Source: https://pegasus.isi.edu/documentation/publications/
Timestamp: 2019-04-21 14:44:40+00:00

Document:
A. Brinckman, E. Deelman, S. Gupta, J. Nabrzyski, S. Park, R. Ferreira da Silva, I. J. Taylor, and K. Vahi, “Collaborative Circuit Designs using the CRAFT Repository,” Future Generation Computer Systems, vol. 94, p. 841–853, 2019.
P. Chang, G. Allen, W. Anderson, F. B. Bianco, J. S. Bloom, P. R. Brady, A. Brazier, B. S. Cenko, S. M. Couch, T. DeYoung, E. Deelman, Z. B. Etienne, R. J. Foley, D. B. Fox, Z. V. Golkhou, D. R. Grant, C. Hanna, K. Holley-Bockelmann, A. D. Howell, E. A. Huerta, M. W. G. Johnson, M. Juric, D. L. Kaplan, D. S. Katz, A. Keivani, W. Kerzendorf, C. Kopper, M. T. Lam, L. Lehner, Z. Marka, S. Marka, J. Nabrzyski, G. Narayan, B. W. O’Shea, D. Petravick, R. Quick, R. A. Street, I. Taboada, F. Timmes, M. J. Turk, A. Weltman, and Z. Zhang, Cyberinfrastructure Requirements to Enhance Multi-messenger Astrophysics, 2019.
R. Ferreira da Silva, A. Orgerie, H. Casanova, R. Tanaka, E. Deelman, and F. Suter, “Accurately Simulating Energy Consumption of I/O-intensive Scientific Workflows,” in 2019 International Conference on Computational Science (ICCS), 2019.
R. Ferreira da Silva, R. Filgueira, E. Deelman, E. Pairo-Castineira, I. M. Overton, and M. Atkinson, “Using Simple PID-inspired Controllers for Online Resilient Resource Management of Distributed Scientific Workflows,” Future Generation Computer Systems, vol. 95, pp. 615-628, 2019.
D. Garijo, D. Khider, V. Ratnakar, Y. Gil, E. Deelman, R. Ferreira da Silva, C. Knoblock, Y. Chiang, M. Pham, J. Pujara, B. Vu, D. Feldman, R. Mayani, K. Cobourn, C. Duffy, A. Kemanian, L. Shu, V. Kumar, A. Khandelwal, K. Tayal, S. Peckham, M. Stoica, A. Dabrowski, D. Hardesty-Lewis, and S. Pierce, “An Intelligent Interface for Integrating Climate, Hydrology, Agriculture, and Socioeconomic Models,” in ACM 24th International Conference on Intelligent User Interfaces (IUI’19), 2019, p. 111–112.
O. Bhide, R. Hill, K. Vahi, M. Rynge, and V. Velch, “Combating Workflow Failures with Integrity-based Checkpoints and Blockchain,” in 6th International Workshop on Distributed Storage and Blockchain Technologies for Big Data, 2018.
E. Deelman, T. Peterka, I. Altintas, C. D. Carothers, K. K. van Dam, K. Moreland, M. Parashar, L. Ramakrishnan, M. Taufer, and J. Vetter, “The future of scientific workflows,” The International Journal of High Performance Computing Applications, vol. 32, iss. 1, p. 159–175, 2018.
T. M. A. Do, M. Jiang, B. Gallagher, A. Chu, C. Harrison, K. Vahi, and E. Deelman, “Enabling Data Analytics Workflows using Node-Local Storage,” in The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18), Poster, 2018.
T. Estrada, J. Benson, H. Carrillo-Cabada, A. Razavi, M. Cuendet, H. Weinstein, E. Deelman, and M. Taufer, “Graphic Encoding of Macromolecules for Efficient High-Throughput Analysis,” in 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, 2018, pp. 315-324.
R. Ferreira da Silva, D. Garijo, S. Peckham, Y. Gil, E. Deelman, and V. Ratnakar, “Towards Model Integration via Abductive Workflow Composition and Multi-Method Scalable Model Execution,” in 9th International Congress on Environmental Modelling and Software, 2018.
R. Filgueira, R. Ferreira da Silva, E. Deelman, V. Christodoulou, and A. Krause, “IoT-Hub: New IoT data-platform for Virtual Research Environments,” in 10th International Workshop on Science Gateways (IWSG 2018), 2018.
Y. Gil, K. Cobourn, E. Deelman, C. Duffy, R. Ferreira da Silva, A. Kemanian, C. Knoblock, V. Kumar, S. Peckham, L. Carvalho, Y. Chiang, D. Garijo, D. Khider, A. Khandelwal, M. Pahm, J. Pujara, V. Ratnakar, M. Stoica, and B. Vu, “MINT: Model Integration Through Knowledge-Powered Data and Process Composition,” in 9th International Congress on Environmental Modelling and Software, 2018.
T. H. Jordan, S. Callaghan, R. W. Graves, F. Wang, K. R. Milner, C. A. Goulet, P. J. Maechling, K. B. Olsen, Y. Cui, G. Juve, K. Vahi, J. Yu, E. Deelman, and D. Gill, “CyberShake Models of Seismic Hazards in Southern and Central California,” in 11th National Conference in Earthquake Engineering, 2018.
T. H. Jordan, S. Callaghan, R. W. Graves, F. Wang, K. R. Milner, C. A. Goulet, P. J. Maechling, K. B. Olsen, Y. Cui, G. Juve, K. Vahi, J. Yu, E. Deelman, and D. Gill, “CyberShake Models of Seismic Hazards in Southern and Central California,” Seismological Research Letters, vol. 89, iss. 2B, p. 875–876, 2018.
K. Levi, M. Rynge, E. Abeysinghe, and R. A. Edwards, “Searching the Sequence Read Archive Using Jetstream and Wrangler,” in Proceedings of the Practice and Experience on Advanced Research Computing, 2018, p. 50:1–50:7.
S. Pandey, K. Vahi, R. Ferreira da Silva, E. Deelman, M. Jian, C. Harrison, A. Chu, and H. Casanova, Event-Based Triggering and Management of Scientific Workflow Ensembles, 2018.
S. Thapa, R. W. Gardner, K. Herner, D. Hufnagel, D. Lesny, and M. Rynge, “Homogenizing OSG and XSEDE: Providing Access to XSEDE Allocations Through OSG Infrastructure,” in Proceedings of the Practice and Experience on Advanced Research Computing, 2018, p. 15:1–15:7.
B. Tovar, R. Ferreira da Silva, G. Juve, E. Deelman, W. Allcock, D. Thain, and M. Livny, “A Job Sizing Strategy for High-Throughput Scientific Workflows,” IEEE Transactions on Parallel and Distributed Systems, vol. 29, iss. 2, p. 240–253, 2018.
K. Vahi, M. H. Wang, C. Chang, S. Dodelson, M. Rynge, and E. Deelman, “Workflows using Pegasus: Enabling Dark Energy Survey Pipelines,” in 28th annual international Astronomical Data Analysis Software & Systems (ADASS), 2018.
B. P. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, V. Adya, and others, “All-sky search for periodic gravitational waves in the O1 LIGO data,” Physical Review D, vol. 96, iss. 6, p. 62002, 2017.
B. P. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, V. Adya, and others, “Search for gravitational waves from Scorpius X-1 in the first Advanced LIGO observing run with a hidden Markov model,” Physical Review D, vol. 95, iss. 12, p. 122003, 2017.
B. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, V. Adya, and others, “Upper limits on gravitational waves from Scorpius X-1 from a model-based cross-correlation search in Advanced LIGO data,” The Astrophysical Journal, vol. 847, iss. 1, p. 47, 2017.
B. P. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, V. Adya, and others, “First low-frequency Einstein@ Home all-sky search for continuous gravitational waves in Advanced LIGO data,” Physical Review D, vol. 96, iss. 12, p. 122004, 2017.
B. P. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, V. Adya, and others, “Search for intermediate mass black hole binaries in the first observing run of Advanced LIGO,” Physical Review D, vol. 96, iss. 2, p. 22001, 2017.
S. Callaghan, G. Juve, K. Vahi, P. J. Maechling, T. H. Jordan, and E. Deelman, “rvGAHP – Push-based Job Submission using Reverse SSH Connections,” in 12th Workshop on Workflows in Support of Large-Scale Science (WORKS’17), 2017.
E. Deelman, C. Carothers, A. Mandal, B. Tierney, J. S. Vetter, I. Baldin, C. Castillo, G. Juve, D. Krol, V. Lynch, B. Mayer, J. Meredith, T. Proffen, P. Ruth, and R. Ferreira da Silva, “PANORAMA: An Approach to Performance Modeling and Diagnosis of Extreme Scale Workflows,” International Journal of High Performance Computing Applications, vol. 31, iss. 1, p. 4–18, 2017.
R. Ferreira da Silva, R. Filgueira, I. Pietri, M. Jiang, R. Sakellariou, and E. Deelman, “A Characterization of Workflow Management Systems for Extreme-Scale Applications,” Future Generation Computer Systems, vol. 75, p. 228–238, 2017.
R. Ferreira da Silva, S. Callaghan, and E. Deelman, “On the Use of Burst Buffers for Accelerating Data-Intensive Scientific Workflows,” in 12th Workshop on Workflows in Support of Large-Scale Science (WORKS’17), 2017.
Y. Gil, D. Garijo, V. Ratnakar, R. Mayani, R. Adusumilli, H. Boyce, A. Srivastava, and P. Mallick, “Towards Continuous Scientific Data Analysis and Hypothesis Evolution,” in Thirty-First AAAI Conference on Artificial Intelligence, 2017, p. 4406–4414.
B. Jayatilaka, T. Levshina, C. Sehgal, R. Gardner, M. Rynge, and F. Wurthwein, “The OSG Open Facility: an on-ramp for opportunistic scientific computing,” Journal of Physics: Conference Series, vol. 898, iss. 8, p. 82048, 2017.
V. Lynch, J. B. Calvo, E. Deelman, R. Ferreira da Silva, M. Goswami, Y. Hui, E. Lingerfelt, and J. Vetter, “Distributed Workflows for Modeling Experimental Data,” in 2017 IEEE High Performance Extreme Computing Conference (HPEC’17), 2017.
A. Mandal, P. Ruth, I. Baldin, R. Ferreira da Silva, and E. Deelman, “Toward Prioritization of Data Flows for Scientific Workflows Using Virtual Software Defined Exchanges,” in First International Workshop on Workflow Science (WoWS 2017), 2017, p. 566–575.
W. L. Poehlman, M. Rynge, D. Balamurugan, N. Mills, and F. A. Feltus, “OSG-KINC: High-throughput gene co-expression network construction using the open science grid,” in 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017, pp. 1827-1831.
I. Santana-Perez, R. Ferreira da Silva, M. Rynge, E. Deelman, M. S. Perez-Hernandez, and O. Corcho, “Reproducibility of Execution Environments in Computational Science Using Semantics and Clouds,” Future Generation Computer Systems, vol. 67, p. 354–367, 2017.
L. Scientific, B. Abbott, R. Abbott, T. Abbott, F. Acernese, K. Ackley, C. Adams, T. Adams, P. Addesso, R. Adhikari, and others, “GW170104: observation of a 50-solar-mass binary black hole coalescence at redshift 0.2,” Physical Review Letters, vol. 118, iss. 22, p. 221101, 2017.
I. J. Taylor, A. Brinckman, E. Deelman, R. Ferreira da Silva, S. Gupta, J. Nabrzyski, S. Park, and K. Vahi, “Accelerating Circuit Realization via a Collaborative Gateway of Innovations,” in 9th International Workshop on Science Gateways (IWSG 2017), 2017.
W. Chen, R. Ferreira da Silva, E. Deelman, and T. Fahringer, “Dynamic and Fault-Tolerant Clustering for Scientific Workflows,” IEEE Transactions on Cloud Computing, vol. 4, iss. 1, p. 49–62, 2016.
E. Deelman, K. Vahi, M. Rynge, G. Juve, R. Mayani, and R. Ferreira da Silva, “Pegasus in the Cloud: Science Automation through Workflow Technologies,” IEEE Internet Computing, vol. 20, iss. 1, p. 70–76, 2016.
R. Ferreira da Silva, R. Filgueira, E. Deelman, E. Pairo-Castineira, I. M. Overton, and M. Atkinson, “Using Simple PID Controllers to Prevent and Mitigate Faults in Scientific Workflows,” in 11th Workflows in Support of Large-Scale Science (WORKS’16), 2016, p. 15–24.
R. Ferreira da Silva, E. Deelman, R. Filgueira, K. Vahi, M. Rynge, R. Mayani, and B. Mayer, “Automating Environmental Computing Applications with Scientific Workflows,” in Environmental Computing Workshop (ECW’16), IEEE 12th International Conference on e-Science, 2016, p. 400–406.
R. Filgueira, R. Ferreira da Silva, A. Krause, E. Deelman, and M. Atkinson, “Asterism: Pegasus and dispel4py hybrid workflows for data-intensive science,” in 7th International Workshop on Data-Intensive Computing in the Clouds (DataCloud’16), 2016, p. 1–8.
P. Gaikwad, A. Mandal, P. Ruth, G. Juve, D. Krol, and E. Deelman, “Anomaly Detection for Scientific Workflow Applications on Networked Clouds,” in IEEE 2016 International Conference on High Performance Computing & Simulation (HPCS 2016), 2016.
D. Krol, R. Ferreira da Silva, E. Deelman, and V. E. Lynch, “Workflow Performance Profiles: Development and Analysis,” in Euro-Par 2016: Parallel Processing Workshops, , 2016, p. 108–120.
D. Krol, J. Kitowski, R. Ferreira da Silva, G. Juve, K. Vahi, M. Rynge, and E. Deelman, “Science Automation in Practice: Performance Data Farming in Workflows,” in 21st IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2016.
Y. Liu, S. M. Khan, J. Wang, M. Rynge, Y. Zhang, S. Zeng, S. Chen, J. V. Maldonado dos Santos, B. Valliyodan, P. P. Calyam, N. Merchant, H. T. Nguyen, D. Xu, and T. Joshi, “PGen: large-scale genomic variations analysis workflow and browser in SoyKB,” BMC Bioinformatics, vol. 17, iss. 13, p. 337, 2016.
A. Mandal, P. Ruth, I. Baldin, D. Krol, G. Juve, R. Mayani, R. Ferreira da Silva, E. Deelman, J. Meredith, J. Vetter, V. Lynch, B. Mayer, J. Wynne III, M. Blanco, C. Carothers, J. LaPre, and B. Tierney, “Toward an End-to-end Framework for Modeling, Monitoring, and Anomaly Detection for Scientific Workflows,” in Workshop on Large-Scale Parallel Processing (LSPP 2016), 2016, p. 1370–1379.
H. Nawaz, G. Juve, R. Ferreira da Silva, and E. Deelman, “Performance Analysis of an I/O-Intensive Workflow executing on Google Cloud and Amazon Web Services,” in 18th Workshop on Advances in Parallel and Distributed Computational Models (APDCM), 2016, p. 535–544.
W. L. Poehlman, M. Rynge, C. Branton, D. Balamurugan, and F. A. Feltus, “OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid,” Bioinformatics and Biology Insights, vol. 10, p. 133–141, 2016.
High-throughput DNA sequencing technology has revolutionized the study of gene expression while introducing significant computational challenges for biologists. These computational challenges include access to sufficient computer hardware and functional data processing workflows. Both these challenges are addressed with our scalable, open-source Pegasus workflow for processing high-throughput DNA sequence datasets into a gene expression matrix (GEM) using computational resources available to U.S.-based researchers on the Open Science Grid (OSG). We describe the usage of the workflow (OSG-GEM), discuss workflow design, inspect performance data, and assess accuracy in mapping paired-end sequencing reads to a reference genome. A target OSG-GEM user is proficient with the Linux command line and possesses basic bioinformatics experience. The user may run this workflow directly on the OSG or adapt it to novel computing environments.
S. Schlagkamp, R. Ferreira da Silva, E. Deelman, and U. Schwiegelshohn, “Understanding User Behavior: from HPC to HTC,” in International Conference on Computational Science (ICCS), 2016.
S. Schlagkamp, R. Ferreira da Silva, W. Allcock, E. Deelman, and U. Schwiegelshohn, “Consecutive Job Submission Behavior at Mira Supercomputer,” in 25th ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC), 2016.
V. Stodden, M. McNutt, D. H. Balley, E. Deelman, Y. Gil, B. Hanson, M. A. Heroux, J. P. A. Ioannidis, and Taufer, “Enhancing reproducibility for computational methods,” Science, vol. 354, iss. 6317, p. 1240–1241, 2016.
T. L. Swetnam, J. D. Pelletier, C. Rasmussen, N. R. Callahan, N. Merchant, E. Lyons, M. Rynge, Y. Liu, V. Nandigam, and C. Crosby, “Scaling GIS Analysis Tasks from the Desktop to the Cloud Utilizing Contemporary Distributed Computing and Data Management Approaches: A Case Study of Project-based Learning and Cyberinfrastructure Concepts,” in XSEDE16 Conference on Diversity, Big Data, and Science at Scale, 2016, p. 21:1–21:6.
P. Bryk, M. Malawski, G. Juve, and E. Deelman, “Storage-aware Algorithms for Scheduling of Workflow Ensembles in Clouds,” Journal of Grid Computing, vol. 14, iss. 2, p. 359–378, 2015.
W. Chen, R. Ferreira da Silva, E. Deelman, and R. Sakellariou, “Using Imbalance Metrics to Optimize Task Clustering in Scientific Workflow Executions,” Future Generation Computer Systems, vol. 46, p. 69–84, 2015.
E. Deelman, C. Carothers, A. Mandal, B. Tierney, J. S. Vetter, I. Baldin, C. Castillo, G. Juve, D. Krol, V. Lynch, B. Mayer, J. Meredith, T. Proffen, P. Ruth, and R. Ferreira da Silva, “Panorama: Modeling The Performance of Scientific Workflows,” in Workshop on Modeling and Simulation of Systems and Applications (ModSim 2015), 2015.
R. Ferreira da Silva, G. Juve, M. Rynge, E. Deelman, and M. Livny, “Online Task Resource Consumption Prediction for Scientific Workflows,” Parallel Processing Letters, vol. 25, iss. 3, 2015.
R. Ferreira da Silva, M. Rynge, G. Juve, I. Sfiligoi, E. Deelman, J. Letts, F. Wurthwein, and M. Livny, “Characterizing a High Throughput Computing Workload: The Compact Muon Solenoid (CMS) Experiment at LHC,” Procedia Computer Science, International Conference On Computational Science, ICCS 2015 Computational Science at the Gates of Nature, vol. 51, p. 39–48, 2015.
T. Glatard, L. B. Lewis, R. Ferreira da Silva, R. Adalat, N. Beck, C. Lepage, P. Rioux, M. Rousseau, T. Sherif, E. Deelman, N. Khalili-Mahani, and A. C. Evans, “Reproducibility of neuroimaging analyses across operating systems,” Frontiers in Neuroinformatics, vol. 9, iss. 12, 2015.
T. Glatard, R. Ferreira da Silva, N. Boujelben, R. Adalat, N. Beck, P. Rioux, M. Rousseau, E. Deelman, and A. C. Evans, “Boutiques: an application-sharing system based on Linux containers,” in NeuroInformatics 2015, 2015.
J. Howison, E. Deelman, M. J. McLennan, R. Ferreira da Silva, and J. D. Herbsleb, “Understanding the scientific software ecosystem and its impact: Current and future measures,” Research Evaluation, vol. 24, iss. 4, p. 454–470, 2015.
G. Juve, B. Tovar, R. Ferreira da Silva, D. Krol, D. Thain, E. Deelman, W. Allcock, and M. Livny, “Practical Resource Monitoring for Robust High Throughput Computing,” in Workshop on Monitoring and Analysis for High Performance Computing Systems Plus Applications, 2015.
M. Malawski, K. Figiela, M. Bubak, E. Deelman, and J. Nabrzyski, “Scheduling Multilevel Deadline-Constrained Scientific Workflows on Clouds Based on Cost Optimization,” Scientific Programming, vol. 2015, p. 1–13, 2015.
M. Malawski, G. Juve, E. Deelman, and J. Nabrzyski, “Algorithms for Cost- and Deadline-Constrained Provisioning for Scientific Workflow Ensembles in IaaS Clouds,” Future Generation Computer Systems, vol. 48, p. 1–18, 2015.
A. Mandal, P. Ruth, I. Baldin, Y. Xin, C. Castillo, G. Juve, M. Rynge, E. Deelman, and J. Chase, “Adapting Scientific Workflows on Networked Clouds Using Proactive Introspection,” in IEEE/ACM Utility and Cloud Computing (UCC), 2015.
B. Mayer, P. Worley, R. Ferreira da Silva, and A. Gaddis, “Climate Science Performance, Data and Productivity on Titan,” in Cray User Group Conference, 2015.
R. Oda, D. Cordeiro, R. Ferreira da Silva, E. Deelman, and K. Braghetto, “The Case for Resource Sharing in Scientific Workflow Executions,” in XVI Simposio em Sistemas Computacionais de Alto Desempenho (WSCAD), 2015.
R. Quick, S. Hayashi, S. Meroueh, M. Rynge, S. Teige, B. Wang, and D. Xu, “Building a Chemical-Protein Interactome on the Open Science Grid,” Proceedings of Science, International Symposium on Grids and Clouds (ISGC) 2015, 2015.
R. Ferreira da Silva, T. Fahringer, J. J. Durillo, and E. Deelman, “A Unified Approach for Modeling and Optimization of Energy, Makespan and Reliability for Scientific Workflows on Large-Scale Computing Infrastructures,” in Workshop on Modeling and Simulation of Systems and Applications (MODSIM), 2014.
R. Ferreira da Silva, W. Chen, G. Juve, K. Vahi, and E. Deelman, “Community Resources for Enabling Research in Distributed Scientific Workflows,” in 10th IEEE International Conference on e-Science (eScience 2014), 2014.
T. Glatard, L. B. Lewis, R. Ferreira da Silva, M. Rousseau, C. Lepage, P. Rioux, N. Mahani, E. Deelman, and A. C. Evans, “Extending provenance information in CBRAIN to address reproducibility issues across computing platforms,” in NeuroInformatics 2014, 2014.
G. Juve, B. Tovar, R. Ferreira da Silva, C. Robinson, D. Thain, E. Deelman, W. Allcock, and M. Livny, “Practical Resource Monitoring for Robust High Throughput Computing,” University of Southern California, Technical Report 14-950, 2014.
M. Malawski, K. Figiela, M. Bubak, E. Deelman, and J. Nabrzyski, “Cost Optimization of Execution of Multi-level Deadline-Constrained Scientific Workflows on Clouds,” Parallel Processing and Applied Mathematics, pp. 251-260, 2014.
M. McLennan, S. Clark, E. Deelman, M. Rynge, K. Vahi, F. McKenna, D. Kearney, and C. Song, “HUBzero and Pegasus: integrating scientific workflows into science gateways,” Concurrency and Computation: Practice and Experience, 2014.
I. Pietri, G. Juve, E. Deelman, and R. Sakellariou, “A Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud,” in 9th Workshop on Workflows in Support of Large-Scale Science (WORKS), 2014.
I. Santana-Perez, R. Ferreira da Silva, M. Rynge, E. Deelman, M. S. Perez-Hernandez, and O. Corcho, “Leveraging Semantics to Improve Reproducibility in Scientific Workflows,” in The reproducibility at XSEDE workshop, 2014.
I. Santana-Perez, R. Ferreira da Silva, M. Rynge, E. Deelman, M. S. Perez-Hernandez, and O. Corcho, “A Semantic-Based Approach to Attain Reproducibility of Computational Environments in Scientific Workflows: A Case Study,” in 1st International Workshop on Reproducibility in Parallel Computing (REPPAR), in conjunction with Euro-Par 2014, 2014.
S. Srinivasan, G. Juve, R. Ferreira da Silva, K. Vahi, and E. Deelman, “A Cleanup Algorithm for Implementing Storage Constraints in Scientific Workflow Executions,” in 9th Workshop on Workflows in Support of Large-Scale Science (WORKS), 2014.
S. Azarnoosh, M. Rynge, G. Juve, E. D. M. Nieć, M. Malawski, and R. Ferreira da Silva, “Introducing PRECIP: An API for Managing Repeatable Experiments in the Cloud,” in Workshop on Cloud Computing for Research Collaborations (CRC), 2013.
B. G. Berriman, G. Juve, J. Vöckler, E. Deelman, and M. Rynge, “The Application of Cloud Computing to Scientific Workflows: A Study of Cost and Performance,” Proceedings of the Royal Society A, vol. 371, iss. 1983, 2013.
W. Chen, R. Ferreira da Silva, E. Deelman, and R. Sakellariou, “Balanced Task Clustering in Scientific Workflows,” in 9th IEEE International Conference on e-Science (eScience 2013), 2013.
W. Chen, E. Deelman, and R. Sakellariou, “Imbalance Optimization in Scientific Workflows,” in International Conference on Supercomputing (ICS 2013), 2013.
E. Deelman, G. Juve, M. Malawski, and J. Nabrzyski, “Hosted Science: Managing Computational Workloads in the Cloud,” Parallel Processing Letters, vol. 23, iss. 2, 2013.
R. Ferreira da Silva, G. Juve, E. Deelman, T. Glatard, F. Desprez, D. Thain, B. Tovar, and M. Livny, “Toward Fine-Grained Online Task Characteristics Estimation in Scientific Workflows,” in 8th Workshop On Workflows in Support of Large-Scale Science (WORKS), 2013.
G. Juve, A. Chervenak, E. Deelman, S. Bharathi, G. Mehta, and K. Vahi, “Characterizing and Profiling Scientific Workflows,” Future Generation Computer Systems, vol. 29, iss. 3, pp. 682-692, 2013.
G. Juve, M. Rynge, E. Deelman, J. Vöckler, and B. G. Berriman, “Comparing FutureGrid, Amazon EC2, and Open Science Grid for Scientific Workflows,” Computing in Science and Engineering, vol. 15, iss. 4, pp. 20-29, 2013.
A. Mandal, P. Ruth, I. Baldin, Y. Xin, C. Castillo, M. Rynge, and E. Deelman, “Evaluating I/O Aware Network Management for Scientific Workflows on Networked Clouds,” in The 3rd International Workshop on Network-aware Data Management, in conjunction with SC13, 2013.
M. McLennan, S. Clark, F. McKenna, E. Deelman, M. Rynge, K. Vahi, D. Kearney, and C. Song, “Bringing Scientific Workflow to the Masses via Pegasus and HUBzero,” in Proceedings of the 5th International Workshop on Science Gateways, 2013.
I. Pietri, M. Malawski, G. Juve, E. Deelman, J. Nabrzyski, and R. Sakellariou, “Energy-Constrained Provisioning for Scientific Workflow Ensembles,” in IEEE International Conference on Cloud and Green Computing (CGC13), 2013.
M. Rynge, G. Juve, J. Kinney, J. Good, B. G. Berriman, A. Merrihew, and E. Deelman, “Producing an Infrared Multiwavelength Galactic Plane Atlas using Montage, Pegasus and Amazon Web Services,” in 23rd Annual Astronomical Data Analysis Software and Systems (ADASS) Conference, 2013.
K. Vahi, I. Harvey, T. Samak, D. Gunter, K. Evans, D. Rogers, I. Taylor, M. Goode, F. Silva, E. Al-Shakarchi, G. Mehta, and E. D. andrew Jones, “A Case Study into Using Common Real-Time Workflow Monitoring Infrastructure for Scientific Workflows,” Journal of Grid Computing, vol. 11, iss. 3, pp. 381-406, 2013.
K. Vahi, M. Rynge, G. Juve, R. Mayani, and E. Deelman, “Rethinking Data Management for Big Data Scientific Workflows,” in Workshop on Big Data and Science: Infrastructure and Services, 2013.
R. Agarwal, G. Juve, and E. Deelman, “Peer-to-Peer Data Sharing for Scientific Workflows on Amazon EC2,” in 7th Workshop on Workflows in Support of Large-Scale Science (WORKS12), 2012.
B. G. Berriman, C. Brinkworth, D. Gelino, D. K. Wittman, E. Deelman, G. Juve, M. Rynge, and J. Kinney, “A Tale Of 160 Scientists, Three Applications, A Workshop and A Cloud,” in Astronomical Data Analysis Software and Systems XXII, 2012.
W. Chen and E. Deelman, “WorkflowSim: A Toolkit for Simulating Scientific Workflows in Distributed Environments,” in The 8th IEEE International Conference on eScience 2012 (eScience 2012), 2012.
W. Chen and E. Deelman, “Integration of Workflow Partitioning and Resource Provisioning,” in The 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2012), Doctoral Symposium, 2012.
W. Chen and E. Deelman, “Fault Tolerant Clustering in Scientific Workflows,” in IEEE 6th International Workshop on Scientific Workflows (SWF 2012) in conjunction with IEEE 8th World Congress on Services (SERVICES 2012), 2012.
A. L. Chervenak, D. E. Smith, W. Chen, and E. Deelman, “Integrating Policy with Scientific Workflow Management for Data-Intensive Applications,” in The 7th Workshop on Workflows in Support of Large-Scale Science (WORKS12), 2012.
E. Deelman, G. Juve, and B. G. Berriman, “Using Clouds for Science, Is it Just Kicking the Can Down The Road?,” in 2nd International Conference on Cloud Computing and Services Science (CLOSER 2012), 2012.
G. Juve, E. Deelman, B. G. Berriman, B. P. Berman, and P. J. Maechling, “An Evaluation of the Cost and Performance of Scientific Workflows on Amazon EC2,” Journal of Grid Computing, vol. 10, iss. 1, pp. 5-21, 2012.
M. Malawski, G. Juve, E. Deelman, and J. Nabrzyski, “Cost- and Deadline-Constrained Provisioning for Scientific Workflow Ensembles in IaaS Clouds,” in 24th IEEE/ACM International Conference on Supercomputing (SC12), 2012.
M. Rynge, G. Juve, K. Vahi, S. Callaghan, G. Mehta, P. J. Maechling, and E. Deelman, “Enabling Large-scale Scientific Workflows on Petascale Resources Using MPI Master/Worker,” in XSEDE12, 2012.
T. Samak, D. Gunter, M. Goode, E. Deelman, G. Juve, and F. Silva, “Failure Analysis of Distributed Scientific Workflows Executing in the Cloud,” in 8th International Conference on Network and Service Management (CNSM 2012), 2012.
K. Vahi, I. Harvey, T. Samak, D. Gunter, K. Evans, D. Rogers, I. Taylor, M. Goode, F. Silva, E. Al-Shakarchi, G. M. andrew Jones, and E. Deelman, “A General Approach to Real-time Workflow Monitoring,” in The 7th Workshop on Workflows in Support of Large-Scale Science (WORKS12), 2012.
B. G. Berriman, J. Good, E. Deelman, and A. Alexov, “Ten years of software sustainability at the Infrared Processing and Analysis Center,” Phil. Trans. R. Soc. A, vol. 369, pp. 3384-3397, 2011.
E. Byun, Y. Kee, J. Kim, E. Deelman, and S. Maeng, “BTS: Resource Capacity Estimate for Time-targeted Science Workflows,” Journal of Parallel and Distributed Computing: Special Issue on Cloud Computing, vol. 71, iss. 6, pp. 848-862, 2011.
S. Callaghan, P. Maechling, P. Small, K. Milner, G. Juve, T. H. Jordan, E. Deelman, G. Mehta, K. Vahi, D. Gunter, and K. Beattie, “Metrics for Heterogeneous Scientific Workflows: A Case Study of an Earthquake Science Application,” International Journal of High Performance Computing Applications, vol. 25, iss. 3, pp. 274-285, 2011.
W. Chen and E. Deelman, “Partitioning and Scheduling Workflows across Multiple Sites with Storage Constraints,” in 9th International Conference on Parallel Processing and Applied Mathmatics, 2011.
W. Chen and E. Deelman, “Workflow Overhead Analysis and Optimizations,” in 6th Workshop on Workflows in Support of Large-Scale Science (WORKS 11), 2011.
D. Gunter, E. Deelman, T. Samak, C. Brooks, M. Goode, G. Juve, G. Mehta, P. Moraes, F. Silva, M. Swany, and K. Vahi, “Online Workflow Management and Performance Analysis with Stampede,” in 7th International Conference on Network and Service Management (CNSM-2011), 2011.
G. Juve and E. Deelman, “Automating Application Deployment in Infrastructure Clouds,” in 3rd IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2011), 2011.
G. Juve and E. Deelman, “Wrangler: Virtual Cluster Provisioning for the Cloud,” in Proceedings of the 20th International Symposium on High Performance Distributed Computing (HPDC11), 2011.
G. Mehta, E. Deelman, J. A. Knowles, T. Chen, Y. Wang, J. Vöckler, S. Buyske, and T. Matise, “Enabling Data and Compute Intensive Workflows in Bioinformatics,” in 2nd International Workshop onHigh Performance Bioinformatics and Biomedicine (HiBB 2011) in conjunction with Euro-Par Conference 2011, 2011.
A. Nagavaram, G. Agrawal, M. Freitas, G. Mehta, R. Mayani, and E. Deelman, “A Cloud‐based Dynamic Workflow for Mass Spectrometry Data Analysis,” in Proceedings of the 7th IEEE International Conference on e-Science (e-Science 2011), 2011.
M. Rynge, G. Juve, G. Mehta, E. Deelman, K. Larson, B. Holzman, I. Sfiligoi, F. Würthwein, B. G. Berriman, and S. Callaghan, “Experiences Using GlideinWMS and the Corral Frontend Across Cyberinfrastructures,” in Proceedings of the 7th IEEE International Conference on e-Science (e-Science 2011), 2011.
T. Samak, D. Gunter, E. Deelman, G. Juve, G. Mehta, F. Silva, and K. Vahi, “Online Fault and Anomaly Detection for Large-Scale Scientific Workflows,” in 13th IEEE International Conference on High Performance Computing and Communications (HPCC-2011), 2011.
T. Samak, D. Gunter, M. Goode, E. Deelman, G. Mehta, F. Silva, and K. Vahi, “Failure Prediction and Localization in Large Scientific Workflows,” in 6th Workshop on Workflows in Support of Large-Scale Science (WORKS 11), 2011.
J. Vöckler, G. Juve, E. Deelman, M. Rynge, and B. G. Berriman, “Experiences Using Cloud Computing for A Scientific Workflow Application,” in Proceedings of 2nd Workshop on Scientific Cloud Computing (ScienceCloud 2011), 2011.
Y. Wang, G. Mehta, R. Mayani, J. Lu, T. Souaiaia, Y. C. andrew Clark, H. J. Yoon, L. Wan, O. V. Evgrafov, J. A. Knowles, E. Deelman, and T. Chen, “RseqFlow: Workflows for RNA-Seq Data Analysis,” Bioinformatics, vol. 27, iss. 18, pp. 2598-2600, 2011.
B. G. Berriman, E. Deelman, P. Groth, and G. Juve, “The Application of Cloud Computing to the Creation of Image Mosaics and Management of Their Provenance,” in SPIE Conference 7740: Software and Cyberinfrastructure for Astronomy, 2010.
B. G. Berriman, G. Juve, E. Deelman, M. Regelson, and P. Plavchan, “The Application of Cloud Computing to Astronomy: A Study of Cost and Performance,” in In Workshop on e-Science challenges in Astronomy and Astrophysics in conjunction with the 6th IEEE International Conference on e-Science (e-Science 2010), 2010.
R. Bolze and E. Deelman, “Exploiting the Cloud of Computing Environments: An Application’s Perspective,” in Cloud Computing and Software Services: Theory and Techniques, S. A. Ahson and M. Ilyas, Eds., CRC Press, 2010.
S. Callaghan, E. Deelman, D. Gunter, G. Juve, P. Maechling, C. Brooks, K. Vahi, K. Milner, R. Graves, E. Field, D. Okaya, and T. Jordan, “Scaling up Workflow-based Applications,” Journal of Computer and System Sciences, vol. 76, iss. 6, pp. 428-446, 2010.
Y. Gil, V. Ratnakar, and E. D. et al, “Wings: Intelligent Workflow-Based Design of Computational Experiments,” IEEE Intelligent Systems, 2010.
R. Graves, T. Jordan, S. Callaghan, E. Deelman, E. Field, G. Juve, C. Kesselman, P. Maechling, G. Mehta, K. Milner, D. Okaya, P. Small, and K. Vahi, “CyberShake: A Physics-Based Seismic Hazard Model for Southern California,” Pure and Applied Geophysics, 2010.
G. Juve, E. Deelman, K. Vahi, and G. Mehta, “Experiences with Resource Provisioning for Scientific Workflows Using Corral,” Scientific Programming, vol. 18, iss. 2, pp. 77-92, 2010.
G. Juve, E. Deelman, K. Vahi, G. Mehta, B. Berriman, B. P. Berman, and P. J. Maechling, “Data Sharing Options for Scientific Workflows on Amazon EC2,” in 22nd IEEE/ACM Conference on Supercomputing (SC10), 2010.
G. Juve and E. Deelman, “Scientific Workflows in the Cloud,” in Grids, Clouds and Virtualization, M. Cafaro and G. Aloisio, Eds., Springer, 2010, p. 71–91.
G. Juve and E. Deelman, “Scientific Workflows and Clouds,” ACM Crossroads, vol. 16, iss. 3, pp. 14-18, 2010.
V. S. Kumar, T. Kurc, V. Ratnakar, J. Kim, G. Mehta, K. Vahi, Y. L. Nelson, P. Sadayappan, E. Deelman, Y. Gil, M. Hall, and J. Saltz, “Parameterized Specification, Configuration and Execution of Data-intensive Scientific Workflows,” Cluster Computing Journal, vol. 13, iss. 3, pp. 315-333, 2010.
R. Sakellariou, H. Zhao, and E. Deelman, “Mapping Workflows on Grid Resources: Experiments with the Montage Workflow,” in Grids, P2P and Services Computing, Springer, 2010, pp. 119-132.
M. Sonntag, D. Karastoyanova, and E. Deelman, “BPEL4Pegasus: Combining Business and Scientific Workflows,” in International Conference on Service-Oriented Computing (ICSOC), 2010.
M. Sonntag, D. Karastoyanova, and E. Deelman, “Bridging The Gap Between Business And Scientific Workflows,” in e-Science 2010, 2010.
E. Deelman, “Grids and Clouds: Making Workflow Applications Work in Heterogeneous Distributed Environments,” International Journal of High Performance Computing Applications, 2009.
P. Groth, E. Deelman, G. Juve, G. Mehta, and B. Berriman, “Pipeline-Centric Provenance Model,” in 4th Workshop on Workflows in Support of Large-Scale Science (WORKS 09), 2009.
G. Juve, E. Deelman, K. Vahi, G. Mehta, B. Berriman, B. P. Berman, and P. J. Maechling, “Scientific Workflow Applications on Amazon EC2,” in Workshop on Cloud-based Services and Applications, 2009.
V. S. Kumar, P. Sadayappan, G. Mehta, K. Vahi, E. Deelman, V. Ratnakar, J. Kim, Y. Gil, M. W. Hall, T. M. Kurç, and J. H. Saltz, “An Integrated Framework for Performance-based Optimization of Scientific Workflows,” in Conference on High Performance and Distributed Computing (HPDC), 2009.
K. Lee, N. W. Paton, R. Sakellariou, E. Deelman, A. A. A. Fernandes, and G. Mehta, “Adaptive Workflow Processing and Execution in Pegasus,” Concurrency and Computation: Practice and Experience, vol. 21, iss. 16, pp. 1965-1981, 2009.
R. Sakellariou, H. Zhao, and E. Deelman, “Mapping Workflows on Grid Resources: Experiments with the Montage Workflow,” in CoreGrid, 2009.
S. Bharathi, A. Chervenak, E. Deelman, G. Mehta, M. Su, and K. Vahi, “Characterization of Scientific Workflows,” in 3rd Workshop on Workflows in Support of Large-Scale Science (WORKS08), 2008.
S. Callaghan, P. Maechling, E. Deelman, K. Vahi, G. Mehta, G. Juve, K. Milner, R. Graves, E. Field, D. Okaya, D. Gunter, K. Beattie, and T. Jordan, “Reducing Time-to-Solution Using Distributed High-Throughput Mega-Workflows – Experiences from SCEC CyberShake,” in Fourth IEEE International Conference on e-Science (e-Science 2008), 2008.
E. Deelman, G. Singh, M. Livny, B. Berriman, and J. Good, “The Cost of Doing Science on the Cloud: The Montage Example,” in Supercomputing 2008, 2008.
E. Deelman, D. Gannon, M. Shields, and I. Taylor, “Workflows and e-Science: An Overview of Workflow System Features and Capabilities,” Future Generation Computer Systems, 2008.
E. Deelman and A. Chervenak, “Data Management Challenges of Data-Intensive Scientific Workflows,” in 3rd International Workshop on Workflow Systems in e-Science (WSES 08), in conjunction with CCGrid 2008, 2008.
C. Hoffa, G. Mehta, T. Freeman, E. Deelman, K. Keahey, B. Berriman, and J. Good, “On the Use of Cloud Computing for Scientific Workflows,” in 3rd International Workshop on Scientific Workflows and Business Workflow Standards in e-Science (SWBES) in conjunction with Fourth IEEE International Conference on e-Science (e-Science 2008), 2008.
G. Juve and E. Deelman, “Resource Provisioning Options for Large-Scale Scientific Workflows,” in Third International Workshop on Scientific Workflows and Business Workflow Standards in e-Science (SWBES) in conjunction with Fourth IEEE International Conference on e-Science (e-Science 2008), 2008.
K. Lee, N. W. Paton, R. Sakellariou, E. Deelman, A. A. A. Fernandes, and G. Mehta, “Adaptive Workflow Processing and Execution in Pegasus,” in 3rd International Workshop on Workflow Management and Applications in Grid Environments (WaGe08), 2008.
S. Miles, P. Groth, E. Deelman, K. Vahi, G. Mehta, and L. Moreau, “Provenance: The Bridge Between Experiments and Data,” Computing in Science and Engineering, vol. 10, iss. 3, pp. 38-46, 2008.
G. Singh, M. Su, K. Vahi, E. Deelman, B. Berriman, J. Good, D. S. Katz, and G. Mehta, “Workflow Task Clustering for Best Effort Systems with Pegasus,” in Mardi Gras Conference, 2008.
B. G. Berriman, E. Deelman, J. Good, J. C. Jacob, D. S. Katz, A. C. Laity, T. A. Prince, G. Singh, and M. Su, “Generating Complex Astronomy Workflows,” in Workflows for e-Science, , 2007.
A. Chervenak, E. Deelman, M. Livny, M. Su, R. Schuler, S. Bharathi, G. Mehta, and K. Vahi, “Data Placement for Scientific Applications in Distributed Environments,” in Proceedings of Grid Conference 2007, 2007.
E. Deelman, G. Mehta, G. Singh, M. Su, and K. Vahi, “Pegasus: Mapping Large-Scale Workflows to Distributed Resources,” in Workflows for e-Science, , 2007.
Y. Gil, E. Deelman, M. Ellisman, T. Fahringer, G. Fox, D. Gannon, C. Goble, M. Livny, L. Moreau, and J. Myers, “Examining the Challenges of Scientific Workflows,” IEEE Computer, vol. 40, iss. 12, pp. 24-32, 2007.
Y. Gil, V. Ratnakar, E. Deelman, G. Mehta, and J. Kim, “Wings for Pegasus: Creating Large-Scale Scientific Applications Using Semantic Representations of Computational Workflows,” in Proceedings of the 19th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2007.
J. Kim, E. Deelman, Y. Gil, G. Mehta, and V. Ratnakar, “Provenance Trails in the Wings/Pegasus Workflow System,” Concurrency and Computation: Practice and Experience, Special Issue on the First Provenance Challenge, 2007.
P. Maechling, E. Deelman, L. Zhao, R. Graves, G. Mehta, N. Gupta, J. Mehringer, C. Kesselman, S. Callaghan, D. Okaya, H. Francoeur, V. Gupta, Y. Cui, K. Vahi, T. Jordan, and E. Field, “SCEC CyberShake Workflows: Automating Probabilistic Seismic Hazard Analysis Calculations,” in Workflows for e-Science, , 2007.
N. Mandal, E. Deelman, G. Mehta, M. Su, and K. Vahi, “Integrating Existing Scientific Workflow Systems: The Kepler/Pegasus Example,” in Proceedings of the Second Workshop on Workflows in Support of Large-Scale Science (WORKS07), 2007.
S. Miles, E. Deelman, P. Groth, K. Vahi, G. Mehta, and L. Moreau, “Connecting Scientific Data to Scientific Experiments with Provenance,” in Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007), 2007.
A. Ramakrishnan, G. Singh, H. Zhao, E. Deelman, R. Sakellariou, K. Vahi, K. Blackburn, D. Meyers, and M. Samidi, “Scheduling Data-Intensive Workflows onto Storage-Constrained Distributed Resources,” in Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid), 2007.
G. Singh, K. Vahi, A. Ramakrishnan, G. Mehta, E. Deelman, H. Zhao, R. Sakellariou, K. Blackburn, D. Brown, S. Fairhurst, D. Meyers, and B. G. Berriman, “Optimizing Workflow Data Footprint,” Special issue of the Scientific Programming Journal dedicated to Dynamic Computational Workflows: Discovery, Optimisation and Scheduling, 2007.
E. Deelman, S. Callaghan, E. Field, H. Francoeur, R. Graves, N. Gupta, V. Gupta, T. H. Jordan, C. Kesselman, P. Maechling, J. Mehringer, G. Mehta, D. Okaya, K. Vahi, and L. Zhao, “Managing Large-Scale Workflow Execution from Resource Provisioning to Provenance tracking: The CyberShake Example,” in e-Science 2006, 2006.
E. Deelman and Y. Gil, “Managing Large-Scale Scientific Workflows in Distributed Environments: Experiences and Challenges,” in Workflows in e-Science, 2006.
A. Lathers, M. Su, A. Kulungowski, A. W. Lin, G. Mehta, S. T. Peltier, E. Deelman, and M. H. Ellisman, “Enabling Parallel Scientific Applications with Workflow Tools,” in Proceedings of Challenges of Large Applications in Distributed Environments (CLADE), 2006.
V. Nefedova, R. Jacob, I. Foster, Z. Liu, Y. Liu, E. Deelman, G. Mehta, M. Su, and K. Vahi, “Automating Climate Science: Large Ensemble Simulations on the TeraGrid with the GriPhyN Virtual Data System,” in e-Science 2006, 2006.
G. Singh, C. Kesselman, and E. Deelman, “Application-level Resource Provisioning on the Grid,” in e-Science 2006, 2006.
I. Taylor, E. Deelman, D. Gannon, and M. Shield, Workflows for e-Science, Springer, 2006.
J. Vöckler, G. Mehta, Y. Zhao, E. Deelman, and M. Wilde, “Kickstarting Remote Applications,” in Second International Workshop on Grid Computing Environments (GCE06), 2006.
J. Blythe, S. Jain, E. Deelman, Y. Gil, K. Vahi, A. Mandal, and K. Kennedy, “Task Scheduling Strategies for Workflow-based Applications in Grids,” in CCGrid 2005, 2005.
D. S. Katz, J. C. Jacob, B. G. Berriman, J. Good, A. C. Laity, E. Deelman, C. Kesselman, G. Singh, M. Su, and T. A. Prince, “Comparison of Two Methods for Building Astronomical Image Mosaics on a Grid,” in International Conference on Parallel Processing (ICPP), 2005.
P. Maechling, H. Chalupsky, M. Dougherty, E. Deelman, Y. Gil, S. Gullapalli, V. Gupta, C. Kesselman, J. Kim, G. Mehta, B. Mendenhall, T. A. Russ, G. Singh, M. Spraragen, G. Staples, and K. Vahi, “Simplifying construction of complex workflows for non-expert users of the Southern California Earthquake Center Community Modeling Environment,” SIGMOD Record, vol. 34, iss. 3, pp. 24-30, 2005.
G. Singh, E. Deelman, G. Mehta, K. Vahi, M. Su, B. G. Berriman, J. Good, J. C. Jacob, D. S. Katz, A. Lazzarini, K. Blackburn, and S. Koranda, “The Pegasus Portal: Web Based Grid Computing,” in The 20th Annual ACM Symposium on Applied Computing, 2005.
G. Singh, C. Kesselman, and E. Deelman, “Optimizing Grid-Based Workflow Execution,” Journal of Grid Computing, vol. 3, iss. 3-4, pp. 201-219, 2005.
E. Deelman, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, S. Patil, M. Su, K. Vahi, and M. Livny, “Pegasus: Mapping Scientific Workflows onto the Grid,” in Across Grids Conference, 2004.
Y. Gil, E. Deelman, J. Blythe, C. Kesselman, and H. Tangmurarunkit, “Artificial Intelligence and Grids: Workflow Planning and Beyond,” IEEE Intelligent Systems, 2004.
B. G. Berriman, J. C. Good, A. C. Laity, A. Bergou, J. C. Jacob, D. S. Katz, E. Deelman, C. Kesselman, G. Singh, M. Su, and R. Williams, “Montage: A Grid Enabled Image Mosaic Service for the National Virtual Observatory,” in ADASS XIII, 2003.
J. Blythe, R. Cavanaugh, E. Deelman, I. Foster, S. Jang, C. Kesselman, K. Marzullo, R. Moore, V. Taylor, and X. Zhang, “Types of Editors and Specifications,” GriPhyN, Technical Report 2004-23, 2003.
J. Blythe, E. Deelman, Y. Gil, and C. Kesselman, “Transparent Grid Computing: a Knowledge-Based Approach,” in IAAI, 2003.
J. Blythe, E. Deelman, and Y. Gil, “Planning for workflow construction and maintenance on the Grid,” in 2003 ICAPS Workshop on Planning for Web Services, 2003.
J. Blythe, E. Deelman, Y. Gil, C. Kesselman, A. Agarwal, G. Mehta, and K. Vahi, “The Role of Planning in Grid Computing,” in ICAPS, 2003.
E. Deelman, J. Blythe, Y. Gil, and C. Kesselman, “Workflow Management in GriPhyN,” in Grid Resource Management, J. Nabrzyski J. Schopf and J. Weglarz, Eds., Kluwer, 2003.
E. Deelman, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, K. Vahi, K. Blackburn, A. Lazzarini, A. Arbree, R. Cavanaugh, and S. Koranda, “Mapping Abstract Complex Workflows onto Grid Environments,” Journal of Grid Computing, vol. 1, iss. 1, pp. 25-39, 2003.
E. Deelman, J. Blythe, Y. Gil, C. Kesselman, S. Koranda, A. Lazzarini, G. Mehta, M. A. Papa, and K. Vahi, “Pegasus and the Pulsar Search: From Metadata to Execution on the Grid,” in Applications Grid Workshop, PPAM 2003, 2003.
E. Deelman, R. Plante, C. Kesselman, G. Singh, M. Su, G. Greene, R. Hanisch, N. Gaffney, A. Volpicelli, J. Annis, V. Sekhri, T. Budavari, M. Nieto-Santisteban, W. O’Mullane, D. Bohlender, T. McGlynn, A. Rots, and O. Pevunova, “Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory,” in Supercomputing 2003, 2003.
E. Deelman, J. Blythe, Y. Gil, C. Kesselman, G. Mehta, K. Vahi, S. Koranda, A. Lazzarini, and M. A. Papa, “From Metadata to Execution on the Grid Pegasus and the Pulsar Search,” GriPhyN, Technical Report 2003-15, 2003.
E. Deelman, I. Foster, C. Kesselman, R. Moore, and S. Ranka, “Overall Architecture and Control Flow,” GriPhyN, Technical Report 2004-24, 2003.
G. Singh and E. Deelman, “Montage on the Grid,” NVO, Technical Report, 2003.
R. Williams, B. G. Berriman, E. Deelman, J. Good, J. C. Jacob, C. Kesselman, C. Lonsdale, S. Oliver, and T. A. Prince, “Multi-Wavelength Image Space: Another Grid-Enabled Science,” Journal of Concurrency and Computation: Practice and Experience, 2003.
E. Deelman, C. Kesselman, G. Mehta, L. Meshkat, L. Pearlman, K. Blackburn, P. Ehrens, A. Lazzarini, R. Williams, and S. Koranda, “GriPhyN and LIGO, Building a Virtual Data Grid for Gravitational Wave Scientists,” in High Performance Distributed Computing (HPDC), 2002.
E. Deelman, J. Blythe, Y. Gil, and C. Kesselman, “Pegasus: Planning for Execution in Grids,” GriPhyN, Technical Report 2002-20, 2002.

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