papka, Michael E. and Patel, Saumil and Rizzi, Silvio and Windgassen, Jonathan},  booktitle = {Workshops of The International Conference on High Performance Computing, Network,    Storage, and Analysis (SC-W 2023)},  title = {{Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEI}},  year = {2023},  doi = {10.1145/3624062.3624159}}
  12. “ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography.” 2023. Synchrotron Radiation News 36 (4): 17–22. https://doi.org/10.1080/08940886.2023.2245722. 
    @article{UnderwoodEtAl2023,  author = {},  title = {ROIBIN-SZ: Fast and Science-Preserving Compression for Serial Crystallography},  journal = {Synchrotron Radiation News},  volume = {36},  number = {4},  pages = {17-22},  year = {2023},  publisher = {Taylor & Francis},  doi = {10.1080/08940886.2023.2245722},  url = {https://doi.org/10.1080/08940886.2023.2245722},  eprint = {https://doi.org/10.1080/08940886.2023.2245722}}
  13. “Integrating TEZip into LibPressio: A Acase Study of Integrating a Dynamic Application into a Static C Envionment.” 2023. 
    @misc{TalukdarEtAl2023,  author = {},  title = {Integrating TEZip into LibPressio: A Acase Study of Integrating a Dynamic Application into a Static C Envionment},  year = {2023}}
  14. Peterka, Tom, Dmitriy Morozov, Arnur Nigmetov, Orcun Yildiz, Bogdan Nicolae, and Philip E Davis. 2023. “LowFive: In Situ Data Transport for High-Performance Workflows.” In IPDPS’23: The 37th IEEE International Parallel and Distributed Processing Symposium. 
    @inproceedings{peterka2023lowfive,  title = {LowFive: In Situ Data Transport for High-Performance Workflows},  author = {Peterka, Tom and Morozov, Dmitriy and Nigmetov, Arnur and Yildiz, Orcun and Nicolae, Bogdan and Davis, Philip E},  booktitle = {IPDPS'23: The 37th IEEE International Parallel and Distributed Processing Symposium},  year = {2023}}
  15. O’Neal, Jared, Mohamed Wahib, Anshu Dubey, Klaus Weide, Tom Klosterman, and Johann Rudi. 2022. “Domain-Specific Runtime to Orchestrate Computation on Heterogeneous Platforms.” In European Conference on Parallel Processing, 154–65. Springer, Cham. 
    @inproceedings{onealEtAl2022,  title = {Domain-specific runtime to orchestrate computation on heterogeneous platforms},  author = {O’Neal, Jared and Wahib, Mohamed and Dubey, Anshu and Weide, Klaus and Klosterman, Tom and Rudi, Johann},  booktitle = {European Conference on Parallel Processing},  pages = {154--165},  year = {2022},  organization = {Springer, Cham}}
  16. Dubey, Anshu, Klaus Weide, Jared O’Neal, Akash Dhruv, Sean Couch, J Austin Harris, Tom Klosterman, et al. 2022. “Flash-X: A Multiphysics Simulation Software Instrument.” SoftwareX 19: 101168. 
    @article{dubeyEtAl2022,  title = {Flash-X: A multiphysics simulation software instrument},  author = {Dubey, Anshu and Weide, Klaus and O’Neal, Jared and Dhruv, Akash and Couch, Sean and Harris, J Austin and Klosterman, Tom and Jain, Rajeev and Rudi, Johann and Messer, Bronson and others},  journal = {SoftwareX},  volume = {19},  pages = {101168},  year = {2022},  publisher = {Elsevier}}
  17. Denoyelle, Nicolas, Swann Perarnau, Kamil Iskra, and Balazs Gerofi. 2022. “Rapid Execution Time Estimation for Heterogeneous Memory Systems Through Differential Tracing.” In High Performance Computing. Springer International Publishing. 
    @inproceedings{denoyelle2022isc,  author = {Denoyelle, Nicolas and Perarnau, Swann and Iskra, Kamil and Gerofi, Balazs},  title = {Rapid Execution Time Estimation for Heterogeneous Memory Systems  	  Through Differential Tracing},  booktitle = {High Performance Computing},  year = {2022},  publisher = {Springer International Publishing}}
  18. Hawila, Ismail, Sophie Cerf, Raphaël Bleuse, Swann Perarnau, and Éric Rutten. 2022. “Adaptive Power Control for Sober High-Performance Computing.” In 6th IEEE Conference on Control Technology and Applications. IEEE. 
    @inproceedings{hawila2022ccta,  author = {Hawila, Ismail and Cerf, Sophie and Bleuse, Rapha{\"e}l and Perarnau, Swann and Rutten, {\'E}ric},  booktitle = {6th IEEE Conference on Control Technology and Applications},  title = {Adaptive Power Control for Sober High-Performance Computing},  year = {2022},  publisher = {IEEE}}
  19. Rüttgers, Mario, Moritz Waldmann, Wolfgang Schröder, and Andreas Lintermann. 2022. “A Machine-Learning-Based Method for Automatizing Lattice-Boltzmann Simulations of Respiratory Flows.” Applied Intelligence, no. first online (January). https://doi.org/10.1007/s10489-021-02808-2. 
    @article{Ruttgers2022APIN,  author = {R{\"{u}}ttgers, Mario and Waldmann, Moritz and Schr{\"{o}}der, Wolfgang and Lintermann, Andreas},  doi = {10.1007/s10489-021-02808-2},  issn = {0924-669X},  journal = {Applied Intelligence},  month = jan,  number = {first online},  title = {{A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows}},  url = {https://link.springer.com/10.1007/s10489-021-02808-2},  year = {2022}}
  20. Hückelheim, Jan, and Laurent Hascoët. 2022. “Source-to-Source Automatic Differentiation of OpenMP Parallel Loops.” ACM Trans. Math. Softw. 48 (1). https://doi.org/10.1145/3472796. 
    @article{HuckelheimHascoet2022,  author = {H\"{u}ckelheim, Jan and Hasco\"{e}t, Laurent},  title = {Source-to-Source Automatic Differentiation of OpenMP Parallel Loops},  year = {2022},  issue_date = {March 2022},  publisher = {Association for Computing Machinery},  address = {New York, NY, USA},  volume = {48},  number = {1},  issn = {0098-3500},  url = {https://doi.org/10.1145/3472796},  doi = {10.1145/3472796},  journal = {ACM Trans. Math. Softw.},  month = feb,  articleno = {7},  numpages = {32},  keywords = {Automatic differentiation, OpenMP, shared-memory parallel, multicore}}
    This article presents our work toward correct and efficient automatic differentiation of OpenMP parallel worksharing loops in forward and reverse mode. Automatic differentiation is a method to obtain gradients of numerical programs, which are crucial in optimization, uncertainty quantification, and machine learning. The computational cost to compute gradients is a common bottleneck in practice. For applications that are parallelized for multicore CPUs or GPUs using OpenMP, one also wishes to compute the gradients in parallel. We propose a framework to reason about the correctness of the generated derivative code, from which we justify our OpenMP extension to the differentiation model. We implement this model in the automatic differentiation tool Tapenade and present test cases that are differentiated following our extended differentiation procedure. Performance of the generated derivative programs in forward and reverse mode is better than sequential, although our reverse mode often scales worse than the input programs.
  21. ———. 2022. “POSTER: Automatic Differentiation of Parallel Loops with Formal Methods.” In Principles and Practice of Parallel Programming (PPoPP) 2022. 
    @conference{ppopp22-poster-ad-z3,  author = {{J}an {H}\"uckelheim and {L}aurent {H}asco\"et},  booktitle = {Principles and Practice of Parallel Programming (PPoPP) 2022},  date-added = {2022-03-15 08:59:01 -0500},  date-modified = {2022-03-15 09:01:06 -0500},  title = {{POSTER}: Automatic Differentiation of Parallel Loops with Formal Methods},  year = {2022}}
  22. Benoit, Anne, Yishu Du, Thomas Herault, Loris Marchal, Guillaume Pallez, Lucas Perotin, Yves Robert, Hongyang Sun, and Frederic Vivien. 2022. “Checkpointing à La Young/Daly: An Overview.” In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, 701–10. IC3-2022. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3549206.3549328. 
    @inproceedings{BenoitEtAl2022,  author = {Benoit, Anne and Du, Yishu and Herault, Thomas and Marchal, Loris and Pallez, Guillaume and Perotin, Lucas and Robert, Yves and Sun, Hongyang and Vivien, Frederic},  title = {Checkpointing \`{a} La Young/Daly: An Overview},  year = {2022},  isbn = {9781450396752},  publisher = {Association for Computing Machinery},  address = {New York, NY, USA},  url = {https://doi.org/10.1145/3549206.3549328},  doi = {10.1145/3549206.3549328},  booktitle = {Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing},  pages = {701–710},  numpages = {10},  location = {Noida, India},  series = {IC3-2022}}
  23. Bosilca, George, Aurélien Bouteiller, Thomas Herault, Valentin Le Fèvre, Yves Robert, and Jack Dongarra. 2022. “Comparing Distributed Termination Detection Algorithms for Modern HPC Platforms.” Int. J. of Networking and Computing 12 (1): 26–46. 
    @article{BosilcaEtAl2022,  title = {{Comparing distributed termination detection algorithms for modern HPC platforms}},  author = {Bosilca, George and Bouteiller, Aurélien and Herault, Thomas and Fèvre, Valentin Le and Robert, Yves and Dongarra, Jack},  journal = {Int. J. of Networking and Computing},  year = {2022},  volume = {12},  number = {1},  pages = {26-46}}
  24. Du, Yishu, Guillaume Pallez, Loris Marchal, and Yves Robert. 2022. “Optimal Checkpointing Strategies for Iterative Applications.” IEEE Trans. Parallel Distributed Systems 33 (3): 507–22. 
    @article{DuEtAl2022,  author = {Du, Yishu and Pallez, Guillaume and Marchal, Loris and Robert, Yves},  journal = {IEEE Trans. Parallel Distributed Systems},  volume = {33},  pages = {507-522},  title = {Optimal checkpointing strategies for iterative applications},  number = {3},  year = {2022}}
  25. Rosendo, Daniel, Alexandru Costan, Patrick Valduriez, and Gabriel Antoniu. 2022. “Distributed Intelligence on the Edge-to-Cloud Continuum: A Systematic Literature Review.” Journal of Parallel and Distributed Computing. 
    @article{DanielEtAl2022,  title = {Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review},  author = {Rosendo, Daniel and Costan, Alexandru and Valduriez, Patrick and Antoniu, Gabriel},  journal = {Journal of Parallel and Distributed Computing},  year = {2022},  publisher = {Elsevier}}
  26. Olaya, Paula, Silvina Caíno-Lores, Vanessa Lama, Ria Patel, Ariel Keller Rorabaugh, Osamu Miyashita, Florence Tama, and Michela Taufer. 2022. “Identifying Structural Properties of Proteins from X-Ray Free Electron Laser Diffraction Patterns.” In 2022 IEEE 18th International Conference on e-Science (e-Science), 21–31. https://doi.org/10.1109/eScience55777.2022.00017. 
    @inproceedings{OlayaEtAl2022,  author = {Olaya, Paula and Caíno-Lores, Silvina and Lama, Vanessa and Patel, Ria and Rorabaugh, Ariel Keller and Miyashita, Osamu and Tama, Florence and Taufer, Michela},  booktitle = {2022 IEEE 18th International Conference on e-Science (e-Science)},  title = {Identifying Structural Properties of Proteins from X-ray Free Electron Laser Diffraction Patterns},  year = {2022},  volume = {},  number = {},  pages = {21-31},  doi = {10.1109/eScience55777.2022.00017}}
  27. Patel, Ria, Ariel Keller Rorabaugh, Paula Olaya, Silvina Caino-Lores, Georgia Channing, Catherine Schuman, Osamu Miyashita, Florence Tama, and Michela Taufer. 2022. “A Methodology to Generate Efficient Neural Networks for Classification of Scientific Datasets.” In 2022 IEEE 18th International Conference on e-Science (e-Science), 389–90. https://doi.org/10.1109/eScience55777.2022.00052. 
    @inproceedings{PatelEtAl2022,  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},  booktitle = {2022 IEEE 18th International Conference on e-Science (e-Science)},  title = {A Methodology to Generate Efficient Neural Networks for Classification of Scientific Datasets},  year = {2022},  volume = {},  number = {},  pages = {389-390},  doi = {10.1109/eScience55777.2022.00052}}
  28. Underwood, Robert, Victoriana Malvoso, Jon C. Calhoun, Sheng Di, and Franck Cappello. 2021. “Productive and Performant Generic Lossy Data Compression with LibPressio.” In 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7), 1–10. https://doi.org/10.1109/DRBSD754563.2021.00005. 
    @inproceedings{libpressio,  author = {Underwood, Robert and Malvoso, Victoriana and Calhoun, Jon C. and Di, Sheng and Cappello, Franck},  booktitle = {2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7)},  title = {Productive and Performant Generic Lossy Data Compression with LibPressio},  year = {2021},  volume = {},  number = {},  pages = {1-10},  doi = {10.1109/DRBSD754563.2021.00005}}
  29. Ogoke, Francis, Kazem Meidani, Amirreza Hashemi, and Amir Barati Farimani. 2021. “Graph Convolutional Networks Applied to Unstructured Flow Field Data.” Machine Learning: Science and Technology 2 (September). https://doi.org/10.1088/2632-2153/ac1fc9. 
    @article{Ogoke2021,  author = {Ogoke, Francis and Meidani, Kazem and Hashemi, Amirreza and Barati Farimani, Amir},  year = {2021},  month = sep,  pages = {},  title = {Graph Convolutional Networks applied to unstructured flow field data},  volume = {2},  journal = {Machine Learning: Science and Technology},  doi = {10.1088/2632-2153/ac1fc9}}
  30. Yoshii, Kazutomo, Rajesh Sankaran, Sebastian Strempfer, Maksim Levental, Mike Hammer, and Antonino Miceli. 2021. “A Hardware Co-Design Workflow for Scientific Instruments at the Edge.” 
    @misc{yoshii2021hardware,  title = {A Hardware Co-design Workflow for Scientific Instruments at the Edge},  author = {Yoshii, Kazutomo and Sankaran, Rajesh and Strempfer, Sebastian and Levental, Maksim and Hammer, Mike and Miceli, Antonino},  year = {2021},  eprint = {2111.01380},  archiveprefix = {arXiv},  primaryclass = {physics.ins-det}}
  31. Ueno, Tomohiro, Atsushi Koshiba, and Kentaro Sano. 2021. “Virtual Circuit-Switching Network with Flexible Topology for High-Performance FPGA Cluster.” In 2021 IEEE 32nd International Conference on Application-Specific Systems, Architectures and Processors (ASAP), 41–48. IEEE. 
    @inproceedings{ueno2021virtual,  title = {Virtual Circuit-Switching Network with Flexible Topology for High-Performance FPGA Cluster},  author = {Ueno, Tomohiro and Koshiba, Atsushi and Sano, Kentaro},  booktitle = {2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP)},  pages = {41--48},  year = {2021},  organization = {IEEE}}
  32. Cerf, Sophie, Raphaël Bleuse, Valentin Reis, Swann Perarnau, and Éric Rutten. 2021. “Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach.” In Euro-Par 2021: Parallel Processing. Springer International Publishing. https://doi.org/10.1007/978-3-030-85665-6_21. 
    @inproceedings{cerf2021europar,  title = {{Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach}},  author = {Cerf, Sophie and Bleuse, Rapha{\"e}l and Reis, Valentin and Perarnau, Swann and Rutten, {\'E}ric},  booktitle = {Euro-Par 2021: Parallel Processing},  year = {2021},  doi = {10.1007/978-3-030-85665-6_21},  publisher = {Springer International Publishing}}
  33. Rüttgers, Mario, Moritz Waldmann, Wolfgang Schröder, and Andreas Lintermann. 2021. “Machine-Learning-Based Control of Perturbed and Heated Channel Flows.” In High Performance Computing, Proceedings of the 36th International Conference, ISC High Performance 2021, 7–22. Frankfurt/Main, Germany: Springer International Publishing. https://doi.org/10.1007/978-3-030-90539-2_1. 
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