Publications

2024

  1. J. Lukasczyk, M. Will, F. Wetzels, G. H. Weber, and C. Garth, “ExTreeM: Scalable Augmented Merge Tree Computation via Extremum Graphs,” IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE VIS 2023), vol. 30, no. 1, 2024.

2023

  1. L. Zhou, C. Yang, W. Gao, T. Perciano, K. M. Davies, and N. K. Sauter, “A machine learning pipeline for membrane segmentation of cryo-electron tomograms,” Journal of Computational Science, vol. 66, p. 101904, Jan. 2023.

2022

  1. R. Mendoza, M. Nguyen, J. W. Zhu, V. Dumont, T. Perciano, J. Mueller, and V. Ganapati, “A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography,” in Proceedings of the Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS) - Machine Learning and the Physical Sciences Workshop, Dec. 2022. https://ml4physicalsciences.github.io/2022/files/NeurIPS_ML4PS_2022_5.pdf.
  2. G. M. Wallace, Z. Bai, R. Sadre, T. Perciano, N. Bertelli, S. Shiraiwa, E. W. Bethel, and J. C. Wright, “Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive,” Journal of Plasma Physics, vol. 88, no. 4, p. 895880401, Aug. 2022.
  3. M. G. Amankwah, D. Camps, E. W. Bethel, R. Van Beeumen, and T. Perciano, “Quantum pixel representations and compression for N-dimensional images,” Scientific Reports, vol. 12, no. 1, p. 7712, May 2022.
  4. S. Zhang, R. Sadre, B. A. Legg, H. Pyles, T. Perciano, E. W. Bethel, D. Baker, O. Rübel, and J. J. D. Yoreo, “Rotational dynamics and transition mechanisms of surface-adsorbed proteins,” Proceedings of the National Academy of Sciences, vol. 119, no. 16, p. e2020242119, Apr. 2022.
  5. C. Varadharajan, A. Appling, B. Arora, D. Christianson, V. Hendric, V. Kumar, A. Lima, J. Müeller, S. Oliver, M. Ombadi, T. Perciano, J. Sadler, H. Weierbach, J. Willard, Z. Xu, and J. Zwart, “Can machine learning accelerate process understanding and decision-relevant predictions of river water quality?,” Hydrological Processes, vol. 36, no. 4, p. e14565, Apr. 2022.
  6. S. Murugesan, M. Kiran, B. Hamann, and G. H. Weber, “Netostat: Analyzing Dynamic Flow Patterns in High-Speed Networks,” Cluster Computing, Mar. 2022.
  7. M. Avaylon, R. Sadre, Z. Bai, and T. Perciano, “Adaptable Deep Learning and Probabilistic Graphical Model System for Semantic Segmentation,” Advances in Artificial Intelligence and Machine Learning, vol. 2, no. 1, pp. 288–302, Mar. 2022.
  8. P.-T. Bremer, G. Tourassi, W. Bethel, K. Gaither, V. Pascucci, and W. Xu, “Visualization for Scientific Discovery, Decision-Making, and Communication,” in Summary Report from the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication, United States, Jan. 2022. https://www.osti.gov/biblio/1845708.
  9. H. Carr, O. Rübel, G. H. Weber, and J. Ahrens, “Optimization and Augmentation for Data Parallel Contour Trees,” IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 10, pp. 3471–3485, 2022. Published online 2021.

2021

  1. R. Sadre, B. Sundaram, S. Majumdar, and D. Ushizima, “Validating deep learning inference during chest X-ray classification for COVID-19 screening,” Nature Scientific Reports, vol. 11, no. 1, p. 16075, Aug. 2021.
  2. M. M. Noack, P. H. Zwart, D. M. Ushizima, M. Fukuto, K. G. Yager, K. C. Elbert, C. B. Murray, A. Stein, G. S. Doerk, E. R. Tsai, R. Li, G. Freychet, M. Zhernenkov, H.-Y. N. Holman, S. Lee, L. Chen, E. Rotenberg, T. Weber, Y. L. Goc, M. Boehm, P. Steffens, P. Mutti, and J. A. Sethian, “Gaussian processes for autonomous data acquisition at large-scale synchrotron and neutron facilities,” Nature Reviews Physics, Jul. 2021.
  3. M. T. Rezende, R. Silva, F. de O. Bernardo, A. H. G. Tobias, P. H. C. Oliveira, T. M. Machado, C. S. Costa, F. N. S. Medeiros, D. M. Ushizima, C. M. Carneiro, and A. G. C. Bianchi, “CRIC searchable image database as a public platform for conventional pap smear cytology data,” Nature Scientific Data, vol. 8, Jun. 2021.
  4. E. W. Bethel, C. Heinemann, and T. Perciano, “Performance Tradeoffs in Shared-memory Platform Portable Implementations of a Stencil Kernel,” in Eurographics Symposium on Parallel Graphics and Visualization, Zürich, Switzerland, Jun. 2021.
  5. H. A. Carr, G. H. Weber, C. M. Sewell, O. Rübel, P. Fasel, and J. P. Ahrens, “Scalable Contour Tree Computation by Data Parallel Peak Pruning,” IEEE Transactions on Visualization and Computer Graphics, vol. 27, no. 4, pp. 2437–2454, Apr. 2021. (Published online 2019).
  6. A. S. Krishnapriyan, J. Montoya, M. Haranczyk, J. Hummelshøj, and D. Morozov, “Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks,” Scientific reports, vol. 11, no. 1, pp. 1–11, Apr. 2021.
  7. O. Rübel, A. J. Tritt, R. Ly, B. K. Dichter, S. S. Ghosh, L. Niu, I. Soltesz, K. Svoboda, L. M. Frank, and K. Bouchard, “The Neurodata Without Borders ecosystem for neurophysiological data science,” bioRxiv, Mar. 2021. (preprint).
  8. K. Xu, A. S. Tremsin, J. Li, D. M. Ushizima, C. A. Davy, A. Bouterf, Y. T. Su, M. Marroccoli, A. M. Mauro, M. Osanna, A. Telesca, and P. J. M. Monteiro, “Microstructure and water absorption of ancient concrete from Pompeii: An integrated synchrotron microtomography and neutron radiography characterization,” Cement and Concrete Research, pp. 106–282, Jan. 2021.
  9. T. Takhtaganov, Z. Lukić, J. Müller, and D. Morozov, “Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations,” The Astrophysical Journal, vol. 906, no. 2, p. 74, Jan. 2021.
  10. V. Dumont, C. Garner, A. Trivedi, C. Jones, V. Ganapati, J. Mueller, T. Perciano, M. Kiran, and M. Day, “HYPPO: A Surrogate-Based Multi-Level Parallelism Tool for Hyperparameter Optimization,” in 2021 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC), pp. 81–93, 2021.
  11. R. Sadre, C. Ophus, A. Butko, and G. H. Weber, “Deep Learning Segmentation of Complex Features in Atomic-Resolution Phase Contrast Transmission Electron Microscopy Images,” Microscopy and Microanalysis, 2021.
  12. J.-T. Sohns, G. H. Weber, and C. Garth, “Distributed Task-Parallel Topology-Controlled Volume Rendering,” in Topological Methods in Data Analysis and Visualization VI: Theory, Algorithms, and Applications, I. Hotz, T. B. Masood, F. Sadlo, and J. Tierny, Eds. Springer International Publishing, 2021. In press.
  13. L. Kang, B. Xu, and D. Morozov, “Evaluating state space discovery by persistent cohomology in the spatial representation system,” Frontiers in computational neuroscience, vol. 15, p. 28, 2021.

2020

  1. B. P. Bowen and O. Rübel, “System and method of managing large data files ,” in US. Patent US10860526B2, pp. 12–21, Dec. 2020.
  2. H. A. Carr, J. Tierney, and G. H. Weber, “Pathological and Test Cases For Reeb Analysis,” in Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications, H. Carr, I. Fujishiro, F. Sadlo, and S. Takahashi, Eds. Springer International Publishing, pp. 103–120, Dec. 2020.
  3. P. Viseshchitra, P. Ercius, P. J. M. Monteiro, M. Scott, D. Ushizima, J. Li, K. Xu, and H.-R. Wenk, “3D Nanotomography of calcium silicate hydrates by transmission electron microscopy,” Journal of the American Ceramic Society, vol. 104, no. 4, pp. 1852–1862, Nov. 2020.
  4. R. Sadre and D. Ushizima, “Computer Aided Diagnostic Tools for COVID-19 Detection via X-Ray Imaging,” in 2020 IEEE/ACM Workshop on Urgent HPC: HPC for Urgent Decision Making at Super Computing, p. 1, Nov. 2020.
  5. D. Ushizima, M. McCormick, and D. Parkinson, “Accelerating Microstructural Analytics with Dask for Volumetric X-ray Images,” in 2020 IEEE/ACM 9th Workshop on Python for High-Performance and Scientific Computing (PyHPC) at Super Computing, pp. 41–48, Nov. 2020.
  6. D. Parkinson, H. Krishnan, D. Ushizima, M. Henderson, and S. Cholia, “Interactive Parallel Workflows for Synchrotron Tomography,” in 2020 IEEE/ACM 2nd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing (XLOOP) at Super Computing, pp. 29–34, Nov. 2020.
  7. H. Childs, S. D. Ahern, J. Ahrens, A. C. Bauer, J. Bennett, E. W. Bethel, P.-T. Bremer, E. Brugger, J. Cottam, M. Dorier, S. Dutta, J. M. Favre, T. Fogal, S. Frey, C. Garth, B. Geveci, W. F. Godoy, C. D. Hansen, C. Harrison, B. Hentschel, J. Insley, C. R. Johnson, S. Klasky, A. Knoll, J. Kress, M. Larsen, J. Lofstead, K.-L. Ma, P. Malakar, J. Meredith, K. Moreland, P. Navrátil, P. O’Leary, M. Parashar, V. Pascucci, J. Patchett, T. Peterka, S. Petruzza, N. Podhorszki, D. Pugmire, M. Rasquin, S. Rizzi, D. H. Rogers, S. Sane, F. Sauer, R. Sisneros, H.-W. Shen, W. Usher, R. Vickery, V. Vishwanath, I. Wald, R. Wang, G. H. Weber, B. Whitlock, M. Wolf, H. Yu, and S. B. Ziegeler, “A Terminology for In Situ Visualization and Analysis Systems,” International Journal of High Performance Computing Applications, vol. 34, no. 6, pp. 676–691, Nov. 2020.
  8. P. Hristov, G. H. Weber, H. A. Carr, O. Rübel, and J. P. Ahrens, “Data Parallel Hypersweeps for In Situ Topological Analysis,” in Proceedings of the 10th IEEE Symposium on Large Data Analysis and Visualization (LDAV), pp. 12–21, Oct. 2020.
  9. E. W. Bethel, D. Camp, T. Perciano, and C. Heinemann, “Performance Analysis of Traditional and Data-Parallel Primitive Implementations of Visualization and Analysis Kernels,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-2001365, Oct. 2020.
  10. D. Morozov and A. Nigmetov, “Towards Lockfree Persistent Homology,” in Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures, New York, NY, USA, pp. 555–557, Jul. 2020.
  11. S. Marchesini, A. Trivedi, P. Enfedaque, T. Perciano, and D. Parkinson, “Sparse Matrix-Based HPC Tomography,” in Computational Science – ICCS 2020, Cham, pp. 248–261, Jun. 2020.
  12. T. Perciano, C. Heinemann, D. Camp, B. Lessley, and E. W. Bethel, “Shared-Memory Parallel Probabilistic Graphical Modeling Optimization: Comparison of Threads, OpenMP, and Data-Parallel Primitives,” in High Performance Computing, Cham, pp. 127–145, Jun. 2020.
  13. B. Loring, M. Wolf, J. Kress, S. Shudler, J. Gu, S. Rizzi, J. Logan, N. Ferrier, and E. W. Bethel, “Improving Performance of M-to-N Processing and Data Redistribution in In Transit Analysis and Visualization,” in Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Norrköping, Sweden, May 2020. \urlhttps://escholarship.org/uc/item/9cn390hq.
  14. S. Murugesan, K. Bouchard, J. Brown, M. Kiran, D. Lurie, B. Hamann, and G. H. Weber, “State-based Network Similarity Visualization,” Information Visualization, vol. 19, no. 2, pp. 96–113, Apr. 2020. First published online November 2019.
  15. A. S. Krishnapriyan, M. Haranczyk, and D. Morozov, “Topological Descriptors Help Predict Guest Adsorption in Nanoporous Materials,” Journal of Physical Chemistry C, vol. 124, no. 17, pp. 9360–9368, Apr. 2020.
  16. T. Peterka, D. Bard, J. C. Bennett, E. W. Bethel, R. A. Oldfield, L. Pouchard, C. Sweeney, and M. Wolf, “Priority research directions for in situ data management: Enabling scientific discovery from diverse data sources,” The International Journal of High Performance Computing Applications, Mar. 2020.
  17. D. Ushizima, K. Xu, and P. Monteiro, “Materials Data Science for Microstructural Characterization of Archaeological Concrete,” MRS Advancements - special issue: Materials Data Science, pp. 1–14, Feb. 2020.
  18. P. Hristov, G. H. Weber, H. A. Carr, O. Rübel, and J. P. Ahrens, “Data Parallel Hypersweeps for in Situ Topological Analysis,” in 2020 IEEE 10th Symposium on Large Data Analysis and Visualization (LDAV), pp. 12–21, 2020.
  19. H. Chang, J. J. Donatelli, P. Enfedaque, G. Freychet, M. Haranczyk, A. Hexemer, Z. Hu, O. Jain, H. Krishnan, D. Kumar, X. Li, L. Lin, M. MacNeil, S. Marchesini, X. Mo, M. Noack, K. Pande, R. Pandolfi, D. Parkinson, D. M. Pelt, T. Perciano, D. A. Shapiro, D. Ushizima, C. Yang, P. H. Zwart, and J. A. Sethian, “Building Mathematics, Algorithms, and Software for Experimental Facilities,” in Handbook on Big Data and Machine Learning in the Physical Sciences, pp. 189–240, 2020.
  20. D. Kang, O. Rübel, S. Byna, and S. Blanas, “Predicting and Comparing the Performance of Array Management Libraries,” in 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 906–915, 2020.
  21. A.-P. Lohfink, F. Wetzels, J. Lukasczyk, G. H. Weber, and C. Garth, “Fuzzy Contour Trees: Alignment and Joint Layout of Multiple Contour Trees,” Computer Graphics Forum (Special Issue, Proceedings Eurographics/IEEE Symposium on Visualization), vol. 39, no. 3, pp. 343–355, 2020.
  22. J. Lukasczyk, C. Garth, G. H. Weber, T. Biedert, R. Maciejewski, and H. Leitte, “Dynamic Nested Tracking Graphs,” IEEE Transactions on Visualization and Computer Graphics (Proceedings IEEE VIS 2019), vol. 26, no. 1, pp. 249–258, 2020.
  23. D. Smirnov and D. Morozov, “Triplet Merge Trees,” in Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications, 2020.

2019

  1. MacNeil, Ushizima, Panerai, Mansour, Barnard, and Parkinson, “Interactive Volumetric Segmentation for Textile Microtomography Data using Wavelets and Non-local means,” Journal of Statistical Analysis and Mining, Sep. 2019.
  2. A. Babichev, D. Morozov, and Y. Dabaghian, “Replays of spatial memories suppress topological fluctuations in cognitive map,” Network neuroscience (Cambridge, Mass.), vol. 3, no. 3, pp. 707–724, Jul. 2019.
  3. Araujo, Silva, Resende, Ushizima, Medeiros, Carneiro, and Bianchi, “Deep Learning for Cell Image Segmentation and Ranking,” Computerized Medical Imaging and Graphics, Mar. 2019.
  4. G. Carlsson, V. de Silva, S. Kališnik, and D. Morozov, “Parametrized homology via zigzag persistence,” Algebraic & Geometric Topology, vol. 19, no. 2, pp. 657–700, Mar. 2019.
  5. T. Peterka, D. Bard, J. Bennett, E. W. Bethel, R. Oldfield, L. Pouchard, C. Sweeney, and M. Wolf, Eds., “Workshop report on In Situ Data Management,” DOE Office of Advanced Scientific Computing Research, Feb. 2019.
  6. O. Erbilgin, O. Rübel, K. B. Louie, M. Trinh, M. de Raad, T. Wildish, D. Udwary, C. Hoover, S. Deutsch, T. R. Northen, and B. P. Bowen, “MAGI: A Method for Metabolite Annotation and Gene Integration,” ACS Chemical Biology, vol. 14, no. 4, pp. 704–714, 2019. PMID: 30896917.
  7. A. J. Tritt, O. Rübel, B. Dichter, R. Ly, D. Kang, E. F. Chang, L. M. Frank, and K. Bouchard, “HDMF: Hierarchical Data Modeling Framework for Modern Science Data Standards,” in 2019 IEEE International Conference on Big Data (Big Data), pp. 165–179, 2019.
  8. J. Gu, B. Loring, K. Wu, and E. W. Bethel, “HDF5 As a Vehicle for in Transit Data Movement,” in Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, New York, NY, USA, pp. 39–43, 2019.
  9. S. Liu, C. N. Melton, S. Venkatakrishnan, R. J. Pandolfi, G. Freychet, D. Kumar, H. Tang, A. Hexemer, and D. M. Ushizima, “Convolutional neural networks for grazing incidence x-ray scattering patterns: thin film structure identification,” MRS Communications, pp. 1–7, 2019.
  10. O. Rübel, A. Tritt, B. Dichter, T. Braun, N. Cain, N. Clack, T. J. Davidson, M. Dougherty, J.-C. Fillion-Robin, N. Graddis, M. Grauer, J. T. Kiggins, L. Niu, D. Ozturk, W. Schroeder, I. Soltesz, F. T. Sommer, K. Svoboda, L. Ng, L. M. Frank, and K. Bouchard, “NWB:N 2.0: An Accessible Data Standard for Neurophysiology,” bioRxiv, 2019. (preprint).
  11. A. Nigmetov and D. Morozov, “Local-global Merge Tree Computation with Local Exchanges,” in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, New York, NY, USA, pp. 60:1–60:13, 2019.
  12. J. Patchett and E. W. Bethel, “Software Complexity, Heterogeneity, and User-facing Issues,” in In Situ Visualization for Computational Science (Dagstuhl Seminar 18271), vol. 8, no. 7, J. C. Bennett, H. Childs, C. Garth, and B. Hentschel, Eds. Dagstuhl, Germany: Schloss Dagstuhl–Leibniz-Zentrum fuer Informatik, pp. 1–43, 2019.

2018

  1. Araujo, Silva, Medeiros, Farias, Calaes, Bianchi, Carneiro, and Ushizima, “Active contours for overlapping cell segmentation,” International Journal of Biomedical Engineering and Technology, Dec. 2018.
  2. G. H. Weber, C. Ophus, and L. Ramakrishnan, “Automated Labeling of Electron Microscopy Images Using Deep Learning,” in Proc. IEEE/ACM Machine Learning in HPC Environments (MLHPC), pp. 26–36, Nov. 2018.
  3. O. Erbilgin, B. P. Bowen, T. R. Northen, M. DeRaad, and O. Ruebel, “Metabolite, annotation, and gene integration system and method,” United States Patent Application, Oct. 2018. Patent Application, Pub. No. US2018/0239863.
  4. B. Lessley, T. Perciano, C. Heinemann, D. Camp, and Hank Childs, and E. W. Bethel, “DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives,” in 8th IEEE Symposium on Large Data Analysis and Visualization (LDAV), Berlin, Germany, Oct. 2018.
  5. G. P. Rodrigo, M. Henderson, G. H. Weber, C. Ophus, K. Antypas, and L. Ramakrishnan, “ScienceSearch: Enabling Search through Automatic Metadata Generation,” in Proceedings IEEE 14th International Conference on e-Science (e-Science) 2018, pp. 93–104, Oct. 2018.
  6. V. de Melo, D. Ushizima, S. Baracho, and R. Coelho, “Gradient Boosting Decision Trees for Echocardiogram Images,” in 2018 International Joint Conference on Neural Networks (IJCNN), Jul. 2018.
  7. R. J. Pandolfi, D. B. Allan, E. Arenholz, L. Barroso-Luque, S. I. Campbell, T. A. Caswell, A. Blair, F. De Carlo, S. Fackler, A. P. Fournier, G. Freychet, M. Fukuto, D. Gürsoy, Z. Jiang, H. Krishnan, D. Kumar, R. J. Kline, R. Li, C. Liman, S. Marchesini, A. Mehta, A. T. N’Diaye, D. Y. Parkinson, H. Parks, L. A. Pellouchoud, T. Perciano, F. Ren, S. Sahoo, J. Strzalka, D. Sunday, C. J. Tassone, D. Ushizima, S. Venkatakrishnan, K. G. Yager, P. Zwart, J. A. Sethian, and A. Hexemer, “Xi-cam: A Versatile Interface for Data Visualization and Analysis,” Journal of Synchrotron Radiation, vol. 25, no. 4, Jul. 2018.
  8. T.-W. Ke, A. S. Brewster, S. X. Yu, D. Ushizima, C. Yang, and N. K. Sauter, “A Convolutional Neural Network-based Screening Tool for X-ray Serial Crystallography,” Journal of Synchrotron Radiation, vol. 25, no. 3, pp. 655–670, May 2018.
  9. K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. D. Simon, F. T. Sommer, and Prabhat, “International Neuroscience Initiatives through the Lens of High-Performance Computing,” Computer, vol. 51, no. 4, pp. 50–59, Apr. 2018.
  10. K. Beketayev, D. Yeliussizov, D. Morozov, G. H. Weber, and B. Hamann, “Measuring the Error in Approximating the Sub-level Set Topology of Sampled Scalar Data,” International Journal of Computational Geometry & Applications (IJCGA), vol. 28, no. 1, pp. 57–77, Mar. 2018.
  11. M. F. Wehner, K. A. Reed, B. Loring, D. Stone, and H. Krishnan, “Changes in tropical cyclones under stabilized 1.5 and 2.0°C global warming scenarios as simulated by the Community Atmospheric Model under the HAPPI protocols,” Earth System Dynamics, vol. 9, no. 1, pp. 187–195, Feb. 2018.
  12. O. Rübel and B. P. Bowen, “BASTet: Shareable and Reproducible Analysis and Visualization of Mass Spectrometry Imaging Data via OpenMSI,” IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 1025–1035, Jan. 2018.
  13. B. Loring, A. Myers, D. Camp, and E. W. Bethel, “Python-based in situ analysis and visualization,” in Proceedings of the Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization - ISAV ’18, 2018.
  14. D. Y. Parkinson, J. I. Pacold, M. Gross, T. D. McDougall, C. Jones, J. Bows, I. Hamilton, D. E. Smiles, S. D. Santis, A. Ratti, D. E. Pelt, J. Sethian, H. Barnard, J. Peterson, A. Ramirez-Hong, A. MacDowell, and D. K. Shuh, “Achieving fast high-resolution 3D imaging by combining synchrotron x-ray microCT, advanced algorithms, and high performance data management,” in Image Sensing Technologies: Materials, Devices, Systems, and Applications V, pp. 136–141, vol. 10656, 2018.
  15. A. Babichev, D. Morozov, and Y. Dabaghian, “Robust spatial memory maps encoded by networks with transient connections,” PLoS computational biology, vol. 14, no. 9, p. e1006433, 2018.
  16. P. Enfedaque, H. Chang, H. Krishnan, and S. Marchesini, “GPU-Based Implementation of Ptycho-ADMM for High Performance X-Ray Imaging,” in Computational Science – ICCS 2018, Cham, pp. 540–553, 2018.
  17. P. Koanantakool, A. Ali, A. Azad, A. Buluc, D. Morozov, L. Oliker, K. Yelick, and S.-Y. Oh, “Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation,” in Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, Canary Islands, pp. 1376–1386, vol. 84, 2018.
  18. T. Liebmann, G. H. Weber, and G. Scheuermann, “Hierarchical Correlation Clustering in Multiple 2D Scalar Fields,” Computer Graphics Forum (Special Issue, Proceedings Eurographics/IEEE Symposium on Visualization), vol. 37, no. 3, 2018.
  19. E. Lohrmann, Z. Lukić, D. Morozov, and J. Müller, “Programmable In Situ System for Iterative Workflows,” in Job Scheduling Strategies for Parallel Processing, pp. 122–131, 2018.

2017

  1. C. Heinemann, T. Perciano, D. Ushizima, and E. W. Bethel, “Distributed Memory Parallel Markov Random Fields Using Graph Partitioning,” in 2017 IEEE International Conference on Big Data (Big Data), pp. 3332–3341, Dec. 2017.
  2. E. W. Bethel, “Towards a Data-Centric Research and Development Roadmap for Large-scale Science User Facilities,” in 13th IEEE International Conference on eScience, Auckland, NZ, Oct. 2017.
  3. B. Lessley, T. Perciano, M. Mathai, H. Childs, and E. W. Bethel, “Maximal Clique Enumeration with Data Parallel Primitives,” in 7th IEEE Symposium on Large Data Analysis and Visualization (LDAV), Phoenix, AZ, USA, Oct. 2017.
  4. T. Perciano, D. Ushizima, H. Krishnan, D. Parkinson, N. Larson, D. M. Pelt, W. Bethel, F. Zok, and J. Sethian, “Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics,” Journal of Synchrotron Radiation, vol. 24, no. 5, pp. 1065–1077, Sep. 2017.
  5. M. Kerber, D. Morozov, and A. Nigmetov, “Geometry Helps to Compare Persistence Diagrams,” Journal of Experimental Algorithmics, vol. 22, pp. 1.4:1–1.4:20, Sep. 2017.
  6. G. H. Weber, M. S. Bandstra, D. Chivers, H. H. Elgammal, V. Hendrix, J. Kua, J. Maltz, K. Muriki, Y. Ong, K. Song, M. Quinlan, L. Ramakrishnan, and B. J. Quiter, “Web-based Visual Data Exploration for Improved Radiological Source Detection,” Concurrency and Computation: Practice and Experience, vol. 29, no. 18, p. e4203, Sep. 2017.
  7. J. Lukasczyk, R. Maciejewski, G. H. Weber, C. Garth, and H. Leitte, “Nested Tracking Graphs,” Computer Graphics Forum (Special Issue, Proceedings Eurographics/IEEE Symposium on Visualization), vol. 36, no. 3, pp. 12–22, Jul. 2017. Best paper award.
  8. S. Murugesan, K. Bouchard, J. A. Brown, B. Hamann, W. W. Seeley, A. Trujillo, and G. H. Weber, “Brain Modulyzer: Interactive Visual Analysis of Functional Brain Connectivity,” IEEE Transactions on Computational Biology and Bioinformatics, vol. 14, no. 4, pp. 805–818, Jul. 2017. LBNL-1005732.
  9. M. De Raad, T. De Rond, O. Rübel, J. D. Keasling, T. R. Northen, and B. P. Bowen, “OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging,” Analytical Chemistry, vol. 89, no. 11, pp. 5818–5823, Jun. 2017.
  10. P. Oesterling, C. Heine, G. H. Weber, D. Morozov, and G. Scheuermann, “Computing and Visualizing Time-Varying Merge Trees for High-Dimensional Data,” in Topological Methods in Data Analysis and Visualization IV: Theory, Algorithms, and Applications, H. Carr, C. Garth, and T. Weinkauf, Eds. Springer International Publishing, pp. 87–101, May 2017. LBNL-1005735. Best paper award.
  11. G. H. Weber, S. Carpendale, D. Ebert, B. Fisher, H. Hagen, B. Shneiderman, and A. Ynnerman, “Apply or Die: On the Role and Assessment of Application Papers in Visualization,” IEEE Computer Graphics & Applications, vol. 37, no. 3, pp. 96–104, Apr. 2017.
  12. M. Farmand, R. Celestre, P. Denes, A. L. D. Kilcoyne, S. Marchesini, H. Padmore, T. Tyliszczak, T. Warwick, X. Shi, J. Lee, Y.-S. Yu, J. Cabana, J. Joseph, H. Krishnan, T. Perciano, F. R. N. C. Maia, and D. A. Shapiro, “Near-edge X-ray refraction fine structure microscopy,” Applied Physics Letters, vol. 110, no. 6, p. 063101, Feb. 2017.
  13. B. J. Daurer, H. Krishnan, T. Perciano, F. R. N. C. Maia, D. A. Shapiro, J. A. Sethian, and S. Marchesini, “Nanosurveyor: a framework for real-time data processing,” Advanced Structural and Chemical Imaging, vol. 3, no. 1, p. 7, Jan. 2017.
  14. O. Erbilgin, O. Rübel, K. B. Louie, M. Trinh, M. de Raad, T. Wildish, D. W. Udwary, C. A. Hoover, S. Deutsch, T. R. Northen, and B. P. Bowen, “MAGI: A Bayesian-like method for metabolite, annotation, and gene integration,” bioRxiv, 2017.
  15. D. Y. Parkinson, D. M. Pelt, T. Perciano, D. Ushizima, H. Krishnan, H. S. Barnard, A. A. MacDowell, and J. Sethian, “Machine learning for micro-tomography,” in Proc. SPIE, pp. 10391–10391 - 8, vol. 10391, 2017.
  16. H. Edelsbrunner and D. Morozov, “Persistent Homology,” in Handbook of Discrete and Computational Geometry, 3rd ed., J. E. Goodman, J. O’Rourke, and C. D. Tóth, Eds. CRC Press, 2017.
  17. S. Murugesan, K. Bouchard, E. Chang, M. Dougherty, B. Hamann, and G. H. Weber, “Multi-scale Visual Analysis of Time-varying Electrocorticography Data via Clustering of Brain Regions,” BMC Bioinformatics, vol. 18, no. Suppl 6, p. 236, 2017.
  18. T. E. Williams, D. Ushizima, C. Zhu, A. Anders, D. J. Milliron, and B. A. Helms, “Nearest-neighbour nanocrystal bonding dictates framework stability or collapse in colloidal nanocrystal frameworks,” Chemical Communications, vol. 53, no. 35, pp. 4853–4856, 2017.
  19. M. Alegro, P. Theofilas, A. Nguy, P. A. Castruita, W. Seeley, H. Heinsen, D. M. Ushizima, and L. T. Grinberg, “Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding,” Journal of Neuroscience Methods, vol. 282, pp. 20–33, 2017.

2016

  1. M. Alegro, E. Amaro, B. Loring, H. Heinsen, E. Alho, L. Zollei, D. Ushizima, and L. T. Grinberg, “Multimodal Whole Brain Registration: MRI and High Resolution Histology,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 634–642, Dec. 2016.
  2. O. Rübel, M. Dougherty, Prabhat, P. Denes, D. Conant, E. F. Chang, and K. Bouchard, “Methods for specifying scientific data standards and modeling relationships with applications to neuroscience,” Frontiers in Neuroinformatics, vol. 10, no. NOV, Nov. 2016.
  3. D. M. Ushizima, H. A. Bale, E. W. Bethel, P. Ercius, B. A. Helms, H. Krishnan, L. T. Grinberg, M. Haranczyk, A. A. Macdowell, K. Odziomek, D. Y. Parkinson, T. Perciano, R. O. Ritchie, and C. Yang, “IDEAL: Images Across Domains, Experiments, Algorithms and Learning,” JOM, vol. 68, no. 11, pp. 2963–2972, Nov. 2016.
  4. D. Morozov and T. Peterka, “Efficient Delaunay tessellation through K-D tree decomposition,” in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Piscataway, NJ, USA, p. 62, Nov. 2016.
  5. U. Ayachit, B. Whitlock, M. Wolf, B. Loring, B. Geveci, D. Lonie, and E. W. Bethel, “The SENSEI Generic In Situ Interface,” in Proceedings of In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization (ISAV 2016), Salt Lake City, UT, USA, Nov. 2016. LBNL-1007263.
  6. U. Ayachit, A. Bauer, E. P. N. Duque, G. Eisenhauer, N. Ferrier, J. Gu, K. Jansen, B. Loring, Z. Lukić, S. Menon, D. Morozov, P. O’Leary, M. Rasquin, C. P. Stone, V. Vishwanath, G. H. Weber, B. Whitlock, M. Wolf, K. J. Wu, and E. W. Bethel, “Performance Analysis, Design Considerations, and Applications of Extreme-scale In Situ Infrastructures,” in ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC16), Salt Lake City, UT, USA, Nov. 2016. LBNL-1007264.
  7. A. Ovsyannikov, M. Romanus, B. Van Straalen, G. H. Weber, and D. Trebotich, “Scientific Workflows at DataWarp-Speed: Accelerated Data-Intensive Science using NERSC’s Burst Buffer,” in Proceedings of the 1st Joint International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems, pp. 1–6, Nov. 2016.
  8. H. A. Carr, G. H. Weber, C. M. Sewell, and J. P. Ahrens, “Parallel Peak Pruning for Scalable SMP Contour Tree Computation,” in Proceedings of the 6th IEEE Symposium on Large Data Analysis and Visualization (LDAV), pp. 75–84, Oct. 2016. Best paper award.
  9. E. W. Bethel, M. Greenwald, K. K. van Dam, M. Parashar, S. M. Wild, and H. S. Wiley, “Management, Analysis, and Visualization of Experimental and Observational Data – The Convergence of Data and Computing,” in Proceedings of the 2016 IEEE 12th International Conference on eScience, Baltimore, MD, USA, Oct. 2016. LBNL-1006061.
  10. H. Nguyen, D. Stone, and E. W. Bethel, “Statistical Projections for Multi-dimensional Visual Data Exploration,” in 6th IEEE Symposium on Large Data Analysis and Visualization, Baltimore, MD, USA, Oct. 2016.
  11. T. Perciano, D. M. Ushizima, E. W. Bethel, Y. D. Mizrahi, D. Parkinson, and J. A. Sethian, “Reduced-complexity image segmentation under parallel Markov Random Field formulation using graph partitioning,” in 2016 IEEE International Conference on Image Processing (ICIP), pp. 1259–1263, Sep. 2016.
  12. S. Marchesini, H. Krishnan, B. J. Daurer, D. A. Shapiro, T. Perciano, J. A. Sethian, and F. R. N. C. Maia, “\it SHARP: a distributed GPU-based ptychographic solver,” Journal of Applied Crystallography, vol. 49, no. 4, pp. 1245–1252, Aug. 2016.
  13. B. Friesen, A. Almgren, Z. Lukić, G. H. Weber, D. Morozov, V. Beckner, and M. Day, “In Situ and In-transit Analysis of Cosmological Simulations,” Computational Astrophysics and Cosmology, vol. 3, no. 4, pp. 1–18, Aug. 2016. LBNL-1006104.
  14. A. C. Bauer, H. Abbasi, J. Ahrens, H. Childs, B. Geveci, S. Klasky, K. Moreland, P. O’Leary, V. Vishwanath, B. Whitlock, and E. W. Bethel, “In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms, a State-of-the-art (STAR) Report,” Computer Graphics Forum, Proceedings of Eurovis 2016, vol. 35, no. 3, Jun. 2016. LBNL-1005709.
  15. H. Tang, S. Byna, S. Harenberg, X. Zou, W. Zhang, K. Wu, B. Dong, O. Rubel, K. Bouchard, S. Klasky, and N. F. Samatova, “Usage Pattern-Driven Dynamic Data Layout Reorganization,” in 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp. 356–365, May 2016.
  16. P. Koanantakool, A. Azad, A. Buluc, D. Morozov, S.-Y. Oh, L. Oliker, and K. Yelick, “Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix Multiplication,” in 2016 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. 842–853, May 2016.
  17. O. Rübel, B. Loring, J. L. Vay, D. P. Grote, R. Lehe, S. Bulanov, H. Vincenti, and E. W. Bethel, “WarpIV: In Situ Visualization and Analysis of Ion Accelerator Simulations,” IEEE Computer Graphics and Applications, vol. 36, no. 3, pp. 22–35, May 2016.
  18. E. W. Bethel and M. Greenwald, Eds., “Report of the DOE Workshop on Management, Analysis, and Visualization of Experimental and Observational data – The Convergence of Data and Computing,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, May 2016. LBNL-1005155.
  19. H. T. Nguyen, D. Stone, and E. W. Bethel, “Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, Jan. 2016. LBNL-1003958.
  20. K. E. Bouchard, J. B. Aimone, M. Chun, T. Dean, M. Denker, M. Diesmann, D. D. Donofrio, L. M. Frank, N. Kasthuri, C. Koch, O. Rübel, H. D. Simon, F. T. Sommer, and Prabhat, “High-Performance Computing in Neuroscience for Data-Driven Discovery, Integration, and Dissemination,” Neuron, vol. 92, no. 3, pp. 628–631, 2016.
  21. O. Rübel, M. Dougherty, Prabhat, P. Denes, D. Conant, E. F. Chang, and K. Bouchard, “Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience,” Frontiers in Neuroinformatics, vol. 10, p. 48, 2016.
  22. A. Gittens, J. Kottalam, J. Yang, M. F. Ringenburg, J. Chhugani, E. Racah, M. Singh, Y. Yao, C. Fischer, O. Rübel, B. Bowen, N. G. Lewis, M. W. Mahoney, V. Krishnamurthy, and Prabhat, “A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark,” in 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 1403–1412, 2016.
  23. T. A. O’Brien, W. D. Collins, K. Kashinath, O. Rübel, S. Byna, J. Gu, H. Krishnan, and P. A. Ullrich, “Resolution dependence of precipitation statistical fidelity in hindcast simulations,” Journal of Advances in Modeling Earth Systems, vol. 8, no. 2, pp. 976–990, 2016.
  24. T. Perciano, F. Tupin, R. H. Jr., and R. M. C. Jr., “A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data,” International Journal of Remote Sensing, vol. 37, no. 16, pp. 3584–3610, 2016.
  25. D. Y. Parkinson, K. Beattie, X. Chen, J. Correa, E. Dart, B. J. Daurer, J. R. Deslippe, A. Hexemer, H. Krishnan, A. A. MacDowell, F. R. N. C. Maia, S. Marchesini, H. A. Padmore, S. J. Patton, T. Perciano, J. A. Sethian, D. Shapiro, R. Stromsness, N. Tamura, B. L. Tierney, C. E. Tull, and D. Ushizima, “Real-time data-intensive computing,” AIP Conference Proceedings, vol. 1741, no. 1, p. 050001, 2016.
  26. W. Bhimji, D. Bard, M. Romanus, D. Paul, A. Ovsyannikov, B. Friesen, M. Bryson, J. Correa, G. K. Lockwood, V. Tsulaia, S. Byna, S. Farrell, D. Gursoy, C. Daley, V. Beckner, B. Van Straalen, D. Trebotich, C. Tull, G. H. Weber, N. J. Wright, K. Antypas, and Prabhat, “Accelerating Science with the NERSC Burst Buffer Early User Program,” in CUG2016 Proceedings, 2016. LBNL-1005736. Best paper award.
  27. D. Morozov and Z. Lukić, “Master of Puppets: Cooperative Multitasking for In Situ Processing,” in Proceedings of the Symposium on High-Performance Parallel and Distributed Computing (HPDC), pp. 285–288, 2016.
  28. D. Morozov and T. Peterka, “Block-Parallel Data Analysis with DIY2,” in Proceedings of the IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2016.
  29. M. Kerber, D. Morozov, and A. Nigmetov, “Geometry Helps to Compare Persistence Diagrams,” in Proceedings of the Workshop on Algorithm Engineering and Experiments (ALENEX), 2016.
  30. S. Murugesan, K. Bouchard, E. Chang, M. Dougherty, B. Hamann, and G. H. Weber, “Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data,” in Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, New York, NY, USA, pp. 630–639, 2016. Best paper award.
  31. S. V. Venkatakrishnan, K. A. Mohan, K. Beattie, J. Correa, E. Dart, J. R. Deslippe, A. Hexemer, H. Krishnan, A. A. MacDowell, S. Marchesini, S. J. Patton, T. Perciano, J. A. Sethian, R. Stromsness, B. L. Tierney, C. E. Tull, D. Ushizima, and D. Y. Parkinson, “Making Advanced Scientific Algorithms and Big Scientific Data Management More Accessible,” Electronic Imaging, vol. 2016, no. 19, pp. 1–7, 2016.
  32. C. R. Fischer, O. Rübel, and B. P. Bowen, “An accessible, scalable ecosystem for enabling and sharing diverse mass spectrometry imaging analyses ,” Archives of Biochemistry and Biophysics , vol. 589, pp. 18–26, 2016. Applications of Metabolomics .

2015

  1. D. Ushizima, T. Perciano, and D. Parkinson, “Fast detection of material deformation through structural dissimilarity,” in Big Data (Big Data), 2015 IEEE International Conference on, pp. 2775–2781, Oct. 2015. LBNL-1003925.
  2. B. Loring, H. Karimabadi, and V. Rortershteyn, “A Screen Space GPGPU Surface LIC Algorithm for Distributed Memory Data Parallel Sort Last Rendering Infrastructures,” in Astronomical Society of the Pacific Conference Series, p. 231, vol. 498, Oct. 2015.
  3. E. W. Bethel, D. Camp, D. Donofrio, and M. Howison, “Improving Performance of Structured-memory, Data-Intensive Applications on Multi-core Platforms via a Space-Filling Curve Memory Layout,” in International Workshop on High Performance Data Intensive Computing, an IEEE International Parallel and Distributed Processing Symposium (IPDPS) workshop, Hyderabad, India, May 2015. LBNL-6999E.
  4. E. W. Bethel, “zorder-lib: Library API for Z-Order Memory Layout,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, Apr. 2015. LBNL-176763.
  5. D. S. Dalisay, K. W. Kim, C. Lee, H. Yang, O. Rübel, B. P. Bowen, L. B. Davin, and N. G. Lewis, “Dirigent Protein-Mediated Lignan and Cyanogenic Glucoside Formation in Flax Seed: Integrated Omics and MALDI Mass Spectrometry Imaging,” Journal of Natural Products, vol. 78, no. 6, pp. 1231–1242, 2015. PMID: 25981198.
  6. J. Yang, O. Rübel, Prabhat, M. W. Mahoney, and B. P. Bowen, “Identifying Important Ions and Positions in Mass Spectrometry Imaging Data Using CUR Matrix Decompositions,” Analytical Chemistry, vol. 87, no. 9, pp. 4658–4666, 2015. PMID: 25825055.
  7. Y. Yao, T. Sun, T. Wang, O. Rübel, T. Northen, and B. P. Bowen, “Analysis of Metabolomics Datasets with High-Performance Computing and Metabolite Atlases,” Metabolites, vol. 5, no. 3, p. 431, 2015.
  8. O. Rübel, M. Prabhat, P. Denes, D. Conant, E. Chang, and K. Bouchard, “BRAINformat: A Data Standardization Framework for Neuroscience Data,” bioRxiv, 2015. LBNL-188372.
  9. A. W. Wills, D. J. Michalak, P. Ercius, E. R. Rosenberg, T. Perciano, D. Ushizima, R. Runser, and B. A. Helms, “Block Copolymer Packing Limits and Interfacial Reconfigurability in the Assembly of Periodic Mesoporous Organosilicas,” Advanced Functional Materials, pp. n/a–n/a, 2015.
  10. R. Lewis and D. Morozov, “Parallel Computation of Persistent Homology using the Blowup Complex,” in Proceedings of the Annual Symposium on Parallelism in Algorithms and Architectures, pp. 323–331, 2015.
  11. A. Agranovsky, D. Camp, K. I. Joy, and H. Childs, “Subsampling-based compression and flow visualization,” in Proc. SPIE, pp. 93970J–93970J-14, vol. 9397, 2015.
  12. J. Donatelli, M. Haranczyk, A. Hexemer, H. Krishnan, X. Li, L. Lin, F. Maia, S. Marchesini, D. Parkinson, T. Perciano, D. Shapiro, D. Ushizima, C. Yang, and J. A. Sethian, “CAMERA: The Center for Advanced Mathematics for Energy Research Applications,” Synchrotron Radiation News, vol. 28, no. 2, pp. 4–9, 2015.

2014

  1. H. Childs, S. Biersdorff, D. Poliakoff, D. Camp, and A. D. Malony, “Particle Advection Performance Over Varied Architectures and Workloads,” in 21th Annual International Conference on High Performance Computing, HiPC 2014, Goa, India, Dec. 2014. LBNL-6730E.
  2. A. Agranovsky, D. Camp, C. Garth, E. W. Bethel, K. I. Joy, and H. Childs, “Improved Post Hoc Flow Analysis Via Lagrangian Representations,” in Proceedings of the IEEE Symposium on Large Data Visualization and Analysis (LDAV), Paris, France, pp. 67–75, Nov. 2014. LBNL-6731E. Best paper award.
  3. M. Howison and E. W. Bethel, “GPU-Accelerated Denoising of 3D Magnetic Resonance Images,” Journal of Real-Time Image Processing, pp. 1–12, Jun. 2014. LBNL-6707E.
  4. O. Rübel, C. G. R. Geddes, M. Chen, E. Cormier-Michel, and E. W. Bethel, “Feature-Based Analysis of Plasma-Based Particle Acceleration Data,” IEEE Transactions on Visualization and Computer Graphics, vol. 20, no. 2, pp. 196–210, Feb. 2014.
  5. W. Daughton, T. K. M. Nakamura, H. Karimabadi, V. Roytershteyn, and B. Loring, “Computing the reconnection rate in turbulent kinetic layers by using electron mixing to identify topology,” Physics of Plasmas, vol. 21, no. 5, Jan. 2014.
  6. D. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian, “Structure recognition from high resolution images of ceramic composites,” in Proceedings - 2014 IEEE International Conference on Big Data, IEEE Big Data 2014, pp. 683–691, Jan. 2014.
  7. H. Karimabadi, V. Roytershteyn, H. X. Vu, Y. A. Omelchenko, J. Scudder, W. Daughton, A. Dimmock, K. Nykyri, M. Wan, D. Sibeck, M. Tatineni, A. Majumdar, B. Loring, and B. Geveci, “The link between shocks, turbulence, and magnetic reconnection in collisionless plasmas,” Physics of Plasmas, vol. 21, no. 6, Jan. 2014.
  8. G. H. Weber and H. Hauser, “Interactive Visual Exploration and Analysis,” in Scientific Visualization: Uncertainty, Multifield, Bio-Medical and Scalable Visualization, C. D. Hansen, M. Chen, C. R. Johnson, A. E. Kaufman, and H. Hagen, Eds. Springer-Verlag, pp. 161–174, 2014. LBNL-6655E.
  9. K. Beketayev, D. Yeliussizov, D. Morozov, G. H. Weber, and B. Hamann, “Measuring the Distance Between Merge Trees,” in Topological Methods in Data Analysis and Visualization III: Theory, Algorithms, and Applications, P.-T. Bremer, I. Hotz, V. Pascucci, and R. Peikert, Eds. Springer-Verlag, pp. 151–166, 2014. LBNL-6629E.
  10. W. Harvey, I.-H. Park, O. Rübel, V. Pascucci, P.-T. Bremer, C. Li, and Y. Wang, “A collaborative visual analytics suite for protein folding research,” Journal of Molecular Graphics and Modelling, vol. 53, pp. 59–71, 2014.
  11. G. H. Weber, H. Johansen, D. T. Graves, and T. J. Ligocki, “Simulating Urban Environments for Energy Analysis,” in Workshop on Visualisation in Environmental Sciences (EnvirVis), 2014. LBNL-6652E.
  12. D. Morozov and G. H. Weber, “Distributed Contour Trees,” in Topological Methods in Data Analysis and Visualization III: Theory, Algorithms, and Applications, P.-T. Bremer, I. Hotz, V. Pascucci, and R. Peikert, Eds. Springer-Verlag, pp. 89–102, 2014. LBNL-6654E.

2013

  1. C. Müller, D. Camp, B. Hentschel, and C. Garth, “Distributed Parallel Particle Advection using Work Requesting,” in Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV), Oct. 2013. LBNL-6467E.
  2. D. Williams, C. Doutriaux, J. Patchett, S. Williams, G. Shipman, R. Miller, C. Steed, H. Krishnan, C. Silva, A. Chaudhary, P.-T. Bremer, D. Pugmire, W. Bethel, H. Childs, M. Prabhat, B. Geveci, A. Bauer, A. Pletzer, J. Poco, T. Ellqvist, E. Santos, G. Potter, B. Smith, T. Maxwell, D. Kindig, and D. Koop, “Ultrascale Visualization of Climate Data,” IEEE Computer, vol. 46, no. 9, pp. 68–76, Sep. 2013. LBNL-6278E.
  3. D. Camp, E. W. Bethel, and H. Childs, “Transitioning Data Flow-Based Visualization Software to Multi-Core Hybrid Parallelism,” in 3rd International Workshop on Data-Flow Execution Models for Extreme Scale Computing (DFM 2013), pp. 41–44, Sep. 2013.
  4. K. Wu, E. W. Bethel, M. Gu, D. Leinweber, and O. Rübel, “Testing VPIN on Big Data – Response to ’Reflecting on the VPIN Dispute,’” Social Sciences Research Network, Aug. 2013.
  5. H. Karimabadi, B. Loring, P. O’leary, A. Majumdar, M. Tatineni, and B. Geveci, “In-situ visualization for global hybrid simulations,” in ACM International Conference Proceeding Series, Aug. 2013.
  6. H. Childs, B. Geveci, W. J. Schroeder, J. S. Meredith, K. Moreland, C. Sewell, T. Kuhlen, and E. W. Bethel, “Research Challenges for Visualization Software,” IEEE Computer, vol. 46, no. 5, pp. 34–42, May 2013.
  7. D. Camp, H. Krishnan, D. Pugmire, C. Garth, I. Johnson, E. W. Bethel, K. I. Joy, and H. Childs, “GPU Acceleration of Particle AdvectionWorkloads in a Parallel, Distributed Memory Setting,” in Proceedings of EuroGraphics Symposium on Parallel Graphics and Visualization, pp. 1–8, May 2013. LBNL-6146E.
  8. P. Oesterling, C. Heine, G. H. Weber, and G. Scheuermann, “Visualizing nD Point Clouds as Topological Landscape Profiles to Guide Local Data Analysis,” IEEE Transactions on Visualization and Computer Graphics, vol. 19, no. 3, pp. 514–526, Mar. 2013. LBNL-5694E.
  9. E. W. Bethel, Prabhat, S. Byna, O. Rübel, K. J. Wu, and M. Wehner, “Why High Performance Visual Data Anaytics is Both Relevant and Difficult,” in Visualization and Data Analysis, IS&T/SPIE Electronic Imaging 2013, San Francisco, CA, USA, Feb. 2013. LBNL-6063E.
  10. H. Karimabadi, V. Roytershteyn, M. Wan, W. H. Matthaeus, W. Daughton, P. Wu, M. Shay, B. Loring, J. Borovsky, E. Leonardis, S. C. Chapman, and T. K. M. Nakamura, “Coherent structures, intermittent turbulence, and dissipation in high-temperature plasmas,” Physics of Plasmas, vol. 20, no. 1, Jan. 2013.
  11. O. Rübel, A. Greiner, S. Cholia, K. Louie, E. W. Bethel, T. R. Northen, and B. P. Bowen, “OpenMSI: A High-Performance Web-Based Platform for Mass Spectrometry Imaging,” Analytical Chemistry, vol. 85, no. 21, pp. 10354–10361, 2013. LBNL-6477E.
  12. D. Morozov and G. H. Weber, “Distributed Merge Trees,” in Proceedings of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’13), New York, NY, USA, pp. 93–102, 2013. LBNL-6137E.

2012

  1. J. Meyer, E. W. Bethel, J. L. Horsman, S. S. Hubbard, H. Krishnan, A. Romosan, E. H. Keating, L. Monroe, R. Strelitz, P. Moore, G. Taylor, B. Torkian, T. C. Johnson, and I. Gorton, “Visual Data Analysis as an Integral Part of Environmental Management,” IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 12, pp. 2088–2094, Dec. 2012. LBNL-6599E.
  2. M. Wan, W. H. Matthaeus, H. Karimabadi, V. Roytershteyn, M. Shay, P. Wu, W. Daughton, B. Loring, and S. C. Chapman, “Intermittent dissipation at kinetic scales in collisionless plasma turbulence,” Physical Review Letters, vol. 109, no. 19, Nov. 2012.
  3. H. Childs, D. Pugmire, S. Ahern, B. Whitlock, M. Howison, Prabhat, G. Weber, and E. W. Bethel, “Visualization at Extreme Scale Concurrency,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 291–306, Nov. 2012. LBNL-6321E.
  4. E. W. Bethel, D. Camp, H. Childs, C. Garth, M. Howison, K. I. Joy, and D. Pugmire, “Hybrid Parallelism,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 261–290, Nov. 2012. LBNL-6326E.
  5. H. Childs, K.-L. Ma, H. Yu, B. Whitlock, J. Meredith, J. Favre, S. Klasky, N. Podhorszki, K. Schwan, M. Wolf, M. Parashar, and F. Zhang, “In Situ Processing,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 171–198, Nov. 2012. LBNL-6322E.
  6. E. W. Bethel and M. Howison, “Performance Optimization and Auto-tuning,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 307–329, Nov. 2012. LBNL-6466E.
  7. O. Rübel, E. W. Bethel, Prabhat, and K. Wu, “Query-Driven Visualization and Analysis,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 117–144, Nov. 2012. LBNL-6323E.
  8. E. W. Bethel and M. Miller, “Remote and Distributed Visualization Architectures,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 25–48, Nov. 2012. LBNL-6325E.
  9. C. Hansen, E. W. Bethel, T. Ize, and C. Brownlee, “Rendering,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 49–60, Nov. 2012. LBNL-6324E.
  10. H. Childs, E. Brugger, B. Whitlock, J. Meredith, S. Ahern, D. Pugmire, K. Biagas, M. Miller, G. H. Weber, H. Krishnan, T. Fogal, A. Sanderson, C. Garth, E. W. Bethel, D. Camp, O. Rübel, M. Durant, J. Favre, and P. Navratil, “VisIt: An End-User Tool for Visualizing and Analyzing Very Large Data,” in High Performance Visualization—Enabling Extreme-Scale Scientific Insight, E. W. Bethel, H. Childs, and C. Hansen, Eds. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, pp. 357–372, Nov. 2012. LBNL-6320E.
  11. E. W. Bethel, H. Childs, and C. Hansen, Eds., High Performance Visualization—Enabling Extreme-Scale Scientific Insight. Boca Raton, FL, USA: CRC Press/Francis–Taylor Group, Nov. 2012. \urlhttp://www.crcpress.com/product/isbn/9781439875728.
  12. E. W. Bethel and M. Howison, “Multi-core and Many-core Shared-memory Parallel Raycasting Volume Rendering Optimization and Tuning,” International Journal of High Performance Computing Applications, vol. 26, no. 4, pp. 399–412, Nov. 2012. lbnl-5362e.
  13. D. Camp, H. Childs, C. Garth, D. Pugmire, and K. I. Joy, “Parallel Stream Surface Computation for Large Data Sets,” in Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV), pp. 39–47, Oct. 2012.
  14. G. H. Weber, H. Childs, and J. S. Meredith, “Efficient Parallel Extraction of Crack-free Isosurfaces from Adaptive Mesh Refinement (AMR) Data,” in Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV), pp. 31–38, Oct. 2012. LBNL-5799E.
  15. O. Rübel, C. G. R. Geddes, M. Chen, E. Cormier-Michel, and E. W. Bethel, “Query-driven Analysis of Plasma-based Particel Acceleration Data,” in Poster Abstracts of IEEE VisWeek 2012, Oct. 2012. LBNL-5906E.
  16. E. W. Bethel, R. Ross, W.-K. Liao, Prabhat, K. Schuchardt, P.-T. Bremer, O. Rübel, S. Byna, K. Wu, F. Li, M. Wehner, J. Patchett, H.-W. Shen, D. Pugmire, and D. Williams, “Recent Advances in Visual Data Exploration and Analysis of Climate Data,” in SciDAC 3 Principal Investigator Meeting, Rockville, MD, USA, Sep. 2012. Poster.
  17. E. W. Bethel, S. Byna, J. Chou, E. Cormier-Michel, C. G. R. Geddes, M. Howison, F. Li, Prabhat, J. Qiang, O. Rübel, R. D. Ryne, M. Wehner, and K. Wu, “Big Data Analysis and Visualization: What Do LINACS and Tropical Storms Have In Common?,” in 11th International Computational Accelerator Physics Conference, ICAP 2012, Rostock-Warnemünde, Germany, Aug. 2012. LBNL-5766E.
  18. M. Balman, E. Pouyoul, Y. Yao, E. W. Bethel, B. Loring, Prabhat, J. Shalf, A. Sim, and B. L. Tierney, “Experiences with 100Gbps network applications,” in DIDC’12 - 5th International Workshop on Data-Intensive Distributed Computing, pp. 33–42, Jul. 2012.
  19. Prabhat, O. Rübel, S. Byna, K. Wu, F. Li, M. Wehner, and E. W. Bethel, “TECA: A Parallel Toolkit for Extreme Climate Analysis,” in Third Worskhop on Data Mining in Earth System Science (DMESS 2012) at the International Conference on Computational Science (ICCS 2012), Omaha, Nebraska, Jun. 2012.
  20. A. R. Sanderson, B. Whitlock, O. Rübel, H. Childs, G. H. Weber, Prabhat, and K. Wu, “A System for Query Based Analysis and Visualization,” in Third International Eurovis Workshop on Visual Analytics (EuroVA) 2012, Vienna, Austria, Jun. 2012. LBNL-5507E.
  21. K. L. Schuchardt, D. A. Agarwal, S. A. Finsterle, C. W. Gable, I. Gorton, L. J. Gosink, E. H. Keating, C. S. Lansing, J. Meyer, W. A. M. Moeglein, G. S. H. Pau, E. A. Porter, S. Purohit, M. L. Rockhold, A. Shoshani, and C. Sivaramakrishnan, “Akuna - Integrated Toolsets Supporting Advanced Subsurface Flow and Transport Simulations for Environmental Management,” in XIX International Conference on Computational Methods in Water Resources (CMWR 2012), University of Illinois at Urbana-Champaign, Jun. 2012. LBNL publication number pending.
  22. M. Balman, E. Pouyoul, Y. Yao, B. L. E. Wes Bethel, Prabhat, J. Shalf, A. Sim, and B. L. Tierney, “Experiences with 100G Network Applications,” in Proceedings of the 5th International Workshop on Data Intensive and Distributed Computing (DIDC 2012), Delft, Netherlands, Jun. 2012.
  23. P. Navratil, D. Fussell, C. Lin, and H. Childs, “Dynamic Scheduling for Large-Scale Distributed-Memory Ray Tracing,” in Proceedings of EuroGraphics Symposium on Parallel Graphics and Visualization, pp. 61–70, May 2012. Best paper award.
  24. G. H. Weber, D. Morozov, K. Beketayev, J. Bell, P.-T. Bremer, M. Day, B. Hamann, C. Heine, M. Haranczyk, M. Hlawitschka, V. Pascucci, P. Oesterling, and G. Scheuermann, “Topology-based Visualization and Analysis of High-dimensional Data and Time-varying Data at the Extreme Scale,” in DOE Exascale Research Conference, Portland, OR, Apr. 2012. LBNL-5691E-Poster.
  25. G. H. Weber and P.-T. Bremer, “In-situ Analysis: Challenges and Opportunities,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-5692E, Apr. 2012. Position paper for DOE Exascale Research Conference in Portland, OR.
  26. G. H. Weber, K. Beketayev, P.-T. Bremer, B. Hamann, M. Haranczyk, M. Hlawitschka, and V. Pascucci, “Comprehensible Presentation of Topological Information,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-5693E, Apr. 2012. Status report for DOE Exascale Research Conference in Portland, OR.
  27. E. W. Bethel, D. Camp, H. Childs, M. Howison, H. Krishnan, B. Loring, J. Meyer, Prabhat, O. Rübel, D. Ushizima, and G. Weber, “Towards Exascale: High Performance Visualization and Analytics – Project Status Report,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-5767E, Apr. 2012.
  28. M. Wehner, S. Byna, Prabhat, T. Yopes, and J. Wu, “Atmospheric Rivers in the CMIP3/5 Historical and Projection Simulations,” in World Climate Research Programme (WCRP) Workshop on CMIP5 Model Analysis, Honolulu, HI, USA, Mar. 2012. Poster.
  29. D. M. Ushizima, G. H. Weber, D. Morozov, E. W. Bethel, and J. A. Sethian, “Algorithms for Microstructure Description Applied to Microtomography,” in Carbon Cycle 2.0 Symposium, Feb. 2012.
  30. O. Rübel, S. V. E. Keränen, M. D. Biggin, D. W. Knowles, G. H. Weber, H. Hagen, B. Hamann, and E. W. Bethel, “Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data,” in Visualization in Medicine and Life Sciences II, Progress and New Challenges, L. Linsen, B. Hamann, H. Hagen, and H.-C. Hege, Eds. Heidelberg, Germany: Springer Verlag, pp. 267–285, Jan. 2012. LBNL-4891E.
  31. M. Howison, E. W. Bethel, and H. Childs, “Hybrid Parallelism for Volume Rendering on Large, Multi, and Many-core Systems,” IEEE Transactions on Visualization and Computer Graphics, vol. 18, no. 1, pp. 17–29, Jan. 2012. LBNL-4370E.
  32. J. Kim, R. L. Martin, O. Rübel, M. Haranczyk, and B. Smit, “High-Throughput Characterization of Porous Materials Using Graphics Processing Units,” Journal of Chemical Theory and Computation, vol. 8, no. 5, pp. 1684–1693, 2012. PMID: 26593662.
  33. S. Byna, J. Chou, O. Rübel, Prabhat, H. Karimabadi, W. S. Daughter, V. Roytershteyn, E. W. Bethel, M. Howison, K.-J. Hsu, K.-W. Lin, A. Shoshani, A. Uselton, and K. Wu, “Parallel I/O, analysis, and visualization of a trillion particle simulation,” in SC ’12: Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, pp. 1–12, 2012.
  34. S. Gerber, O. Rübel, P.-T. Bremer, V. Pascucci, and R. T. Whitaker, “Morse-Smale Regression,” Journal of Computational and Graphical Statistics, vol. 22, no. 1, pp. 193–214, 2012.
  35. E. W. Bethel, D. Leinweber, O. Rübel, and K. Wu, “Federal Market Information Technology in the Post Flash Crash Era: Roles of Supercomputing,” The Journal of Trading, vol. 7, no. 2, pp. 9–25, 2012. LBNL-5263E.
  36. E. W. Bethel, “Exploration of Optimization Options for Increasing Performance of a GPU Implementation of a Three-Dimensional Bilateral Filter,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-5406E, 2012.
  37. D. M. Ushizima, D. Morozov, G. H. Weber, A. G. C. Bianchi, J. A. Sethian, and E. W. Bethel, “Augmented Topological Descriptors of Pore Networks for Material Science,” IEEE Transactions on Visualization and Computer Graphics (Proc. IEEE Vis 2012), vol. 18, no. 12, pp. 2041–2050, 2012. LBNL-5964E.
  38. K. Beketayev, G. H. Weber, D. Morozov, A. Abzhanov, and B. Hamann, “Geometry-Preserving Topological Landscapes,” in Proceedings of the Workshop at SIGGRAPH Asia 2012, New York, NY, USA, pp. 155–160, 2012. LBNL-6082E.
  39. D. Demir, K. Beketayev, G. H. Weber, P.-T. Bremer, V. Pascucci, and B. Hamann, “Topology Exploration with Hierarchical Landscapes,” in Proceedings of the Workshop at SIGGRAPH Asia 2012, New York, NY, USA, pp. 147–154, 2012. LBNL-6083E.
  40. K. P. Gaither, H. Childs, K. Schulz, C. Harrison, B. Barth, D. Donzis, and P. K. Yeung, “Using Visualization and Data Analysis to Understand Critical Structures in Massive Time Varying Turbulent Flow Simulations,” IEEE Computer Graphics and Applications, vol. 32, no. 4, pp. 34–45, 2012.

2011

  1. W. Harvey, O. Rübel, V. Pascucci, P. T. Bremer, and Y. Wang, “Enhanced Topology-Sensitive Clustering by Reeb Graph Shattering,” in Topological Methods in Data Analysis and Visualization II. Mathematics and Visualization, Nov. 2011.
  2. J. Chou, K. Wu, O. Rübel, M. Howison, Ji Qiang, Prabhat, B. Austin, E. W. Bethel, R. D. Ryne, and A. Shoshani, “Parallel index and query for large scale data analysis,” in SC ’11: Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1–11, Nov. 2011.
  3. M.-Y. Huang, L. Mackey, S. V. E. Keränen, G. H. Weber, M. I. Jordan, D. W. Knowles, M. D. Biggin, and B. Hamann, “Visually Relating Gene Expression and in vivo DNA Binding Data,” in Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine 2011 (IEEE BIBM 2011), Los Alamitos, California, pp. 586–589, Nov. 2011. LBNL-5423E.
  4. E. W. Bethel, D. Leinweber, O. Rübel, and K. Wu, “Federal Market Information Technology in the Post Flash Crash Era: Roles of Supercomputing,” in Workshop on High Performance Computational Finance at SC11, Seattle, WA, USA, Nov. 2011. LBNL-5263E.
  5. D. Camp, C. Garth, H. Childs, D. Pugmire, and K. I. Joy, “Streamline Integration Using MPI-Hybrid Parallelism on a Large Multicore Architecture,” IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 11, pp. 1702–1713, Nov. 2011.
  6. Prabhat, S. Byna, C. Paciorek, G. Weber, K. Wu, T. Yopes, M. Wehner, W. Collins, G. Ostrouchov, R. Strelitz, and E. W. Bethel, “Pattern Detection and Extreme Value Analysis on Large Climate Data,” in DOE/BER Climate and Earth System Modeling PI Meeting, Washington, DC, USA, Sep. 2011. Poster.
  7. C. Paciorek, M. Wehner, and Prabhat, “Computationally-efficient Spatial Analysis of Precipitation Extremes Using Local Likelihood,” in Statistical and Applied Mathematical Sciences Institute Uncertainty Quantification program, Climate Modeling Opening Workshop, Pleasanton, CA, USA, Aug. 2011. Poster.
  8. M. Philpott, Prabhat, and Y. Kawazoe, “Magnetism and Bonding in Graphene Nanodots with H modified Interior, Edge and Apex,” J. Chem Physics, vol. 135, no. 8, Aug. 2011.
  9. D. M. Ushizima, G. H. Weber, J. Ajo-Franklin, Y. Kim, A. Macdowell, D. Morozov, P. Nico, D. Parkinson, D. Trebotich, J. Wan, and B. E.W., “Analysis and Visualization for Multiscale Control of Geologic CO2,” in Journal of Physics: Conference Series, Proceedings of SciDAC 2011, Denver, CO, USA, Jul. 2011. LBNL-4948E.
  10. G. H. Weber, P.-T. Bremer, A. Gyulassy, and Valerio Pascucci, “Topology-based Feature Definition and Analysis,” in Numerical Modeling of Space Plasma Flows—ASTRONUM-2010, pp. 292–297, vol. 444, Jun. 2011. Conference held June 2010 in San Diego, CA, USA. LBNL-5020E..
  11. K. Beketayev, G. H. Weber, M. Haranczyk, P.-T. Bremer, M. Hlawitschka, and B. Hamann, “Topology-based Visualization of Transformation Pathways in Complex Chemical Systems,” Computer Graphics Forum (Special Issue, Proceedings Eurographics/IEEE Symposium on Visualization), pp. 663–672, May 2011. LBNL-5242E.
  12. R. Martin, Prabhat, D. Donofrio, and M. Haranczyk, “Accelerating Analysis of void spaces in porous materials on multicore and GPU platforms,” International Journal of High Performance Computing Applications, Feb. 2011.
  13. E. W. Bethel, J. van Rosendale, D. Southard, K. Gaither, H. Childs, E. Brugger, and S. Ahern, “Visualization at Supercomputing Centers: The Tale of Little Big Iron and the Three Skinny Guys,” IEEE Computer Graphics and Applications, vol. 31, no. 1, pp. 90–95, Jan. 2011. LBNL-4180E.
  14. Prabhat, Q. Koziol, K. Schuchardt, E. W. Bethel, J. Chuo, M. Howison, M. McGreevy, B. Palmer, O. Rübel, and J. Wu, “ExaHDF5: An I/O Platform for Exascale Data Models, Analysis and Performance,” in SciDAC 2011, 2011. Invited Paper.
  15. M. Haranczyk, R. Martin, Prabhat, and J. Sethian, “Computational Approaches for the High-Throughput Analysis of Porous materials for Energy related applications,” in SciDAC 2011, 2011. Invited Paper.
  16. R. Martin, T. Willems, C. Rycroft, Prabhat, M. Kazi, and M. Haranczyk, “High Throughput structure analysis and descriptor generation for crystalline porous materialsi,” International Conference on Chemical Structures, 2011. Poster.
  17. R. Martin, Prabhat, M. Haranczyk, and J. Sethian, “PDE-based analysis of void space of porous materials on multicore CPUs,” Manycore and Accelerator-based High-performance Scientific Computing, 2011. Poster.
  18. Prabhat, D. Zubarev, and W. A. Lester, “Statistical Exploration of Electronic Structure of Molecules from Quantum Monte Carlo Simulations,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-4564E, 2011.
  19. J. Chou, K. Wu, and Prabhat, “FastQuery: A general Index and Query system for scientific data,” in Scientific and Statistical Database Management Conference, 2011. Poster.
  20. S. Byna, Prabhat, M. F. Wehner, and K. J. Wu, “Detecting atmospheric rivers in large climate datasets,” in Proceedings of the 2nd international workshop on Petascal data analytics: challenges and opportunities, New York, NY, USA, pp. 7–14, 2011.
  21. J. Chou, K. Wu, and Prabhat, “FastQuery: A Parallel Indexing System for Scientific Data,” in Proceedings of the 2011 IEEE International Conference on Cluster Computing, Washington, DC, USA, pp. 455–464, 2011.
  22. J. Chou, K. Wu, and Prabhat, “Design of FastQuery: how to generalize Indexing and Querying systems for scientific data,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL publication number pending, 2011.
  23. P.-T. Bremer, G. H. Weber, J. Tierny, V. Pascucci, M. S. Day, and J. B. Bell, “Interactive Exploration and Analysis of Large Scale Turbulent Combustion Using Topology-based Data Segmentation,” IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 9, pp. 1307–1324, 2011. LBNL-5921E.
  24. D. Camp, H. Childs, A. Chourasia, C. Garth, and K. I. Joy, “Evaluating the Benefits of An Extended Memory Hierarchy for Parallel Streamline Algorithms,” in Proceedings of the IEEE Symposium on Large-Scale Data Analysis and Visualization (LDAV), 2011.
  25. G. H. Weber, P.-T. Bremer, M. S. Day, J. B. Bell, and V. Pascucci, “Feature Tracking Using Reeb Graphs,” in Topological Methods in Data Analysis and Visualization: Theory, Algorithms, and Applications, pp. 241–253, 2011. LBNL-4226E.
  26. E. Deines, G. H. Weber, C. Garth, B. Van Straalen, S. Borovikov, D. F. Martin, and K. Joy, “On the Computation of Integral Curves in Adaptive Mesh Refinement Vector Fields,” in Scientific Visualization: Interactions, Features, Metaphors, pp. 73–91, vol. 2, 2011. LBNL-4972E.
  27. G. H. Weber, P.-T. Bremer, and V. Pascucci, “Topological Cacti: Visualizing Contour-based Statistics,” in Topological Methods in Data Analysis and Visualization II, Heidelberg, Germany: Springer Verlag, pp. 63–76, 2011. LBNL-5018E.
  28. B. MacCarthy, H. Carr, and G. H. Weber, “Topological Galleries: A High Level User Interface for Topology Controlled Volume Rendering,” Lawerence Berkeley National Laboratory, LBNL-5019E, 2011.
  29. L. J. Gosink, C. Garth, J. C. Anderson, E. W. Bethel, and K. I. Joy, “An Application of Multivariate Statistical Analysis for Query-Driven Visualization,” IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 3, pp. 264–275, 2011. LBNL-3536E.

2010

  1. P. Oesterling, G. Scheuermann, S. Teresniak, G. Heyer, S. Koch, T. Ertl, and G. H. Weber, “Two-stage Framework for a Topology-Based Projection and Visualization of Classified Document Collections,” in Proceedings IEEE Symposium on Visual Analytics Science and Technology (IEEE VAST), pp. 91–98, Oct. 2010. LBNL-4074E.
  2. M. Howison, Q. Koziol, D. Knaak, J. Mainzer, and J. Shalf, “Tuning HDF5 for Lustre File Systems,” in Proceedings of 2010 Workshop on Interfaces and Abstractions for Scientific Data Storage (IASDS10), Heraklion, Crete, Greece, Sep. 2010. LBNL-4803E.
  3. M. Howison, A. Adelmann, E. W. Bethel, A. Gsell, B. Oswald, and Prabhat, “H5hut: A High-Performance I/O Library for Particle-Based Simulations,” in Proceedings of 2010 Workshop on Interfaces and Abstractions for Scientific Data Storage (IASDS10), Heraklion, Crete, Greece, Sep. 2010. LBNL-4021E.
  4. M. Howison, E. W. Bethel, and H. Childs, “Hybrid Parallelism for Volume Rendering on Large, Multi-core Systems,” in Proceedings of SciDAC 2010, Chattanooga, TN, USA, Jul. 2010. LBNL-4024E.
  5. M. Howison, E. W. Bethel, and H. Childs, “Hybrid Parallelism for Volume Rendering on Large, Multi-core Systems,” in Proceedings of Astronum 2010, San Diego, CA, USA, Jun. 2010. LBNL-4024E-Conf.
  6. T. Fogal, H. Childs, S. Shankar, J. Krüger, R. D. Bergeron, and P. Hatcher, “Large Data Visualization on Distributed Memory Multi-GPU Clusters,” in Proceedings of High Performance Graphics 2010, pp. 57–66, Jun. 2010.
  7. O. Rübel, S. Ahern, E. W. Bethel, M. D. Biggin, H. Childs, E. Cormier-Michel, A. DePace, M. B. Eisen, C. C. Fowlkes, C. G. R. Geddes, H. Hagen, B. Hamann, M.-Y. Huang, S. V. E. Keränen, D. W. Knowles, C. L. L. Hendriks, J. Malik, J. Meredith, P. Messmer, Prabhat, D. Ushizima, G. H. Weber, and K. Wu, “Coupling Visualization and Data Analysis for Knowledge Discovery from Multi-dimensional Scientific Data,” in Procedia Computer Science, Proceedings of International Conference on Computational Science, ICCS 2010, May 2010. LBNL-3669E.
  8. M. Isenburg, P. Lindstrom, and H. Childs, “Parallel and Streaming Generation of Ghost Data for Structured Grids,” IEEE Computer Graphics and Applications, vol. 30, no. 3, pp. 32–44, May 2010.
  9. M. Howison, E. W. Bethel, and H. Childs, “MPI-hybrid Parallelism for Volume Rendering on Large, Multi-core Systems,” in Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Norrköping, Sweden, May 2010. LBNL-3297E.
  10. H. Childs, D. Pugmire, S. Ahern, B. Whitlock, M. Howison, Prabhat, G. Weber, and E. W. Bethel, “Extreme Scaling of Production Visualization Software on Diverse Architectures,” IEEE Computer Graphics and Applications, vol. 30, no. 3, pp. 22–31, May 2010. LBNL-3403E.
  11. O. Rübel, G. H. Weber, M.-Y. Huang, E. W. Bethel, M. D. Biggin, C. C. Fowlkes, C. L. Hendriks, S. V. E. Keränen, M. B. Eisen, D. W. Knowles, J. Malik, H. Hagen, and B. Hamann, “Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data,” IEEE Transactions on Computational Biology and Bioinformatics, vol. 7, no. 1, pp. 64–79, Mar. 2010. LBNL-382E.
  12. P.-T. Bremer, G. H. Weber, V. Pascucci, M. S. Day, and J. B. Bell, “Analyzing and Tracking Burning Structures in Lean Premixed Hydrogen Flames,” IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 2, pp. 248–260, Mar. 2010. LBNL-2276E.
  13. O. Rübel, G. H. Weber, M.-Y. Huang, E. W. Bethel, M. D. Biggin, C. C. Fowlkes, C. L. Luengo Hendriks, S. V. E. Keränen, M. D. Eisen, D. Knowles, J. Malik, H. Hagen, and B. Hamann, “Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data,” IEEE Transactions on Computational Biology and Bioinformatics, vol. 7, no. 1, pp. 64–79, Jan. 2010.
  14. E. W. Bethel, “Using wesBench to Study the Rendering Performance of Graphics Processing Units,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-3025E, 2010.
  15. M.-Y. Huang, G. H. Weber, X.-Y. Li, M. D. Biggin, and B. Hamann, “Quantitative Visualization of ChIP-chip Data by Using Linked Views,” in Proceedings IEEE International Conference on Bioinformatics and Biomedicine 2010 (IEEE BIBM 2010) Workshops, Workshop on Integrative Data Analysis in Systems Biology (IDASB), Los Alamitos, California, pp. 195–200, 2010. LBNL-4491E.
  16. E. A. Carvalho, D. M. Ushizima, F. N. S. Medeiros, C. I. O. Martins, R. C. P. Marques, and I. N. S. Oliveira, “SAR imagery segmentation by statistical region growing and hierarchical merging,” Digital Signal Processing, vol. 20, no. 5, pp. 1365–1378 , 2010.
  17. J. Meredith and H. Childs, “Visualization and Analysis-Oriented Reconstruction of Material Interfaces,” Computer Graphics Forum (Proceedings of Eurographics/IEEE-VGTC Symposium on Visualization 2010 (EuroVis 2010)), vol. 29, no. 3, pp. 1241–1250, 2010.
  18. G. H. Weber, S. Ahern, E. W. Bethel, S. Borovikov, H. R. Childs, E. Deines, C. Garth, H. Hagen, B. Hamann, K. I. Joy, D. Martin, J. Meredith, Prabhat, D. Pugmire, O. Rübel, B. Van Straalen, and K. Wu, “Recent Advances in VisIt: AMR Streamlines and Query-Driven Visualization,” in Numerical Modeling of Space Plasma Flows: Astronum-2009 (Astronomical Society of the Pacific Conference Series), pp. 329–334, vol. 429, 2010. LBNL-3185E.
  19. D. M. Ushizima, C. G. Geddes, E. Cormier-Michel, E. W. Bethel, J. Jacobsen, Prabhat, O. Rubel, G. H. Weber, B. Hamann, P. Messmer, and H. Hagen, “Automated Detection and Analysis of Particle Beams in Laser-Plasma Accelerator Simulations,” in Machine Learning, Y. Zhang, Ed. Rijeka, Croatia: IntechOpen, 2010. LBNL-3845E.

2009

  1. P.-T. Bremer, G. H. Weber, J. Tierny, V. Pascucci, M. S. Day, and J. B. Bell, “A Topological Framework for the Interactive Exploration of Large Scale Turbulent Combustion,” in Proceedings of the 5th IEEE International Conference on e-Science, Oxford, UK, pp. 247–254, Dec. 2009. LBNL-3183E.
  2. O. Rübel, Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-energy Physics, vol. 28. Der Dekan (hrsg), Fachbereich Informatik, Technische Universität Kaiserslautern, Dec. 2009.
  3. E. W. Bethel, H. Childs, A. Mascarenhas, V. Pascucci, and Prabhat, “Scientific Data Managment Challenges in High Performance Visual Data Analysis,” in Scientific Data Management: Challenges, Existing Technology, and Deployment, A. Shoshani and D. Rotem, Eds. Chapman & Hall/CRC Press, Dec. 2009. LBNL-1449E.
  4. O. Rübel, C. G. R. Geddes, E. Cormier-Michel, K. Wu, Prabhat, G. H. Weber, D. M. Ushizima, P. Messmer, H. Hagen, B. Hamann, and W. Bethel, “Automatic Beam Path Analysis of Laser Wakefield Particle Acceleration Data,” IOP Computational Science & Discovery, vol. 2, no. 015005 (38pp), Nov. 2009. LBNL-2734E.
  5. D. Pugmire, H. Childs, C. Garth, S. Ahern, and G. H. Weber, “Scalable Computation of Streamlines on Very Large Datasets,” in Proc. Supercomputing SC09, Portland, OR, USA, Nov. 2009. LBNL-3264E.
  6. N. Shah, S. E. Dillard, G. H. Weber, and B. Hamann, “Volume visualization of multiple alignment of large genomic DNA,” in Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration, T. Möller, B. Hamann, and R. Russell, Eds. Heidelberg, Germany: Springer-Verlag, pp. 325–342, Jul. 2009. LBNL-63126.
  7. M. Howison and C. Sequin, “CAD Tools for Creating Space-filling 3D Escher Tiles,” in Computer-Aided Design and Applications, Reno, NV, USA, pp. 737–748, vol. 6, Jun. 2009. LBNL-2467E.
  8. K. Wu, S. Ahern, E. W. Bethel, J. Chen, H. Childs, E. Cormier-Michel, C. G. R. Geddes, J. Gu, H. Hagen, B. Hamann, W. Koegler, J. Laurent, J. Meredith, P. Messmer, E. Otoo, V. Perevoztchikov, A. Poskanzer, Prabhat, O. Rübel, A. Shoshani, A. Sim, K. Stockinger, G. Weber, and W.-M. Zhang, “FastBit: Interactively Searching Massive Data,” Journal of Physics Conference Series, Proceedings of SciDAC 2009, vol. 180, p. 012053, Jun. 2009. LBNL-2164E.
  9. E. W. Bethel, C. Johnson, S. Ahern, J. Bell, P.-T. Bremer, H. Childs, E. Cormier-Michel, M. Day, E. Deines, T. Fogal, C. Garth, C. G. R. Geddes, H. Hagen, B. Hamann, C. Hansen, J. Jacobsen, K. Joy, J. Krüger, J. Meredith, P. Messmer, G. Ostrouchov, V. Pascucci, K. Potter, Prabhat, D. Pugmire, O. Rübel, A. Sanderson, C. Silva, D. Ushizima, G. Weber, B. Whitlock, and K. Wu., “Occam’s Razor and Petascale Visual Data Analysis,” Journal of Physics Conference Series, Proceedings of SciDAC 2009, vol. 180, p. 012084, Jun. 2009. LBNL-2210E.
  10. L. Gosink, K. Wu, E. W. Bethel, J. D. Owens, and K. I. Joy, “Data Parallel Bin-based Indexing for Answering Queries on Multi-core Architectures,” in 21st International Conference on Scientific and Statistical Database Management (SSDBM), pp. 110–129, vol. 5566, Jun. 2009. LBNL-2211E.
  11. M. Hlawitschka, G. H. Weber, A. Anwander, O. T. Carmichael, B. Hamann, and G. Scheuermann, “Interactive Volume Rendering of Diffusion Tensor Data,” in Visualization and Processing of Tensor Fields: Advances and Perspectives, Heidelberg, Germany: Springer-Verlag, pp. 161–176, Apr. 2009.
  12. S. E. Dillard, V. Natarajan, G. H. Weber, V. Pascucci, and B. Hamann, “Topology-guided Tessellation of Quadratic Elements,” International Journal of Computational Geometry & Applications (IJCGA), vol. 19, no. 2, pp. 195–211, Apr. 2009. A preliminary version of this paper appeared in Proceedings of the 17th International Symposium on Algorithms and Computation, Kolkata, India, Lecture Notes in Computer Science (LNCS) 4288, 2006, 722–731. LBNL-63771.
  13. G. H. Weber, O. Rübel, M.-Y. Huang, A. H. DePace, C. C. Fowlkes, S. V. E. Keränen, C. L. Luengo Hendriks, H. Hagen, D. W. Knowles, J. Malik, M. D. Biggin, and B. Hamann, “Visual Exploration of Three-dimensional Gene Expression using Physical Views and Linked Abstract Views,” IEEE Transactions on Computational Biology and Bioinformatics, vol. 6, no. 2, pp. 296–309, Apr. 2009. LBNL-63776.
  14. Y. Yang, D. P. Harris, F. Luo, W. Xiong, M. Joachimiak, L. Wu, P. Dehal, J. Jacobsen, A. V. Palumbo, A. P. Arkin, and J. Zhou, “Snapshot of iron response in Shewanella oneidensis by gene network reconstruction,” BMC Genomics 2009, vol. 10, no. 131, Mar. 2009.
  15. S. Borglin, D. Joyner, J. Jacobsen, A. Mukhopadhyay, and T. C. Hazen, “Overcoming the anaerobic hurdle in phenotype microarrays: Generation and visualization of growth curve data for Desulfovibrio vulgaris Hildenborough,” J. Microbiological Methods, vol. 76, no. 2, pp. 159–168, Feb. 2009.
  16. E. W. Bethel, “High Performance, Three-Dimensional Bilateral Filtering,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-1601E, 2009.
  17. C. Garth, E. Deines, K. I. Joy, E. W. Bethel, H. Childs, G. Weber, S. Ahern, D. Pugmire, A. Sanderson, and C. Johnson, “Twists and Turns: Vector Field Visual Data Analysis for Petascale Computational Science,” SciDAC Review, no. 15, pp. 10–21, 2009. LBNL-2983E.
  18. C. G. R. Geddes, E. Cormier-Michel, E. H. Esarey, C. B. Schroeder, J.-L. Vay, W. P. Leemans, D. L. Bruhwiler, J. R. Cary, B. Cowan, M. Durant, P. Hamill, P. Messmer, P. Mullowney, C. Nieter, K. Paul, S. Shasharina, S. Veitzer, G. Weber, O. Rübel, D. Ushizima, Prabhat, E. W.Bethel, and K. Wu, “Large Fields for Smaller Facility Sources,” SciDAC Review, no. 13, pp. 13–21, 2009. LBNL-2299E.

2008

  1. D. Ushizima, O. Rübel, Prabhat, G. Weber, E. W. Bethel, C. Aragon, C. Geddes, E. Cormier-Michel, B. Hamann, P. Messmer, and H. Hagen, “Automated Analysis for Detecting Beams in Laser Wakefield Simulations,” in 2008 Seventh International Conference on Machine Learning and Applications, Proceedings of IEEE ICMLA’08, pp. 382–387, Dec. 2008. LBNL-960E.
  2. O. Rübel, Prabhat, K. Wu, H. Childs, J. Meredith, C. G. R. Geddes, E. Cormier-Michel, S. Ahern, G. H. weber, P. Messmer, H. Hagen, B. Hamann, and E. W. Bethel, “High Performance Multivariate Visual Data Exploration for Extemely Large Data,” in SuperComputing 2008 (SC08), Austin, Texas, USA, Nov. 2008. LBNL-716E.
  3. L. J. Gosink, J. C. Anderson, E. W. Bethel, and K. I. Joy, “Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data,” IEEE Transactions on Visualization and Computer Graphics (Special Issue: Proceedings of IEEE Visualization 2008), vol. 14, no. 6, pp. 1715–1722, Nov. 2008. LBNL-803E.
  4. C. Aragon, S. Poon, G. Aldering, R. Thomas, and R. Quimby, “Using Visual Analytics to Maintain Situational Awareness in Astrophysics,” in Proceedings of 2008 IEEE Symposium on Visual Analytics Science and Technology, Oct. 2008. LBNL-658E.
  5. O. Rübel, Prabhat, K. Wu, H. Childs, J. Meredith, C. G. R. Geddes, E. Cormier-Michel, S. Ahern, G. H. Weber, P. Messmer, H. Hagen, B. Hamann, and E. W. Bethel, “Application of High-performance Visual Analysis Methods to Laser Wakefield Particle Acceleration Data,” IEEE Visualization 2008. Columbus, Ohio, USA, Oct-2008. LBNL-952E.
  6. E. W. Bethel, O. Rübel, Prabhat, K. Wu, G. H. Weber, V. Pascucci, H. Childs, A. Mascarenhas, J. Meredith, and S. Ahern, “Modern Scientific Visualization is More than Just Pretty Pictures,” in Numerical Modeling of Space Plasma Flows: Astronum-2008 (Astronomical Society of the Pacific Conference Series), St. Thomas, USVI, pp. 301–317, Jun. 2008. LBNL-1450E.
  7. C. Aragon, S. Bailey, S. Poon, K. Runge, and R. Thomas, “Sunfall: A Collbaroatvie Visual Analytics System for Astrophysics,” Journal of Physics Conference Series – SciDAC 2008, vol. 125, Jun. 2008. LBNL-657E.
  8. B. Paul, S. Ahern, E. W. Bethel, E. Brugger, R. Cook, J. Daniel, K. Lewis, J. Owen, and D. Southard, “Chromium Renderserver: Scalable and Open Remote Rendering Infrastructure,” IEEE Transactions on Visualization and Computer Graphics, vol. 14, no. 3, pp. 627–639, May 2008. LBNL-63693.
  9. C. C. Fowlkes, C. L. L. Hendriks, S. V. E. Keränen, G. H. Weber, O. Rübel, M.-Y. Huang, S. Chatoor, A. H. DePace, L. Simirenko, C. Henriquez, A. Beaton, R. Weiszmann, S. Celniker, B. Hamann, D. W. Knowles, M. D. Biggin, M. B. Eisen, and J. Malik., “A Quantitative Spatio-temporal Atlas of Gene Expression in the Drosophila Blastoderm,” Cell, vol. 133, no. 2, pp. 364–374, Apr. 2008.
  10. G. H. Weber, V. E. Beckner, H. Childs, T. J. Ligocki, M. Miller, B. van Straalen, and E. W. Bethel, “Visualization of Scalar Adaptive Mesh Refinement Data,” in Numerical Modeling of Space Plasma Flows: Astronum-2007 (Astronomical Society of the Pacific Conference Series), pp. 309–320, vol. 385, Apr. 2008. LBNL-220E.
  11. M.-Y. Huang, O. Rübel, G. H. Weber, C. L. Luengo Hendriks, M. D. Biggn, H. Hagen, and B. Hamann, “Segmenting Gene Expression Patterns of Early-stage Drosophila Embryos,” in Mathematical Methods for Visualization in Medicine and Life Sciences, Heidelberg, Germany: Springer Verlag, pp. 313–327, Jan. 2008. LBNL-62450.
  12. O. Rübel, Prabhat, Kesheng Wu, H. Childs, J. Meredith, C. G. R. Geddes, E. Cormier-Michel, S. Ahern, G. H. Weber, P. Messmer, H. Hagen, B. Hamann, and E. Wes Bethel, “High performance multivariate visual data exploration for extremely large data,” in SC ’08: Proceedings of the 2008 ACM/IEEE Conference on Supercomputing, pp. 1–12, 2008.
  13. R. C. P. Marques, F. N. S. Medeiros, and D. M. Ushizima, “Target Dectection on SAR Images Using Level Set Methods,” IEEE Transactions on Systems, Man and Cybernetics, vol. (to appear), 2008. LBNL-958E.
  14. J. Chen, I. Yoon, and E. W. Bethel, “Interactive, Internet Delivery of Visualization via Structured, Prerendered Multiresolution Imagery,” IEEE Transactions in Visualization and Computer Graphics, vol. 14, no. 2, pp. 302–312, 2008. LBNL-62252.
  15. O. Rübel, G. H. Weber, M.-Y. Huang, E. W. Bethel, S. V. E. Keränen, C. C. Fowlkes, C. L. L. Hendriks, A. H. DePace, L. Simirenko, M. B. Eisen, M. D. Biggin, H. Hagen, J. Malik, D. W. Knowles, and B. Hamann, “PointCloudXplore 2: Visual Exploration of 3D Gene Expression,” in Visualization of Large and Unstructured Data Sets, C. Garth, H. Hagen, and M. Hering-Bertram, Eds. Gesellschaft fuer Informatik (GI), 2008. LBNL-249E.
  16. E. W. Bethel, C. Johnson, C. Hansen, C. Silva, S. Parker, A. Sanderson, L. Myers, M. Cole, X. Tricoche, S. Ahern, G. Ostrouchov, D. Pugmire, J. Daniel, J. Meredith, V. Pascucci, H. Childs, P.-T. Bremer, A. Mascarenhas, K. Joy, B. Hamann, C. Garth, C. Aragon, G. Weber, and Prabhat, “Seeing the Unseeable,” SciDAC Review, no. 8, pp. 24–33, 2008. LBNL-472E.

2007

  1. L. Gosink, J. C. Anderson, E. W. Bethel, and K. I. Joy, “Variable Interactions in Query-Driven Visualization,” IEEE Transactions on Visualization and Computer Graphics (Proceedings of Visualization 2007), vol. 13, no. 6, pp. 1400–1407, Nov. 2007. LBNL-63524.
  2. G. H. Weber, P.-T. Bremer, and V. Pascucci, “Topological Landscapes: A Terrain Metaphor for Scientific Data,” IEEE Transactions on Visualization and Computer Graphics (Special Issue: Proceedings of IEEE Visualization 2007), vol. 13, no. 6, pp. 1416–1423, Nov. 2007. LBNL-63763.
  3. S. Bailey, C. Aragon, R. Romano, R. C. Thomas, B. A. Weaver, and D. Wong, “How to Find More Supernovae with Less Work: Object Classification Techniques for Difference Imaging,” Astrophysical Journal, vol. 665, pp. 1246–1253, Aug. 2007.
  4. F. Reiss, K. Stockinger, K. Wu, A. Shoshani, and J. Hellerstein, “Enabling Real-Time Querying of Live and Historical Data Stream,” in International Conference on Scientific and Statistical Database Management (SSDBM 2007), Banff, Canada, Jul. 2007. LBNL-61080.
  5. O. G. Staadt, V. Natarjan, G. H. Weber, D. F. Wiley, and B. Hamann, “Interactive Processing and Visualization of Image Data for Biomedical and Life Science Applications,” BMC Cell Biology, vol. 8 (Suppl 1), no. S10 (10 July), Jul. 2007. LBNL-63127.
  6. J. S. Jacobsen, D. C. Joyner, S. E. Borglin, T. C. Hazen, A. P. Arkin, and E. W. Bethel, “Visualization of Growth Curve Data from Phenotype Microarray Experiments,” in Information Visualization, 2007. IV ’07. 11th International Conference., pp. 535–544, Jul. 2007. LBNL-63251.
  7. E. W. Bethel, C. Johnson, K. Joy, S. Ahern, V. Pascucci, H. Childs, J. Cohen, M. Duchaineau, B. Hamann, C. Hansen, D. Laney, P. Lindstrom, J. Meredith, G. Ostrouchov, S. Parker, C. Silva, A. Sanderson, and X. Tricoche, “SciDAC Visualization and Analytics Center for Enabling Technology,” Journal of Physics Conference Series – SciDAC 2007, vol. 78, p. 012032, Jun. 2007. LBNL-63542.
  8. G. H. Weber, S. E. Dillard, H. Carr, V. Pascucci, and B. Hamann, “Topology-Controlled Volume Rendering,” IEEE Transactions on Visualization and Computer Graphics, vol. 13, no. 2, pp. 330–341, Mar. 2007. LBNL-63120.
  9. R. C. Thomas, G. Aldering, P. Antilogus, C. Aragon, S. Bailey, C. Baltay, E. Baron, A. Bauer, C. Buton, S. Bongard, Y. Copin, E. Gangler, S. Gilles, R. Kessler, S. Loken, P. Nugent, R. Pain, J. Parrent, E. Pécontal, R. Pereira, S. Perlmutter, D. Rabinowitz, G. Rigaudier, K. Runge, R. Scalzo, G. Smadja, L. Wang, and B. A. Weaver, “Nearby Supernova Factory Observations of SN 2006D: On Sporadic Carbon Signatures in Early Type Ia Supernova Spectra,” \apjl, vol. 654, pp. L53–L56, Jan. 2007.
  10. C. Aragon and D. Aragon, “A Fast Contour Descriptor Algorithm for Supernova Image Classification,” in Proceedings of 2007 SPIE/IS&T Conference on Electronic Imaging, Volume 6469-07, 2007. http://vis.lbl.gov/Publications/2007/LBNL-61182.pdf.
  11. Gu, I. Anderson, V. Kunin, M. Cipriano, S. Minovitsky, G. H. Weber, N. Amenta, B. Hamann, and I. Dubchak, “TreeQ-VISTA: An Interactive Tree Visualization Tool with Functional Annotation Query Capabilities,” Bioinformatics, vol. 23, no. 6, pp. 764–766, 2007. LBNL-61863.
  12. C. Aragon and S. Poon, “The Impact of Usability on Supernova Discovery,” in ACM Conference on Human Factors in Computing Systems, 2007. http://vis.lbl.gov/Publications/2007/LBNL-61182.pdf.
  13. G. H. Weber, V. E. Beckner, H. Childs, T. J. Ligocki, M. Miller, B. van Straalen, and E. W. Bethel, “Visualization Tools for Adaptive Mesh Refinement Data,” in Proceedings of the 4th High End Visualization Workshop, Berlin, Germany, pp. 12–25, 2007. LBNL-62954.
  14. A. Adelmann, A. Gsell, B. Oswald, T. Schietinger, E. W. Bethel, J. Shalf, C. Siegerist, and K. Stockinger, “Progress on H5Part: A Portable High Performance Parallel Data Interface for Electromagnetic Simulations,” in Particle Accelerator Conference PAC07 25–29 June 2007, Albuquerque NM, 2007. http://vis.lbl.gov/Publications/2007/LBNL-63042.pdf.
  15. L. Hendriks, C. C. Fowlkes, S. V. E. Keränen, L. Simirenko, G. Weber, O. Rübel, M.-Y. Huang, A. DePace, C. Henriquez, X.-Y. Li, H. C. Chu, D. W. Kaszuba, A. Beaton, S. E. Celniker, B. Hamann, M. B. Eisen, J. Malik, D. W. Knowles, and M. D. Biggin, “Virtual Embryos as Tools for 3D Gene Expression Analyses,” in Program and Abstracts Volume of the 48th Annual Drosophila Research Conference, Bethesda, Maryland, p. 203, 2007. LBNL-63062.
  16. G. Weber, H. Childs, K. Bonnell, J. Meredith, M. Miller, B. Whitlock, and E. W. Bethel, “Production-quality Tools for Adaptive Mesh Refinement Visualization,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-63657, 2007.
  17. E. W. Bethel, O. Rübel, G. Weber, B. Hamann, and H. Hagen, “Visualization and Analysis of 3D Gene Expression Data,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-63658, 2007.
  18. E. W. Bethel, L. Gosink, and K. I. Joy, “Variable Interactions in Query-Driven Visualization,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-63674, 2007.
  19. E. W. Bethel, J. Chen, and I. Yoon, “Interactive, Internet Delivery of Visualization via Structured, Prerendered Imagery,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-63675, 2007.
  20. E. W. Bethel, C. Johnson, C. Aragon, Prabhat, O. Rübel, G. Weber, V. Pascucci, H. Childs, P.-T. Bremer, B. Whitlock, S. Ahern, J. Meredith, G. Ostrouchov, K. Joy, B. Hamann, C. Garth, M. Cole, C. Hansen, S. Parker, A. Sanderson, C. Silva, and X. Tricoche, “DOE’s SciDAC Visualization and Analytics Center for Enabling Technologies – Strategy for Petascale Visual Data Analysis Success,” CTWatch Quarterly, vol. 3, no. 4, pp. 32–40, 2007. LBNL-63701.
  21. K. I. Joy, M. Miller, H. Childs, E. W. Bethel, J. Clyne, G. Ostrouchov, and S. Ahern, “Frameworks for Visualization at the Extreme Scale,” Journal of Physics Conference Series – SciDAC 2007, vol. 78, p. 012035, 2007. LBNL-63762.
  22. C. Aragon, S. Bailey, S. Poon, K. Runge, and R. Thomas, “Sunfall: A Collaborative Visual Analytics System for Astrophysics,” in IEEE VAST, 2007.

2006

  1. S. J. Bailey, G. Aldering, C. Aragon, S. Bongard, M. Childress, S. Loken, P. Nugent, S. Perlmutter, K. Runge, R. Scalzo, R. Romano, R. Thomas, B. Weaver, C. Baltay, A. Bauer, D. Herrera, D. Rabinowitz, E. Pecontal, G. Rigaudier, P. Antilogus, S. Gilles, R. Pain, R. Pereira, C. Buton, and Y. Copin, “How to Find More Supernovae with Less Work: Object Classification Techniques for Difference Imaging,” in Bulletin of the American Astronomical Society, pp. 1003-+, vol. 38, Dec. 2006.
  2. B. A. Weaver, G. Aldering, C. Aragon, S. Bailey, S. Bongard, M. J. Childress, S. Loken, P. Nugent, S. Perlmutter, R. Romano, K. Runge, R. Scalzo, R. C. Thomas, C. Baltay, A. Bauer, D. Herrera, D. Rabinowitz, E. Pecontal, G. Rigaudier, P. Antilogus, S. Gilles, R. Pain, R. Pereira, C. Buton, and Y. Copin, “The Nearby Supernova Factory,” in Bulletin of the American Astronomical Society, pp. 1100-+, vol. 38, Dec. 2006.
  3. R. Romano, C. Aragon, and C. Ding, “Supernova Recognition Using Support Vector Machines,” in Proceedings of the 5th International Conference on Machine Learning and Applications, Dec. 2006. http://vis.lbl.gov/Publications/2006/LBNL-61192.pdf.
  4. K. Stockinger, E. W. Bethel, S. Campbell, E. Dart, and K. Wu, “Detecting Distributed Scans Using High-Performance Query-Driven Visualization,” in SC ’06: Proceedings of the 2006 ACM/IEEE Conference on High Performance Computing, Networking, Storage and Analysis, Nov. 2006. LBNL-60053.
  5. E. W. Bethel, S. Campbell, E. Dart, K. Stockinger, and K. Wu, “Accelerating Network Traffic Analysis Using Query-Driven Visualization,” in Proceedings of 2006 IEEE Symposium on Visual Analytics Science and Technology, pp. 115–122, Oct. 2006. LBNL-59891.
  6. R. D. Ryne, J. Qiang, E. W. Bethel, I. Pogorelov, J. Shalf, C. Siegerist, M. Venturini, A. J. Dragt, A. Adelmann, D. Abell, J. Amundson, P. Spentzouris, F. Neri, P. Walstrom, C. T. Mottershead, and R. Samulyak, “Recent Progress on the Marylie/Impact Beam Dynamics Code,” in International Computational Accelerator Physics Conference, Oct. 2006. LBNL-62017.
  7. D. Abell, A. Adelmann, J. Amundson, A. Dragt, C. Mottershead, F. Neri, I. Pogorelov, J. Qiang, R. Ryne, J. Shalf, C. Siegerist, P. Spentzouris, E. Stern, M. Venturini, and P. Walstrom, “Beam dynamics,” Journal of Physics Conference Series, vol. 46, pp. 210–214, Sep. 2006. LBNL-61521.
  8. L. Gosink, J. Shalf, K. Stockinger, K. Wu, and E. W. Bethel, “HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices,” in Proceedings of the 18th International Conference on Scientific and Statistical Database Management, pp. 149–158, Jul. 2006. LBNL-59602.
  9. E. W. Bethel, S. Campbell, E. Dart, J. Shalf, K. Stockinger, and K. Wu, “High Performance Visualization Using Query-Driven Visualization and Analytics,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL/PUB-959, Jul. 2006.
  10. K. Wu, K. Stockinger, A. Shoshani, and E. W. Bethel, “Fastbit – Helps Finding the Proverbial Needle in a Haystack,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL/PUB-963, Jul. 2006.
  11. E. W. Bethel, C. Johnson, C. Hansen, S. Parker, A. Sanderson, C. Silva, X. Tricoche, V. Pascucci, H. Childs, J. Cohen, M. Duchaineau, D. Laney, P. Lindstrom, S. Ahern, J. Meredith, G. Ostrouchov, K. Joy, and B. Hamann, “VACET: Proposed SciDAC2 Visualization and Analytics Center for Enabling Technologies,” Journal of Physics Conference Series – SciDAC 2006, vol. 46, pp. 561–569, Jun. 2006. LBNL-60413.
  12. O. Rübel, G. Weber, S. V. E. Keränen, C. C. Fowlkes, C. L. L. Hendriks, L. Simirenko, N. Y. Shah, M. B. Eisen, M. D. Biggin, H. Hagen, D. Sudar, J. Malik, D. W. Knowles., and B. Hamann, “PointCloudXplore: A Visualization Tool for 3D Gene Expression Data,” in Visualization of Large and Unstructured Data Sets, vol. S-4, Bonn, Germany: Gesellschaft fuer Informatik (GI), pp. 107–117, Jun. 2006. LBNL-62336.
  13. O. Rübel, G. H. Weber, S. .V. .E. Keränen, C. C. Fowlkes, C. L. L. Hendriks, L. Simirenko, N. Y. Shah, M. B. Eisen, M. D. Biggin, H. Hagen, J. D. Sudar, J. Malik, D. W. Knowles, and B. Hamann., “PointCloudXplore: Visual analysis of 3D gene expression data using physical views and parallel coordinates,” in Data Visualization 2006 (Proceedings of EuroVis 2006), Aire-la-Ville, Switzerland, pp. 203–210, May 2006.
  14. A. S. Fruchter, A. J. Levan, L. Strolger, P. M. Vreeswijk, S. E. Thorsett, D. Bersier, I. Burud, J. M. Castro Cerón, A. J. Castro-Tirado, C. Conselice, T. Dahlen, H. C. Ferguson, J. P. U. Fynbo, P. M. Garnavich, R. A. Gibbons, J. Gorosabel, T. R. Gull, J. Hjorth, S. T. Holland, C. Kouveliotou, Z. Levay, M. Livio, M. R. Metzger, P. E. Nugent, L. Petro, E. Pian, J. E. Rhoads, A. G. Riess, K. C. Sahu, A. Smette, N. R. Tanvir, R. A. M. J. Wijers, and S. E. Woosley, “Long γ-ray bursts and core-collapse supernovae have different environments,” \nat, vol. 441, pp. 463–468, May 2006.
  15. M. Sullivan, D. A. Howell, K. Perrett, P. E. Nugent, P. Astier, E. Aubourg, D. Balam, S. Basa, R. G. Carlberg, A. Conley, S. Fabbro, D. Fouchez, J. Guy, I. Hook, H. Lafoux, J. D. Neill, R. Pain, N. Palanque-Delabrouille, C. J. Pritchet, N. Regnault, J. Rich, R. Taillet, G. Aldering, S. Baumont, J. Bronder, M. Filiol, R. A. Knop, S. Perlmutter, and C. Tao, “Photometric Selection of High-Redshift Type Ia Supernova Candidates,” The Astrophysical Journal, vol. 131, pp. 960–972, Feb. 2006.
  16. J. Chen, E. W. Bethel, and I. Yoon, “Interactive, Internet Delivery of Scientific Visualization via Structured, Prerendered Imagery,” in Proceedings of 2006 SPIE/IS&T Conference on Electronic Imaging, Volume 6061, A 1-10, Jan. 2006. LBNL-57528.
  17. C. Crawford, O. Kreylos, B. Hamann, and S. Crivelli, “Visualization of Force Fields in Protein Structure Prediction,” in Proceedings of 2006 SPIE/IS&T Conference on Electronic Imaging, Volume 6060, Jan. 2006.
  18. E. W. Bethel, C. Johnson, C. Hansen, S. Parker, A. Sanderson, C. Silva, X. Trichoche, V. Pascucci, H. Childs, J. Cohen, M. Duchaineau, D. Laney, P. Lindstrom, S. Ahern, J. Meredith, G. Ostouchov, K. I. Joy, and B. Hamann, “Meet the Proposed SciDAC2 Visualization and Analytics Center for Enabling Technologies,” in SciDAC 2006 Program Conference, 2006. LBNL-60478.

2005

  1. R. A. Scalzo, G. Aldering, C. Aragon, S. Bailey, S. Bongard, S. Bailey, D. Kocevski, S. Loken, P. Nugent, S. Perlmutter, R. C. Thomas, L. Wang, B. A. Weaver, P. Antilogus, S. Gilles, R. Pain, R. Pereira, N. Blanc, Y. Copin, E. Gangler, L. Sauge, G. Smadja, C. Bonnaud, E. Pecontal, R. Kessler, C. Baltay, D. Rabinowitz, A. Bauer, and Nearby Supernova Factory Collaboration, “Status of the Candidate Search for the Nearby Supernova Factory,” in Bulletin of the American Astronomical Society, pp. 1431-+, vol. 37, Dec. 2005.
  2. K. Stockinger, K. Wu, S. Campbell, S. Lau, M. Fisk, E. Gavrilov, A. Kent, C. Davis, R. Olinger, R. Young, J. Prewitt, P. Weber, T. Caudell, E. W. Bethel, and S. Smith, “Network Traffic Analysis with Query-Driven Visualization – SC05 HPC Analytics Challenge Results,” in SC ’05: Proceedings of the 2005 ACM/IEEE Conference on High Performance Computing, Networking, Storage and Analysis, Nov. 2005. LBNL-58768.
  3. L. Gosink, J. Shalf, K. Stockinger, K. Wu, and E. W. Bethel, “HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices,” in 2005 HDF5 Workshop, San Francisco, CA, USA, Nov. 2005. LBNL-59602-Abs.
  4. K. Stockinger, J. Shalf, K. Wu, and E. W. Bethel, “Query-Driven Visualization of Large Data Sets,” in Proceedings of IEEE Visualization 2005, pp. 167–174, Oct. 2005. LBNL-57511.
  5. C. Co, A. Friedman, D. Grote, J.-L. Vay, E. W. Bethel, and K. I. Joy, “Interactive Methods for Exploring Particle Simulation Data,” in Proceedings of EuroVis 2005, Leeds, UK, pp. 279–286, Jun. 2005. LBNL-55353.
  6. K. Stockinger, J. Shalf, E. W. Bethel, and K. Wu, “DEX: Increasing the Capability of Scientific Data Analysis Pipelines by Using Efficient Bitmap Indices to Accelerate Scientific Visualization,” in Proceedings of Scientific and Statistical Database Management Conference (SSDBM), Santa Barbara, CA, USA, pp. 35–44, Jun. 2005. LBNL-57203.
  7. N. Shah, O. Couronne, L. Pennacchio, M. Brudno, S. Batzoglou, E. W. Bethel, E. Rubin, B. Hamann, and I. Dubchak, “Phylo-VISTA: Interactive Visualization of Multiple DNA Sequence Alignments,” Bioinformatics, vol. 20, no. 5, pp. 636–643, May 2005.
  8. T.-C. Lu, N. Max, J. Ding, E. W. Bethel, and S. N. Crivelli, “DockingShop: A Tool for Interactive Molecular Docking,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-51870, 2005.
  9. E. W. Bethel, S. Campbell, E. Dart, J. Lee, S. A. Smith, K. Stockinger, B. Tierney, and K. Wu, “Interactive Analysis of Large Network Data Collections Using Query-Driven Visualization,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-59166, 2005.
  10. E. W. Bethel and J. Shalf, “Consuming Network Bandwidth with Visapult,” in The Visualization Handbook, C. Hansen and C. Johnson, Eds. Elsevier, pp. 569–589, 2005. LBNL-52171.

2004

  1. S. Crivelli, O. Kreylos, B. Hamann, N. Max, and E. W. Bethel, “ProteinShop: A Tool for Interactive Protein Manipulation and Steering,” Journal of Computer Aided Molecular Design (JCAMD), vol. 18, no. 4, pp. 271–285, Apr. 2004. LBNL-53731.
  2. I. Bowman, J. Shalf, K.-L. Ma, and E. W. Bethel, “Performance Modeling for 3D Visualization in a Heterogeneous Computing Environment,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, 2004. LBNL-56977.

2003

  1. E. W. Bethel, G. Humphreys, B. Paul, and J. D. Brederson, “Sort-First, Distributed Memory Parallel Visualization and Rendering,” in Proceedings of the 2003 IEEE Symposium on Parallel and Large-Data Visualization and Graphics, pp. 41–50, Oct. 2003.
  2. G. Weber, M. Öhler, O. Kreylos, J. Shalf, E. W. Bethel, B. Hamann, and G. Scheuermann, “Parallel Cell Projection Rendering of Adaptive Mesh Refinement Data,” in IEEE Symposium on Parallel and Large-Data Visualization and Graphics, Seattle WA, USA, pp. 51–60, Oct. 2003. LBNL-52469.
  3. O. Kreylos, N. Max, B. Hamann, S. Crivelli, and E. W. Bethel, “Interactive Protein Manipulation,” in Proceedings of IEEE Visualization 2003, Seattle, WA, pp. 581–588, Oct. 2003. LBNL-52414, Winner of the Best Application Paper Award.
  4. E. W. Bethel, R. Frank, S. Fulcomer, C. Hansen, K. I. Joy, J. Kohl, and D. Middleton, “Visual Data Analysis - Report of the Visualization Breakout Session at the 2003 SCaLeS Workshop - Volume II.,” Lawrence Berkeley National Laboratory, Jun. 2003. LBNL-PUB-886.
  5. E. W. Bethel, C. Siegerist, J. Shalf, P. Shetty, T. J. Jankun-Kelly, O. Kreylos, and K.-L. Ma, “VisPortal: Deploying Grid-Enabled Visualization Tools through a Web-portal Interface,” in Wide Area Collaborative Environments, Seattle, WA, USA, Jun. 2003. LBNL-52940.
  6. J. Shalf and E. W. Bethel, “How the Grid Will Affect the Architecture of Future Visualization Systems,” IEEE Computer Graphics and Applications, vol. 23, no. 2, pp. 6–9, May 2003.
  7. J. Shalf and E. W. Bethel, “Cactus and Visapult: A Case Study of Ultra-High Performance Distributed Visualization Using Connectionless Protocols,” IEEE Computer Graphics and Applications, vol. 23, no. 2, pp. 51–59, Mar. 2003. LBNL-51564.
  8. T. J. Jankun-Kelly, O. Kreylos, J. Shalf, K.-L. Ma, B. Hamann, K. I. Joy, and E. W. Bethel, “Deploying Web-based Visual Exploration Tools on the Grid,” IEEE Computer Graphics and Applications, vol. 23, no. 2, pp. 40–49, Mar. 2003. LBNL-51553.
  9. E. W. Bethel, G. Abram, J. Shalf, R. Frank, J. Ahrens, S. Parker, N. Smatova, and M. Miller, “Interoperability of Visualization Software and Data Models is Not an Achievable Goal,” in IEEE Visualization 2003, Seattle, WA. USA, pp. 607–610, 2003. LBNL-53368 Abs..
  10. N. Shah, O. Couronne, L. Pennacchio, M. Brudno, S. Batzoglou, E. W. Bethel, E. Rubin, B. Hamann, and I. Dubchak, “Phylo-Vista: An Interactive Visualization Tool for Multiple DNA Sequence Alignments,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, 2003. LBNL-52539.
  11. B. Hamann, E. W. Bethel, H. Simon, and J. Meza, “The NERSC Visualization Greenbook: Future Visualization Needs of the DOE Computational Science Community Hosted at NERSC,” The International Journal of High Performance Computing Applications, vol. 17, no. 2, pp. 97–124, 2003. LBNL-51699.

2002

  1. J. Shalf and E. W. Bethel, “Cactus and Visapult: A Case Study of Ultra-High Performance Distributed Visualization Using Connectionless Protocols,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-50237, 2002.
  2. E. W. Bethel, S. J. Bastacky, and K. Schwartz, “Interactive Stereo Electron Microscopy Enhanced with Virtual Reality,” in Proceedings of SPIE Vol. 4660: Stereoscopic Displays and Virtual Reality Systems IX, pp. 391–400, 2002. LBNL-48336.
  3. O. Kreylos, G. Weber, E. W. Bethel, J. Shalf, B. Hamann, and K. Joy, “Remote Interactive Direct Volume Rendering of AMR Data,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, 2002. LBNL-49954.

2000

  1. E. W. Bethel, “Visapult – A Prototype Remote and Distributed Application and Framework,” in Proceedings of Siggraph 2000 – Applications and Sketches, Jul. 2000.
  2. E. W. Bethel, “Visualization Dot Com,” IEEE Computer Graphics and Applications, vol. 20, no. 3, pp. 17–20, May 2000. LBNL-44871.

1999

  1. E. W. Bethel, C. Bass, S. R. Clay, B. Hook, M. T. Jones, H. Sowizral, and A. van Dam, “Scene Graph APIs: Wired or Tired?,” in SIGGRAPH ’99: ACM SIGGRAPH 99 Conference abstracts and applications, Los Angeles, CA, USA, pp. 136–138, 1999.

1998

  1. S. P. Uselton, L. Treinish, J. P. Ahrens, E. W. Bethel, and A. State, “Multi-source data analysis challenges,” in IEEE Visualization 1998, Research Triangle Park, NC, USA, pp. 501–504, 1998.

1995

  1. E. W. Bethel, “Modular Virtual Reality Visualization Tools,” in Proceedings of the International Advanced Visual Systems User and Developer Conference (AVS95), Boston, MA, USA, pp. 245–254, Apr. 1995. LBNL-36693.
  2. J. Horsman and E. W. Bethel, “Methods of Constructing a 3D Geological Model from Scatter Data,” in Proceedings of the International Advanced Visual Systems User and Developer Conference (AVS95), Boston, MA, USA, pp. 395–404, Apr. 1995.
  3. J. Jacobsen, E. W. Bethel, A. Datta-Gupta, and P. Holland, “Virtual Reservoir Development a Reality on Prototype System,” American Oil & Gas Reporter, vol. 38, no. 12, pp. 78–86, 1995.
  4. J. Jacobsen, E. W. Bethel, A. Datta-Gupta, and P. Holland, “Petroleum Reservoir Simulation in a Virtual Environment,” in Proceedings of the 13th Symposium on Reservoir Simulation (SPE), San Antonio TX, USA, 1995.

1994

  1. E. W. Bethel, “Chemical Flooding in a Virtual Environment – A Survivor’s Guide to VR Development,” in Proceedings of the International Advanced Visual Systems User and Developer Conference (AVS94), Boston MA, USA, pp. 299–309, May 1994. LBNL-35262.
  2. E. W. Bethel, J. Jacobsen, and P. Holland, “Site Remediation in a Virtual Environment,” in Visual Data Exploration and Analysis, Proceedings of SPIE 2178, San Jose CA, USA, pp. 78–87, Jan. 1994. LBNL-34865.

1993

  1. E. W. Bethel, “Analytic Rendering of Curvilinear Volume Data,” Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 94720, LBNL-33808, 1993.

1989

  1. E. W. Bethel and S. P. Uselton, “Shape Distortion in Computer-Assisted Keyframe Animation,” in State-of-the-art in Computer Animation, Geneva, Switzerland, pp. 215–224, Jun. 1989.