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  2020 (3)
Object Classifications by Image Super-Resolution Preprocessing for Convolutional Neural Networks. Na, B.; and Fox, G., C. Advances in Science, Technology and Engineering Systems Journal, 5(2): 476-483. 2020.
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Understanding ML Driven HPC: Applications and Infrastructure. Jha, S.; and Fox, G. In pages 421-427, 3 2020. Institute of Electrical and Electronics Engineers (IEEE)
Understanding ML Driven HPC: Applications and Infrastructure [pdf]Paper   Understanding ML Driven HPC: Applications and Infrastructure [link]Website   bibtex   abstract  
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations. Fox, G.; and Jha, S. In pages 439-448, 3 2020. Institute of Electrical and Electronics Engineers (IEEE)
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations [pdf]Paper   Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations [link]Website   bibtex   abstract  
  2019 (18)
Learning Everywhere Resource for BDEC. Fox, G.; and July, U. Technical Report 2019.
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Big Data Benchmarks of High-Performance Storage Systems on Commercial Bare Metal Clouds. Lee, H.; and Fox, G. In IEEE International Conference on Cloud Computing (IEEE CLOUD 2019), 5 2019.
Big Data Benchmarks of High-Performance Storage Systems on Commercial Bare Metal Clouds [pdf]Website   bibtex   abstract  
Perspectives on High-Performance Computing in a Big Data World. Fox, G., C. In Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '19), pages 145-145, 2019. Association for Computing Machinery (ACM)
Perspectives on High-Performance Computing in a Big Data World [pdf]Paper   bibtex   abstract  
Twister2: TSet high-performance iterative dataflow. Wickramasinghe, P.; Kamburugamuve, S.; Govindarajan, K.; Abeykoon, V.; Widanage, C.; Perera, N.; Uyar, A.; Gunduz, G.; Akkas, S.; and Fox, G. In 2019 International Conference on High Performance Big Data and Intelligent Systems, HPBD and IS 2019, pages 55-60, 5 2019. Institute of Electrical and Electronics Engineers Inc.
Twister2: TSet high-performance iterative dataflow [pdf]Paper   bibtex   abstract  
Parallel Performance of Molecular Dynamics Trajectory Analysis. Khoshlessan, M.; Paraskevakos, I.; Fox, G., C.; Jha, S.; and Beckstein, O. Technical Report 2019.
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Harnessing the Computing Continuum for Programming Our World. Beckman, P.; Dongarra, J.; Ferrier, N.; Fox, G.; Moore, T.; Reed, D.; and Beck, M. Technical Report 2019.
Harnessing the Computing Continuum for Programming Our World [pdf]Paper   Harnessing the Computing Continuum for Programming Our World [link]Website   bibtex   abstract  
Advances in big data programming, system software and HPC convergence. Hsu, C., H.; Fox, G.; Min, G.; and Sharma, S. 2 2019.
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Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation. Fox, G.; Glazier, J.; Kadupitiya, J.; Jadhao, V.; Kim, M.; Qiu, J.; Sluka, J., P.; Somogy, E.; Marathe, M.; Adiga, A.; Chen, J.; Beckstein, O.; and Jha, S. In 2019 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pages 422-429, 5 2019. IEEE
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation [link]Website   bibtex   abstract  
Twister2: Design of a big data toolkit. Kamburugamuve, S.; Govindarajan, K.; Wickramasinghe, P.; Abeykoon, V.; and Fox, G. Concurrency Computation: Practice and Experience. 2019.
Twister2: Design of a big data toolkit [pdf]Paper   bibtex   abstract  
Machine Learning for Performance Enhancement of Molecular Dynamics Simulations. Kadupitiya, J.; Fox, G., C.; and Jadhao, V. In International Conference on Computational Science ICCS2019, volume 11537 LNCS, pages 116-130, 2019. Springer Verlag
Machine Learning for Performance Enhancement of Molecular Dynamics Simulations [pdf]Paper   bibtex   abstract  
Object Classification by a Super-resolution Method and a Convolutional Neural Networks. Na, B.; and Fox, G., C. International Journal of Data Mining Science, 1(1): 16-23. 2019.
Object Classification by a Super-resolution Method and a Convolutional Neural Networks [pdf]Paper   Object Classification by a Super-resolution Method and a Convolutional Neural Networks [link]Website   bibtex   abstract  
Machine Learning for Performance Enhancement of Molecular Dynamics Simulations. Kadupitiya, J.; Fox, G., C.; and Jadhao, V. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 11537 LNCS, pages 116-130, 2019. Springer Verlag
Machine Learning for Performance Enhancement of Molecular Dynamics Simulations [pdf]Paper   bibtex  
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation: Application Background. Fox, G.; Glazier, J., A.; Kadupitiya, J.; Jadhao, V.; Kim, M.; Qiu, J.; Sluka, J., P.; Somogyi, E.; Marathe, M.; Adiga, A.; Chen, J.; Beckstein, O.; and Jha, S. Technical Report 2019.
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation: Application Background [pdf]Website   bibtex  
Regge phenomenology of the N∗ and Δ∗ poles. Silva-Castro, J., A.; Fernández-Ramírez, C.; Albaladejo, M.; Danilkin, I., V.; Jackura, A.; Mathieu, V.; Nys, J.; Pilloni, A.; Szczepaniak, A., P.; and Fox, G. Physical Review D, 99(3). 2 2019.
Regge phenomenology of the N∗ and Δ∗ poles [pdf]Paper   bibtex   abstract  
Benchmarking Deep Learning for Time Series: Challenges and Directions. Huang, X.; Fox, G., C.; Serebryakov, S.; Mohan, A.; Morkisz, P.; and Dutta, D. In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, pages 5679-5682, 12 2019. Institute of Electrical and Electronics Engineers Inc.
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Streaming Machine Learning Algorithms with Big Data Systems. Abeykoon, V.; Laszewski, G., V.; Kamburugamuve, S.; Govindrarajan, K.; Wickramasinghe, P.; Widanage, C.; Perera, N.; Uyar, A.; Gunduz, G.; and Akkas, S. In Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, pages 5661-5666, 12 2019. Institute of Electrical and Electronics Engineers Inc.
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Automated Ice-Bottom Tracking of 2D and 3D Ice Radar Imagery Using Viterbi and TRW-S. Berger, V.; Xu, M.; Al-Ibadi, M.; Chu, S.; Crandall, D.; Paden, J.; and Fox, G., C. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(9): 3272-3285. 9 2019.
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Scientific image restoration anywhere. Abeykoon, V.; Liu, Z.; Kettimuthu, R.; Fox, G.; and Foster, I. In Proceedings of XLOOP 2019: 1st Annual Workshop on Large-Scale Experiment-in-the-Loop Computing, Held in conjunction with SC 2019: The International Conference for High Performance Computing, Networking, Storage and Analysis, pages 8-13, 11 2019. Institute of Electrical and Electronics Engineers Inc.
Scientific image restoration anywhere [pdf]Paper   Scientific image restoration anywhere [link]Website   bibtex   abstract  
  2018 (24)
Vector meson photoproduction with a linearly polarized beam. Mathieu, V.; Nys, J.; Fernández-Ramírez, C.; Jackura, A.; Pilloni, A.; Sherrill, N.; Szczepaniak, A., P.; and Fox, G. Physical Review D, 97(9). 2018.
Vector meson photoproduction with a linearly polarized beam [link]Website   bibtex   abstract  
Analyticity Constraints for Hadron Amplitudes: Going High to Heal Low Energy Issues. Mathieu, V.; Nys, J.; Pilloni, A.; Fernández-Ramírez, C.; Jackura, A.; Mikhasenko, M.; Pauk, V.; Szczepaniak, A., P.; and Fox, G. Europhysics Letters, 122(4): 41001-p1-p5. 2018.
Analyticity Constraints for Hadron Amplitudes: Going High to Heal Low Energy Issues [link]Website   bibtex   abstract  
Structure of pion photoproduction amplitudes. Mathieu, V.; Nys, J.; Fernández-Ramírez, C.; Blin, A., H.; Jackura, A.; Pilloni, A.; Szczepaniak, A.; and Fox, G. Physical Review D, 98(1): 014041. 2018.
Structure of pion photoproduction amplitudes [link]Website   bibtex  
Big data and extreme-scale computing: Pathways to Convergence-Toward a shaping strategy for a future software and data ecosystem for scientific inquiry. Asch, M.; Moore, T.; Badia, R.; Beck, M.; Beckman, P.; Bidot, T.; Bodin, F.; Cappello, F.; Choudhary, A.; de Supinski, B.; Deelman, E.; Dongarra, J.; Dubey, A.; Fox, G.; Fu, H.; Girona, S.; Gropp, W.; Heroux, M.; Ishikawa, Y.; Keahey, K.; Keyes, D.; Kramer, W.; Lavignon, J., F.; Lu, Y.; Matsuoka, S.; Mohr, B.; Reed, D.; Requena, S.; Saltz, J.; Schulthess, T.; Stevens, R.; Swany, M.; Szalay, A.; Tang, W.; Varoquaux, G.; Vilotte, J., P.; Wisniewski, R.; Xu, Z.; and Zacharov, I. Volume 32 2018.
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Big Data Benchmarks on Bare Metal Cloud. Lee, H.; and Fox, G., C. Technical Report 2018.
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Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture. Liu, X.; Chen, L.; Firoz, J., S.; Qiu, J.; and Jiang, L. In 2018 IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2018, pages 199–208, 2018. Institute of Electrical and Electronics Engineers Inc.
Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture [link]Website   bibtex   abstract  
Crossover analysis and automated layer-tracking assessment of the extracted DEM of the basal topography of the canadian arctic archipelago ice-cap. Al-Ibadi, M.; Sprick, J.; Athinarapu, S.; Berger, V.; Stumpf, T.; Paden, J.; Leuschen, C.; Rodriguez, F.; Xu, M.; Crandall, D.; Fox, G.; Burgess, D.; Sharp, M.; Copland, L.; and Van Wychen, W. 2018 IEEE Radar Conference, RadarConf 2018,862-867. 2018.
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Detecting ice layers in radar images with deep learning. Hamid Kamangir, Maryam Rahnemoonfar, Dugan Dobbs, J Paden, G., F. Technical Report 2018.
Detecting ice layers in radar images with deep learning [pdf]Website   bibtex   abstract  
Finding and Counting Tree-Like Subgraphs Using MapReduce. Zhao, Z.; Chen, L.; Avram, M.; Li, M.; Wang, G.; Butt, A.; Khan, M.; Marathe, M.; Qiu, J.; and Vullikanti, A. IEEE Transactions on Multi-Scale Computing Systems, 4(3): 217-230. 7 2018.
Finding and Counting Tree-Like Subgraphs Using MapReduce [link]Website   bibtex  
Object Detection by a Super-Resolution Method and a Convolutional Neural Networks. Na, B.; and Fox, G., C. In 2018 IEEE International Conference on Big Data, Big Data, pages 2263-2269, 1 2018. Institute of Electrical and Electronics Engineers Inc.
Object Detection by a Super-Resolution Method and a Convolutional Neural Networks [pdf]Paper   bibtex   abstract  
Machine Learning for Parameter Auto-tuning in Molecular Dynamics Simulations: Efficient Dynamics of Ions near Polarizable Nanoparticles. Kadupitiya, J.; Fox, G., C.; and Jadhao, V. Technical Report 2018.
Machine Learning for Parameter Auto-tuning in Molecular Dynamics Simulations: Efficient Dynamics of Ions near Polarizable Nanoparticles [pdf]Paper   Machine Learning for Parameter Auto-tuning in Molecular Dynamics Simulations: Efficient Dynamics of Ions near Polarizable Nanoparticles [pdf]Website   bibtex   abstract  
Contributions to High-Performance Big Data Computing. Fox, G.; Qiu, J.; Crandall, D.; Laszewski, G., V.; Beckstein, O.; Paden, J.; Paraskevakos, I.; Jha, S.; Wang, F.; Marathe, M.; Vullikanti, A.; and Cheatham, T. Technical Report 2018.
Contributions to High-Performance Big Data Computing [pdf]Paper   Contributions to High-Performance Big Data Computing [link]Website   bibtex   abstract  
Harp-DAAL for High Performance Big Data Computing. Qiu, J. Parallel Universe. 3 2018.
Harp-DAAL for High Performance Big Data Computing [pdf]Paper   Harp-DAAL for High Performance Big Data Computing [pdf]Website   bibtex   abstract  
Global analysis of charge exchange meson production at high energies. Nys, J.; Hiller Blin, A., N.; Mathieu, V.; Fernández-Ramírez, C.; Jackura, A.; Pilloni, A.; Ryckebusch, J.; Szczepaniak, A., P.; and Fox, G. . 2018.
Global analysis of charge exchange meson production at high energies [pdf]Paper   bibtex   abstract  
Deep hybrid wavelet network for ice boundary detection in radra imagery. Kamangir, H.; Rahnemoonfar, M.; Dobbs, D.; Paden, J.; and Fox, G. In International Geoscience and Remote Sensing Symposium (IGARSS), volume 2018-July, pages 3449-3452, 10 2018. Institute of Electrical and Electronics Engineers Inc.
Deep hybrid wavelet network for ice boundary detection in radra imagery [pdf]Paper   bibtex   abstract  
Evaluating the scientific impact of XSEDE. Wang, F.; Fox, G., C.; Von Laszewski, G.; Furlani, T., R.; Gallo, S., M.; Whitson, T.; and DeLeon, R., L. In Proceedings of the Practice and Experience on Advanced Research Computing (PEARC '18), 7 2018. Association for Computing Machinery
Evaluating the scientific impact of XSEDE [pdf]Paper   bibtex   abstract  
Task-parallel analysis of molecular dynamics trajectories. Paraskevakos, I.; Chantzialexiou, G.; Luckow, A.; Cheatham, T., E.; Khoshlessan, M.; Beckstein, O.; Fox, G., C.; and Jha, S. In Proceedings of the 47th International Conference on Parallel Processing (ICPP 2018), 8 2018. Association for Computing Machinery
Task-parallel analysis of molecular dynamics trajectories [pdf]Paper   bibtex   abstract  
Twister: Net - Communication Library for Big Data Processing in HPC and Cloud Environments. Kamburugamuve, S.; Wickramasinghe, P.; Govindarajan, K.; Uyar, A.; Gunduz, G.; Abeykoon, V.; and Fox, G. In IEEE International Conference on Cloud Computing, CLOUD, volume 2018-July, pages 383-391, 9 2018. IEEE Computer Society
Twister: Net - Communication Library for Big Data Processing in HPC and Cloud Environments [pdf]Paper   bibtex   abstract  
Evaluation of Production Serverless Computing Environments. Lee, H.; Satyam, K.; and Fox, G. In IEEE International Conference on Cloud Computing, CLOUD, volume 2018-July, pages 442-450, 9 2018. IEEE Computer Society
Evaluation of Production Serverless Computing Environments [pdf]Paper   bibtex   abstract  
Multi-task Spatiotemporal Neural Networks for Structured Surface Reconstruction. Xu, M.; Fan, C.; Paden, J., D.; Fox, G., C.; and Crandall, D., J. In Proceedings - 2018 IEEE Winter Conference on Applications of Computer Vision, WACV 2018, volume 2018-Janua, pages 1273-1282, 5 2018. Institute of Electrical and Electronics Engineers Inc.
Multi-task Spatiotemporal Neural Networks for Structured Surface Reconstruction [pdf]Paper   bibtex   abstract  
Automated tracking of 2D and 3D ice radar imagery using Viterbi and TRW-S. Berger, V.; Xu, M.; Chu, S.; Crandall, D.; Paden, J.; and Fox, G., C. In International Geoscience and Remote Sensing Symposium (IGARSS), volume 2018-July, pages 4162-4165, 10 2018. Institute of Electrical and Electronics Engineers Inc.
Automated tracking of 2D and 3D ice radar imagery using Viterbi and TRW-S [pdf]Paper   bibtex   abstract  
Features of πΔ photoproduction at high energies. Nys, J.; Mathieu, V.; Fernández-Ramírez, C.; Jackura, A.; Mikhasenko, M.; Pilloni, A.; Sherrill, N.; Ryckebusch, J.; Szczepaniak, A., P.; Fox, G., C.; and Center, J., P., A. Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, 779: 77-81. 2018.
Features of πΔ photoproduction at high energies [link]Website   bibtex   abstract  
Task Scheduling in Big Data - Review, Research Challenges, and Prospects. Govindarajan, K.; Kamburugamuve, S.; Wickramasinghe, P.; Abeykoon, V.; and Fox, G. In 2017 9th International Conference on Advanced Computing, ICoAC 2017, pages 165-173, 8 2018. Institute of Electrical and Electronics Engineers Inc.
Task Scheduling in Big Data - Review, Research Challenges, and Prospects [pdf]Paper   bibtex   abstract  
  2017 (4)
Comet - Tales from the Long Tail - Two years in and 10,000 users later. Strandea, S.; Caia, H.; Cooper, T.; Flammer, K.; Irving, C.; Von Laszewski, G.; Majumdar, A.; Mishin, D.; Papadopoulos, P.; Pfeiffer, W.; Sinkovits, R.; Tatineni, M.; Wagner, R.; Wang, F.; Wilkins-Diehr, N.; Wolter, N.; and Norman, M. In Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact (PEARC17), volume Part F1287, 2017.
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High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication. Chen, L.; Peng, B.; Ossen, S.; Vullikanti, A.; Marathe, M.; Jiang, L.; and Qiu, J. In Big Data and HPC: Ecosystem and Convergence, TopHPC 2017, pages 173-197, 2017.
High-Performance Massive Subgraph Counting Using Pipelined Adaptive-Group Communication. [link]Website   bibtex   abstract  
Introduction to Harp: when Big Data Meets HPC. Zhang, B.; Peng, B.; Chen, L.; Li, E.; Zhou, Y.; and Qiu, J. Technical Report 2017.
Introduction to Harp: when Big Data Meets HPC [pdf]Paper   Introduction to Harp: when Big Data Meets HPC [link]Website   bibtex   abstract  
  2016 (3)
Providing Statistical Reliability Guarantee for Cloud Clusters. Yang, Z.; Du, A., Y.; Das, S.; Ramesh, R.; Furlani, T.; von Laszewski, G.; and Qiao, C. In Providing Statistical Reliability Guarantee for Cloud Clusters. Submitted to Global Communications Conference, 2016.
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User managed virtual clusters in comet. Wagner, R.; Papadopoulos, P.; Mishin, D.; Cooper, T.; Tatineti, M.; Von Laszewski, G.; Wang, F.; and Fox, G. In ACM International Conference Proceeding Series, volume 17-21-July, 2016.
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NIST Big Data Interoperability Framework: Volume 3, Use Cases and General Requirements (NIST Special Publication 1500-3). Subgroup, N., B., D., P., W., G., U., C., a., R. , 3(June). 2016.
NIST Big Data Interoperability Framework: Volume 3, Use Cases and General Requirements (NIST Special Publication 1500-3) [pdf]Website   bibtex   abstract  
  2015 (6)
Peer comparison of XSEDE and NCAR publication data. Von Laszewski, G.; Wang, F.; Fox, G.; Hart, D.; Furlani, T.; Deleon, R.; and Gallo, S. In Proceedings - IEEE International Conference on Cluster Computing, ICCC, volume 2015-Octob, 2015.
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TAS view of XSEDE users and usage. DeLeon, R.; Furlani, T.; Gallo, S.; White, J.; Jones, M.; Patra, A.; Innus, M.; Yearke, T.; Palmer, J.; Sperhac, J.; Rathsam, R.; Simakov, N.; Von Laszewski, G.; and Wang, F. In ACM International Conference Proceeding Series, volume 2015-July, 2015.
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Scalability Analysis of the Multi-Look Time Domain Processor on XSEDE Compute Resources. von Laszewski, G.; Wang, F.; Fox, G., C.; Li, J.; and Paden, J. Technical Report 2015.
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NIST Special Publication 1500-6 : NIST Big Data Interoperability Framework - Reference Architecture. (NBD-PWG), N., B., D., P., W., G. , 6(June): 1-62. 2015.
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Pervasive Technology Institute annual report: Research innovations and advanced cyberinfrastructure services in support of IU strategic goals during FY 2015. Stewart, Craig A.; Plale, Beth; Welch, Von; Link, Matthew R.; Miller, Therese; Wernert, Eric A.; Boyles, Michael J.; Fulton, Ben; Hancock, David Y.; Henschel, Robert; Michael, Scott A.; Pierce, Marlon; Ping, Robert J.; Gniady, Tassie; Fox, Geoffrey C.; Mi, G. Technical Report 2015.
Pervasive Technology Institute annual report: Research innovations and advanced cyberinfrastructure services in support of IU strategic goals during FY 2015 [pdf]Paper   Pervasive Technology Institute annual report: Research innovations and advanced cyberinfrastructure services in support of IU strategic goals during FY 2015 [link]Website   bibtex  
  2014 (6)
Comprehensive, open-source resource usage measurement and analysis for HPC systems. Browne, J.; Deleon, R.; Patra, A.; Barth, W.; Hammond, J.; Jones, M.; Furlani, T.; Schneider, B.; Gallo, S.; Ghadersohi, A.; Gentner, R.; Palmer, J.; Simakov, N.; Innus, M.; Bruno, A.; White, J.; Cornelius, C.; Yearke, T.; Marcus, K.; Von Laszewski, G.; and Wang, F. Concurrency Computation Practice and Experience, 26(13). 2014.
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Towards understanding cloud usage through resource allocation analysis on xsede. Lee, H.; von Laszewski, G.; Wang, F.; and Fox, G., C. Technical Report 2014.
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Towards a scientific impact measuring framework for large computing facilities - A case study on XSEDE. Wang, F.; Von Laszewski, G.; Fox, G.; Furlani, T.; DeLeon, R.; and Gallo, S. In ACM International Conference Proceeding Series, 2014.
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Accessing multiple clouds with Cloudmesh. Von Laszewski, G.; Wang, F.; Lee, H.; Chen, H.; and Fox, G. In BigSystem 2014 - Proceedings of the 2014 ACM International Workshop on Software-Defined Ecosystems, Co-located with HPDC 2014, 2014.
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DDDAS-Parallel Simulation of Threat Management in Urban Water Distribution Systems for Cloud Computing. Wang, L.; and von Laszewski, G. Computing in Science & Engineering, 16(1). 2014.
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The FutureGrid Testbed for Big Data. Von Laszewski, G.; and Fox, G., C. Cloud Computing for Data-Intensive Applications, pages 27-59. Springer, 2014.
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  2013 (4)
Performance metrics and auditing framework using application kernels for high-performance computer systems. Furlani, T.; Jones, M.; Gallo, S.; Bruno, A.; Lu, C.; Ghadersohi, A.; Gentner, R.; Patra, A.; Deleon, R.; Von Laszewski, G.; Wang, F.; and Zimmerman, A. Concurrency Computation Practice and Experience, 25(7). 2013.
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Co-processing SPMD computation on CPUs and GPUs cluster. Li, H.; Fox, G.; Von Laszewski, G.; and Chauhan, A. In Proceedings - IEEE International Conference on Cluster Computing, ICCC, 2013.
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Using XDMoD to facilitate XSEDE operations, planning and analysis. Furlani, T.; Schneider, B.; Jones, M.; Towns, J.; Hart, D.; Gallo, S.; Deleon, R.; Lu, C.; Ghadersohi, A.; Gentner, R.; Patra, A.; Laszewski, G.; Wang, F.; Palmer, J.; and Simakov, N. In ACM International Conference Proceeding Series, 2013.
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On-demand service hosting on production grid infrastructures. Wang, L.; Kurze, T.; Tao, J.; Kunze, M.; and Von Laszewski, G. Journal of Supercomputing, 66(3). 2013.
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  2012 (7)
Abstract image management and universal image registration for cloud and HPC infrastructures. Diaz, J.; Von Laszewski, G.; Wang, F.; and Fox, G. In Proceedings - 2012 IEEE 5th International Conference on Cloud Computing, CLOUD 2012, 2012.
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Data analytics driven cyberinfrastructure operations, planning and analysis using XDMoD. Furlani, T., R.; Schneider, B., I.; Jones, M., D.; Towns, J.; Hart, D., L.; Patra, A., K.; DeLeon, R., L.; Gallo, S., M.; Lu, C.; and Ghadersohi, A. In submitted SC12 Conference, Salt Lake City, Utah, 2012.
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Qualitative Comparison of Multiple Cloud Frameworks. Von Laszewski, G.; Diaz, J.; Wang, F.; and Fox, G., G., C. In Proceedings: 2012 IEEE 5th international conference on cloud computing, pages 734-741, 2012.
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Design of an accounting and metric-based cloud-shifting and cloud-seeding framework for federated clouds and bare-metal environments. Von Laszewski, G.; Lee, H.; Diaz, J.; Wang, F.; Tanaka, K.; Karavinkoppa, S.; Fox, G.; and Furlani, T. In FederatedClouds'12 - Proceedings of the 2012 Workshop on Cloud Services, Federation, and the 8th Open Cirrus Summit, Co-located with ICAC'12, 2012.
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Message from the program co-chairs. Von Laszewski, G.; Grossman, R.; Milojicic, D.; Kozuch, M.; and McGeer, R. In FederatedClouds'12 - Proceedings of the 2012 Workshop on Cloud Services, Federation, and the 8th Open Cirrus Summit, Co-located with ICAC'12, 2012.
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Design of a Dynamic Provisioning System for a Federated Cloud and Bare-metal Environment. von Laszewski, G.; Lee, H.; Diaz, J.; Wang, F.; Tanaka, K.; Karavinkoppa, S.; Fox, G., C.; and Furlani, T. In Proc. Workshop on Cloud Services, Federation, and the 8th Open Cirrus Summit, 2012.
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Supporting experimental computer science. Desprez, F.; Fox, G.; Jeannot, E.; Keahey, K.; Kozuch, M.; Margery, D.; Neyron, P.; Nussbaum, L.; Perez, C.; and Richard, O. INRIA, 2012.
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  2011 (11)
FutureGrid User Support. Pike, G.; Younge, A.; von Laszewski, G.; Wang, F.; Diaz, J.; Kulshrestha, A.; and Fox, G. FutureGrid NSF Review, Indiana University. 2011.
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FutureGrid image repository: A generic catalog and storage system for heterogeneous virtual machine images. Diaz, J.; Von Laszewski, G.; Wang, F.; Younge, A.; and Fox, G. In Proceedings - 2011 3rd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2011, 2011.
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eMOLST: a documentation flow for distributed health informatics. von Laszewski, G.; Dayal, J.; and Wang, L. Concurrency and Computation: Practice and Experience, 23(16): 1857-1867. 2011.
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Towards generic FutureGrid image management. Von Laszewski, G.; Diaz, J.; Wang, F.; Younge, A.; Kulshrestha, A.; and Fox, G. In Proceedings of the TeraGrid 2011 Conference: Extreme Digital Discovery, TG'11, 2011.
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Towards cloud deployments using FutureGrid. von Laszewski, G.; Diaz, J.; Wang, F.; Fox, G., C.; von Laszewski, G.; Wang, F.; and Fox, G., C. Indiana University, Bloomington, IN, 47408. 2011.
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Task scheduling with ANN-based temperature prediction in a data center: a simulation-based study. Wang, L.; von Laszewski, G.; Huang, F.; Dayal, J.; Frulani, T.; and Fox, G. Engineering with Computers, 27(4): 381-391. 2011.
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Towards on demand it service deployment. Dayal, J.; Rathbone, C.; Wang, L.; and von Laszewski, G. Internet Policies and Issues, 7: 249-262. 2011.
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Threat detection in urban water distribution systems with simulations conducted in grids and clouds. Von Laszewski, G.; Wang, L.; Wang, F.; Fox, G.; and Mahinthakumar, G. Civil-Comp Proceedings, 95. 2011.
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WANG, Lizhe. Wang, L.; Kunze, M.; Tao, J.; Von Laszewski, G.; Chen, D.; Deng, Z.; Huang, F.; Khan, S., U.; Dayal, J.; and Chen, J. Advances in Engineering Software, 42(9): 714-722. 2011.
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Analysis of virtualization technologies for high performance computing environments. Younge, A., J.; Henschel, R.; Brown, J., T.; Von Laszewski, G.; Qiu, J.; and Fox, G., C. In Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011, pages 9-16, 2011.
Analysis of virtualization technologies for high performance computing environments [link]Website   bibtex   abstract  
Towards building a cloud for scientific applications. Wang, L.; Kunze, M.; Tao, J.; and von Laszewski, G. Advances in Engineering software, 42(9): 714-722. 2011.
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  2010 (16)
Design of the Futuregrid experiment management framework. Von Laszewski, G.; Fox, G.; Wang, F.; Younge, A.; Kulshrestha, A.; Pike, G.; Smithy, W.; Vöcklerz, J.; Figueiredox, R.; Fortesx, J.; and Keahey, K. In 2010 Gateway Computing Environments Workshop, GCE 2010, 2010.
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Cyberaide onServe: Software as a Service on Production Grids. Kurze, T.; Wang, L.; von Laszewski, G.; Tao, J.; Kunze, M.; Kramer, D.; and Karl, W. In Parallel Processing (ICPP), 2010 39th International Conference on, pages 395-403, 2010. IEEE
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Framing the issues of cloud computing & sustainability: A design perspective. Pan, Y.; Maini, S.; and Blevis, E. In Proceedings - 2nd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2010, pages 603-608, 2010.
Framing the issues of cloud computing & sustainability: A design perspective [link]Website   bibtex   abstract  
Schedule distributed virtual machines in a service oriented environment. Wang, L.; Von Laszewski, G.; Kunze, M.; and Tao, J. In Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on, pages 230-236, 2010. IEEE
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Power aware scheduling for parallel tasks via task clustering. Wang, L.; Tao, J.; von Laszewski, G.; and Chen, D. In Parallel and Distributed Systems (ICPADS), 2010 IEEE 16th International Conference on, pages 629-634, 2010. IEEE
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Provide virtual distributed environments for grid computing on demand. Wang, L.; Von Laszewski, G.; Kunze, M.; Tao, J.; and Dayal, J. Advances in Engineering Software, 41(2): 213-219. 2010.
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GreenIT service level agreements. von Laszewski, G.; and Wang, L. Grids and Service-Oriented Architectures for Service Level Agreements, pages 77-88. Springer, 2010.
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Enabling energy-efficient analysis of massive neural signals using GPGPU. Chen, D.; Wang, L.; Wang, S.; Xiong, M.; von Laszewski, G.; and Li, X. In Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom), pages 147-154, 2010. IEEE
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Cyberaide virtual applicance: On-demand deploying middleware for cyberinfrastructure. Kurze, T.; Wang, L.; Von Laszewski, G.; Tao, J.; Kunze, M.; Wang, F.; Kramer, D.; Karl, W.; and Ekanayake, J. Volume 34 LNICST 2010.
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Provide virtual machine information for grid computing. Wang, L.; Von Laszewski, G.; Chen, D.; Tao, J.; and Kunze, M. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 40(6): 1362-1374. 2010.
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Towards energy aware scheduling for precedence constrained parallel tasks in a cluster with DVFS. Wang, L.; Von Laszewski, G.; Dayal, J.; and Wang, F. In CCGrid 2010 - 10th IEEE/ACM International Conference on Cluster, Cloud, and Grid Computing, 2010.
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Multicores in Cloud Computing: Research Challenges for Applications. Wang, L.; Tao, J.; von Laszewski, G.; and Marten, H. JCP, 5(6): 958-964. 2010.
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Schedule Virtual Machines in a Distributed Service Oriented Environment. Wang, L.; von Laszewski, G.; Kunze, M.; Tao, J.; Dayal, J.; and Rathbone, C. In 24th IEEE International Conference on Advanced Information Networking and Applications, pages 230-236, 2010. Eggenstein-Leopoldshafen, Germany
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Virtual data system on distributed virtual machines in computational grids. Wang, L.; Laszewski, G., V.; Tao, J.; and Kunze, M. International Journal of Ad Hoc and Ubiquitous Computing, 6(4): 194-204. 2010.
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Efficient resource management for cloud computing environments. Younge, A., J.; Von Laszewski, G.; Wang, L.; Lopez-Alarcon, S.; and Carithers, W. In Green Computing Conference, 2010 International, pages 357-364, 2010. IEEE
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  2009 (8)
Grid virtualization engine: design, implementation, and evaluation. Wang, L.; Von Laszewski, G.; Tao, J.; and Kunze, M. IEEE Systems Journal, 3(4): 477-488. 2009.
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Thermal aware workload scheduling with backfilling for green data centers. Wang, L.; von Laszewski, G.; Dayal, J.; and Furlani, T., R. In Performance Computing and Communications Conference (IPCCC), 2009 IEEE 28th International, pages 289-296, 2009. IEEE
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Open grid computing environments. Pierce, M.; Marru, S.; Wu, W.; Kandaswami, G.; von Laszewski, G.; Dooley, R.; Dahan, M.; Wilkins-Diehr, N.; Thomas, M.; and Center, T. In Proceedings of the Fourth Annual TeraGrid Conference, 2009.
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Cyberaide Virtual Applicance: On-Demand Deploying Middleware for Cyberinfrastructure. Kurze, T.; Wang, L.; Von Laszewski, G.; Tao, J.; Kunze, M.; Wang, F.; Kramer, D.; Karl, W.; and Ekanayake, J. In International Conference on Cloud Computing, pages 132-144, 2009. Springer
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Water Threat Management Report. von Laszewski, G. Technical Report 2009.
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Cyberaide creative: On-demand cyberinfrastructure provision in clouds. Rathbone, C.; Wang, L.; Von Laszewski, G.; and Wang, F. In I-SPAN 2009 - The 10th International Symposium on Pervasive Systems, Algorithms, and Networks, 2009.
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Flexible framework for commodity FPGA cluster computing. Espenshade, J.; Lukowiak, M.; Shaaban, M.; and von Laszewski, G. In Field-Programmable Technology, 2009. FPT 2009. International Conference on, pages 465-471, 2009. IEEE
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Towards Thermal Aware Workload Scheduling in a Data Center. Wang, L.; Dayal, J.; and von Laszewski, G. In Pervasive Systems, Algorithms, and Networks (ISPAN), 2009 10th International Symposium on, 2009.
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  undefined (1)
FutureGrid Image Management Framework to Support Cloud and HPC Dynamic Provisioning. Diaz, J.; von Laszewski, G.; Wang, F.; and Fox, G. . .
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