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Lavanya Ramakrishnan

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Lavanya Ramakrishnan
Senior Scientist/SciData Division Deputy
Phone: +1 510 486 4384

Biographical Sketch

Lavanya Ramakrishnan is a senior scientist at Lawrence Berkeley National Laboratory. She started at the Lab in 2009 as an Alvarez Fellow and has also served as group lead for the Usable Software Systems group. Ramakrishnan has over 15 years of experience working on grants funded from various federal agencies including DOE, NSF, DOD, DARPA in various roles. Her research interests are in building software tools for computational and data-intensive science with a focus on workflow, resource, and data management. More recently, she has been using user research methods to understand as well as verify/validate the context of use and social challenges that often impact tool design and development. She currently leads a number of project teams that consist of a mix of social scientists, software engineers, and computer scientists.

Ramakrishnan has also worked closely with scientists from multiple domains including bioinformatics, biomedical science, storm-surge modeling, weather modeling, high-energy physics, and light source facilities. She has previously worked as a research staff member at Renaissance Computing Institute and MCNC in North Carolina. She has an M.S. and Ph.D. in Computer Science from Indiana University and a bachelor's degree in computer engineering from VJTI, University of Mumbai. She joined Berkeley Lab as an Alvarez Postdoctoral Fellow in 2009.

 »Publications

Journal Articles

Devarshi Ghoshal, Ludovico Bianchi, Abdelilah Essiari, Michael Beach, Drew Paine, Lavanya Ramakrishnan, "Science Capsule - Capturing the Data Life Cycle", Journal of Open Source Software, 2021, 6:2484, doi: 10.21105/joss.02484

D. A. Agarwal, J. Damerow, C. Varadharajan, D. S. Christianson, G. Z. Pastorello, Y.-W. Cheah, L. Ramakrishnan, "Balancing the needs of consumers and producers for scientific data collections", Ecological Informatics, 2021, 62:101251, doi: 10.1016/j.ecoinf.2021.101251

Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, "Experiences with a Flexible User Research Process to Build Data Change Tools", Journal of Open Research Software, September 1, 2020, doi: 10.5334/jors.284

Scientific software development processes are understood to be distinct from commercial software development practices due to uncertain and evolving states of scientific knowledge. Sustaining these software products is a recognized challenge, but under-examined is the usability and usefulness of such tools to their scientific end users. User research is a well-established set of techniques (e.g., interviews, mockups, usability tests) applied in commercial software projects to develop foundational, generative, and evaluative insights about products and the people who use them. Currently these approaches are not commonly applied and discussed in scientific software development work. The use of user research techniques in scientific environments can be challenging due to the nascent, fluid problem spaces of scientific work, varying scope of projects and their user communities, and funding/economic constraints on projects.

In this paper, we reflect on our experiences undertaking a multi-method user research process in the Deduce project. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists make decisions around data change. There is a lack of common terminology since the concept of systematically measuring and managing data change is under explored in scientific environments. To bridge this gap we conducted user research that focuses on user practices, needs, and motivations to help us design and develop metrics and tools for data change. This paper contributes reflections and the lessons we have learned from our experiences. We offer key takeaways for scientific software project teams to effectively and flexibly incorporate similar processes into their projects.

E Deelman, T Peterka, I Altintas, CD Carothers, KK van Dam, K Moreland, M Parashar, L Ramakrishnan, M Taufer, J Vetter, "The future of scientific workflows", International Journal of High Performance Computing Applications, 2018, 32:159--175, doi: 10.1177/1094342017704893

GP Rodrigo, PO Östberg, E Elmroth, K Antypas, R Gerber, L Ramakrishnan, "Towards understanding HPC users and systems: A NERSC case study", Journal of Parallel and Distributed Computing, 2018, 111:206--221, doi: 10.1016/j.jpdc.2017.09.002

GH Weber, MS Bandstra, DH Chivers, HH Elgammal, V Hendrix, J Kua, JS Maltz, K Muriki, Y Ong, K Song, MJ Quinlan, L Ramakrishnan, BJ Quiter, "Web-based visual data exploration for improved radiological source detection", Concurrency Computation, 2017, 29, doi: 10.1002/cpe.4203

D Ghoshal, V Hendrix, W Fox, S Balasubhramanian, L Ramakrishnan, "FRIEDA: Flexible Robust Intelligent Elastic Data Management Framework", The Journal of Open Source Software, 2017, 2:164--164, doi: 10.21105/joss.00164

M Verma, JB Fisher, K Mallick, Y Ryu, H Kobayashi, A Guillaume, G Moore, L Ramakrishnan, V Hendrix, S Wolf, M Sikka, G Kiely, G Wohlfahrt, B Gielen, O Roupsard, P Toscano, A Arain, A Cescatti, "Global surface net-radiation at 5 km from MODIS Terra", Remote Sensing, 2016, 8, doi: 10.3390/rs8090739

CS Daley, D Ghoshal, GK Lockwood, S Dosanjh, L Ramakrishnan, NJ Wright, "Performance characterization of scientific workflows for the optimal use of Burst Buffers", CEUR Workshop Proceedings, 2016, 1800:69--73,

E Dede, B Sendir, P Kuzlu, J Weachock, M Govindaraju, L Ramakrishnan, "Processing Cassandra Datasets with Hadoop-Streaming Based Approaches", IEEE Transactions on Services Computing, 2016, 9:46--58, doi: 10.1109/tsc.2015.2444838

E Feller, L Ramakrishnan, C Morin, "Performance and energy efficiency of big data applications in cloud environments: A Hadoop case study", Journal of Parallel and Distributed Computing, 2015, 79-80:80--89, doi: 10.1016/j.jpdc.2015.01.001

V Hendrix, L Ramakrishnan, Y Ryu, C Van Ingen, KR Jackson, D Agarwal, "CAMP: Community access MODIS pipeline", Future Generation Computer Systems, 2014, 36:418--429, doi: 10.1016/j.future.2013.09.023

Lavanya Ramakrishnan, Dennis Gannon, Jeffrey Chase, Daniel Nurmi, Rich Wolski, "Deadline-Sensitive Workflow Orchestration Without Explicit Resource Control", Journal of Parallel and Distributed Computing, 2011,

Keith R. Jackson, Krishna Muriki, Lavanya Ramakrishnan, Karl J. Runge, Rollin C. Thomas, "Performance and cost analysis of the Supernova factory on the Amazon AWS cloud", Sci. Program., 2011, 19:107--119,

Lavanya Ramakrishnan, Daniel A. Reed, "Predictable Quality of Service Atop Degradable Distributed Systems", Journal of Cluster Computing, 2009,

Kelvin K. Droegemeier, Dennis Gannon, Daniel Reed, Beth Plale, Jay Alameda, Tom Baltzer, Keith Brewster, Richard Clark, Ben Domenico, Sara Graves, Everette Joseph, Donald Murray, Rahul Ramachandran, Mohan Ramamurthy, Lavanya Ramakrishnan, John A. Rushing, Daniel Weber, Robert Wilhelmson, Anne Wilson, Ming Xue, Sepideh Yalda, "Service-Oriented Environments for Dynamically Interacting with Mesoscale Weather", Computing in Science and Engg., 2005, 7:12--29, doi: http://dx.doi.org/10.1109/MCSE.2005.124

Lavanya Ramakrishnan, "Securing Next-Generation Grids", IT Professional., 2004, 6:34-39,

Dennis Gannon, Randall Bramley, Geoffrey Fox, Shava Smallen, Al Rossi, Rachana Ananthakrishnan, Felipe Bertrand, Ken Chiu, Matt Farrellee, Madhu Govindaraju, Sriram Krishnan, Lavanya Ramakrishnan, Yogesh Simmhan, Alek Slominski, Yu Ma, Caroline Olariu, Nicolas Rey-Cenvaz, "Programming the Grid: Distributed Software Components, P2P and Grid Web Services for Scientific Applications", Journal of Cluster Computing, 2002, 5:325--336,

Conference Papers

Devarshi Ghoshal, Ludovico Bianchi, Abdelilah Essiari, Drew Paine, Sarah Poon, Michael Beach, Alpha N'Diaye, Patrick Huck, Lavanya Ramakrishnan, "Science Capsule: Towards Sharing and Reproducibility of Scientific Workflows", 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), November 15, 2021, doi: 10.1109/WORKS54523.2021.00014

Workflows are increasingly processing large volumes of data from scientific instruments, experiments and sensors. These workflows often consist of complex data processing and analysis steps that might include a diverse ecosystem of tools and also often involve human-in-the-loop steps. Sharing and reproducing these workflows with collaborators and the larger community is critical but hard to do without the entire context of the workflow including user notes and execution environment. In this paper, we describe Science Capsule, which is a framework to capture, share, and reproduce scientific workflows. Science Capsule captures, manages and represents both computational and human elements of a workflow. It automatically captures and processes events associated with the execution and data life cycle of workflows, and lets users add other types and forms of scientific artifacts. Science Capsule also allows users to create `workflow snapshots' that keep track of the different versions of a workflow and their lineage, allowing scientists to incrementally share and extend workflows between users. Our results show that Science Capsule is capable of processing and organizing events in near real-time for high-throughput experimental and data analysis workflows without incurring any significant performance overheads.

Devarshi Ghoshal, Drew Paine, Gilberto Pastorello, Abdelrahman Elbashandy, Dan Gunter, Oluwamayowa Amusat, Lavanya Ramakrishnan, "Experiences with Reproducibility: Case Studies from Scientific Workflows", (P-RECS'21) Proceedings of the 4th International Workshop on Practical Reproducible Evaluation of Computer Systems, ACM, June 21, 2021, doi: 10.1145/3456287.3465478

Reproducible research is becoming essential for science to ensure transparency and for building trust. Additionally, reproducibility provides the cornerstone for sharing of methodology that can improve efficiency. Although several tools and studies focus on computational reproducibility, we need a better understanding about the gaps, issues, and challenges for enabling reproducibility of scientific results beyond the computational stages of a scientific pipeline. In this paper, we present five different case studies that highlight the reproducibility needs and challenges under various system and environmental conditions. Through the case studies, we present our experiences in reproducing different types of data and methods that exist in an experimental or analysis pipeline. We examine the human aspects of reproducibility while highlighting the things that worked, that did not work, and that could have worked better for each of the cases. Our experiences capture a wide range of scenarios and are applicable to a much broader audience who aim to integrate reproducibility in their everyday pipelines.

Drew Paine, Lavanya Ramakrishnan, "Surfacing Data Change in Scientific Work", iConference 2019, Springer Verlag, March 19, 2019, 15-26, doi: 10.1007/978-3-030-15742-5_2

Payton A Linton, William M Melodia, Alina Lazar, Deborah Agarwal, Ludovico Bianchi, Devarshi Ghoshal, Kesheng Wu, Gilberto Pastorello, Lavanya Ramakrishnan, "Identifying Time Series Similarity in Large-Scale Earth System Datasets", 2019,

GP Rodrigo, M Henderson, GH Weber, C Ophus, K Antypas, L Ramakrishnan, "ScienceSearch: Enabling Search through Automatic Metadata Generation", 2018 IEEE 14th International Conference on e-Science (e-Science), IEEE, 2018, doi: 10.1109/escience.2018.00025

Gunther H. Weber, Colin Ophus, Lavanya Ramakrishnan, "Automated Labeling of Electron Microscopy Images Using Deep Learning", Proc. IEEE/ACM Machine Learning in HPC Environments (MLHPC), 2018, 26--36, doi: 10.1109/MLHPC.2018.8638633

S Swaid, M Maat, H Krishnan, D Ghoshal, L Ramakrishnan, "Usability heuristic evaluation of scientific data analysis and visualization tools", Advances in Intelligent Systems and Computing, 2018, 607:471--482, doi: 10.1007/978-3-319-60492-3_45

D Ghoshal, L Ramakrishnan, D Agarwal, "Dac-Man: Data Change Management for Scientific Datasets on HPC Systems", SC ’18, Piscataway, NJ, USA, IEEE Press, 2018, 72:1--72:1,

GP Rodrigo, E Elmroth, P-O Ostberg, L Ramakrishnan, "ScSF: A Scheduling Simulation Framework", Job Scheduling Strategies for Parallel Processing, Cham, Springer International Publishing, 2018, 152--173,

Devarshi Ghoshal, Lavanya Ramakrishnan, "MaDaTS: Managing Data on Tiered Storage for Scientific Workflows", Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing (HPDC '17), ACM, 2017, 41--52, doi: 10.1145/3078597.3078611

W Fox, D Ghoshal, A Souza, GP Rodrigo, L Ramakrishnan, "E-HPC: A library for elastic resource management in HPC environments", Proceedings of WORKS 2017: 12th Workshop on Workflows in Support of Large-Scale Science - Held in conjunction with SC 2017: The International Conference for High Performance Computing, Networking, Storage and Analysis, 2017, doi: 10.1145/3150994.3150996

L Ramakrishnan, D Gunter, "Ten principles for creating usable software for science", Proceedings - 13th IEEE International Conference on eScience, eScience 2017, 2017, 210--218, doi: 10.1109/eScience.2017.34

GP Rodrigo, E Elmroth, P-O Östberg, L Ramakrishnan, "Enabling Workflow-Aware Scheduling on HPC Systems", Proceedings of the 26th International Symposium on High-Performance Parallel and Distributed Computing - HPDC 17, ACM Press, 2017, doi: 10.1145/3078597.3078604

V Hendrix, J Fox, D Ghoshal, L Ramakrishnan, "Tigres Workflow Library: Supporting Scientific Pipelines on HPC Systems", Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2016, 2016, 146--155, doi: 10.1109/CCGrid.2016.54

NC Chen, SS Poon, L Ramakrishnan, CR Aragon, "Considering time in designing Large-Scale systems for scientific computing", Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, 2016, 27:1535--1547, doi: 10.1145/2818048.2819988

GP Rodrigo, P-O Ostberg, E Elmroth, K Antypas, R Gerber, L Ramakrishnan, IEEE, "Towards Understanding Job Heterogeneity in HPC: A NERSC Case Study", 2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), 2016, 521--526, doi: 10.1109/CCGrid.2016.32

C Daley, L Ramakrishnan, S Dosanjh, N Wright, "Analyses of Scientific Workflows for Effective Use of Future Architectures", The 6th International Workshop on Big Data Analytics: Challenges, and Opportunities (BDAC-15), 2015 at SC, 2015,

GP Rodrigo Álvarez, P-O Östberg, E Elmroth, K Antypas, R Gerber, L Ramakrishnan, "HPC System Lifetime Story: Workload Characterization and Evolutionary Analyses on NERSC Systems", Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, 2015, 57--60,

H Sim, Y Kim, SS Vazhkudai, D Tiwari, A Anwar, AR Butt, L Ramakrishnan, ACM, "AnalyzeThis: An Analysis Workflow-Aware Storage System", PROCEEDINGS OF SC15: THE INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2015, doi: 10.1145/2807591.2807622

Elif Dede, Zacharia Fadika, Madhusudhan Govindaraju, Lavanya Ramakrishnan, "Benchmarking MapReduce Implementations Under Different Application Scenarios", Future Generation Computer Systems, 2014,

Elif Dede, Zacharia Fadika, Madhusudhan Govindaraju, Lavanya Ramakrishnan, "MARIANE: Using MApReduce In HPC Environments", Future Generation Computer Systems, 2014,

Elif Dede, Bedri Sendir, Pinar Kuzlu, Madhusudhan Govindaraju, Lavanya Ramakrishnan, "A Processing Pipeline for Cassandra Datasets Based on Hadoop Streaming", IEEE International Congress on Big Data, 2014,

Tonglin Hawk, Ioan Raicu, Lavanya Ramakrishnan, "Scalable State Management for Scientific Applications in the Cloud", IEEE International Congress on Big Data, 2014,

Lavanya Ramakrishnan, Sarah S. Poon, Val C. Hendrix, Dan K. Gunter, Gilberto Z. Pastorello, Deb A. Agarwal, "Experiences with User-Centered Design for the Tigres Workflow API", Proceedings of the 10th IEEE International Conference on e-Science (e-Science 2014), Guaruja, Brazil, 2014, doi: 10.1109/eScience.2014.56

JR Balderrama, M Simonin, L Ramakrishnan, V Hendrix, C Morin, D Agarwal, C Tedeschi, "Combining workflow templates with a shared space-based execution model", Proceedings of WORKS 2014: The 9th Workshop on Workflows in Support of Large-Scale Science - held in conjunction with SC 2014: The International Conference for High Performance Computing, Networking, Storage and Analysis, 2014, 50--58, doi: 10.1109/WORKS.2014.14

Devarshi Ghoshal, Lavanya Ramakrishnan, "FRIEDA: Flexible Robust Intelligent Elastic Data Management in Cloud Environments", 2012 SC Companion: High Performance Computing, Networking, Storage and Analysis (SCC), IEEE, 2013, 1096--1105, doi: 10.1109/SC.Companion.2012.132

Eugen Feller, Lavanya Ramakrishnan, Christine Morin, "On the Performance and Energy Efficiency of Hadoop Deployment Models", The IEEE International Conference on Big Data 2013 (IEEE BigData 2013), Santa Clara, U.S.A, 2013,

Elif Dede, Madhusudhan Govindaraju, Daniel Gunter, Richard Canon, Lavanya Ramakrishnan, "Semi-Structured Data Analysis using MongoDB and MapReduce: A Performance Evaluation", Proceedings of the 4th international workshop on Scientific cloud computing, 2013,

You-Wei Cheah, Richard Canon, Beth Plale, Lavanya Ramakrishnan, "Milieu: Provenance Collection and Query Framework for High Performance Computing Systems", IEEE Big Data Congress, 2013,

Zacharia Fadika, Madhusudhan Govindaraju, Shane Canon, Lavanya Ramakrishnan, "Evaluting Hadoop for Data-Intensive Scientific Operations", IEEE Cloud Computing, 2012,

D Gunter, S Cholia, A Jain, M Kocher, K Persson, L Ramakrishnan, SP Ong, G Ceder, "Community accessible datastore of high-throughput calculations: Experiences from the materials project", Proceedings - 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, SCC 2012, 2012, 1244--1251, doi: 10.1109/SC.Companion.2012.150

Lavanya Ramakrishnan, Richard Shane Canon, Krishna Muriki, Iwona Sakrejda, Nicholas J. Wright, "Evaluating Interconnect and Virtualization Performance for High Performance Computing", Special Issue of ACM Performance Evaluation Review, 2012, 40(2),

Elif Dede, Zacharia Fadika, Jessica Hartog, Modhusudhan Govindaraju, Lavanya Ramakrishnan, Daniel Gunter, Richard Shane Canon, "MARISSA: MApReduce Implementation for Streaming Science Applications", IEEE eScience Conference, 2012,

Devarshi Ghoshal, Richard Shane Canon, Lavanya Ramakrishnan, "I/O Performance of Virtualized Cloud Environments", Proceedings of the Second International Workshop on Data Intensive Computing in the Clouds (DataCloud-SC '11), ACM, 2011, 71--80, doi: 10.1145/2087522.2087535

Elif Dede, Madhusudan Govindaraju, Daniel Gunter, Lavanya Ramakrishnan, "Riding the Elephant: Managing Ensembles with Hadoop", 4th Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS), 2011,

Zacharia Fadika, Elif Dede, Madhusudhan Govindaraju, Lavanya Ramakrishnan, "Benchmarking MapReduce Implementations for Application Usage Scenarios", Grid 2011: 12th IEEE/ACM International Conference on Grid Computing, Lyon Conference Centre, France, IEEE Computer Society, 2011, 1-8, doi: http://grid2011.mnm-team.org/?page_id138

Zacharia Fadika, Elif Dede, Madhusudhan Govindaraju, Lavanya Ramakrishnan, "MARIANE: MApReduce Implementation Adapted for HPC Environments", Grid 2011: 12th IEEE/ACM International Conference on Grid Computing, Lyon Conference Centre, France, IEEE Computer Society, 2011, 1-8, doi: http://grid2011.mnm-team.org/?page_id138

You-Wei Cheah, Beth Plale, Joey Kendall-Morwick, David Leake, Lavanya Ramakrishnan, "A Noisy 10GB Provenance Database", Second International Workshop on Traceability and Compliance of Semi-Structured Processes (TC4SP2011), 2011,

Lavanya Ramakrishnan, Piotr T. Zbiegel, Scott Campbell, Rick Bradshaw, Richard Shane Canon, Susan Coghlan, Iwona Sakrejda, Narayan Desai, Tina Declerck, Anping Liu, "Magellan: Experiences from a Science Cloud", ScienceCloud 11, New York, NY, USA, ACM, 2011, 49--58, doi: http://doi.acm.org/10.1145/1996109.1996119

Keith Jackson, Lavanya Ramakrishnan, Rollin Thomas, Karl J. Runge, "Seeking Supernovae in the Clouds: A Performance Study", 1st Workshop on Scientific Cloud Computing, co-located with ACM HPDC 2010 (High Performance Distributed Computing), Chicago, IL, 2010,

Lavanya Ramakrishnan, Keith Jackson, Shane Canon, Shreyas Cholia, John Shalf, "Defining Future Platform Requirements for e-Science Cloud (Position paper)", ACM Symposium on Cloud Computing 2010 (ACM SOCC 2010), Indianapolis, Indiana, 2010,

Lavanya Ramakrishnan, Dennis Gannon, Beth Plale, "WORKEM: Representing and Emulating Distributed Scientific Workflow Execution State", 10th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2010), Melbourne Australia, 2010,

Y Simmhan, E Soroush, C Van Ingen, D Agarwal, L Ramakrishnan, "BReW: Blackbox resource selection for e-Science workflows", 2010 5th Workshop on Workflows in Support of Large-Scale Science, WORKS 2010, 2010, doi: 10.1109/WORKS.2010.5671857

Lavanya Ramakrishnan, Beth Plale, "A Multi-Dimensional Classification Model for Scientific Workflow Characteristics", Workshop on Workflow Approaches to New Data-centric Science, Indianapolis, Indiana, 2010,

Yogesh Simmhan, Lavanya Ramakrishnan, "Comparison of Resource Platform Selection Approaches for Scientific Workflows", 1st Workshop on Scientific Cloud Computing, co-located with ACM HPDC 2010 (High Performance Distributed Computing), Chicago, Illinois, 2010,

KR Jackson, L Ramakrishnan, K Muriki, S Canon, S Cholia, J Shalf, HJ Wasserman, NJ Wright, "Performance analysis of high performance computing applications on the Amazon Web Services cloud", Proceedings - 2nd IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2010, 2010, 159--168, doi: 10.1109/CloudCom.2010.69

L Ramakrishnan, C Guok, K Jackson, E Kissel, DM Swany, D Agarwal, "On-demand overlay networks for large scientific data transfers", CCGrid 2010 - 10th IEEE/ACM International Conference on Cluster, Cloud, and Grid Computing, 2010, 359--367, doi: 10.1109/CCGRID.2010.82

Lavanya Ramakrishnan, Daniel Nurmi, Anirban Mandal, Charles Koelbel, Dennis Gannon, T. Mark Huang, Yang-Suk Kee, Graziano Oberteli, Kiran Thyagaraja, Rich Wolski, Asim Yarkhan, Dmitrii Zagorodnov, "VGrADS: Enabling e-Science Workflows on Grids and Clouds with Fault Tolerance", Proceedings of the ACM/IEEE SC2009 Conference on High Performance Computing, Networking, Storage and Analysis, Portland, Oregon, Portland, Oregon, 2009,

Lavanya Ramakrishnan, Daniel A. Reed, "Performability Modeling for Scheduling and Fault Tolerance Strategies for Scientific Workflows", ACM/IEEE International Symposium on High Performance Distributed Computing, Boston Massachusetts, 2008,

Lavanya Ramakrishnan, Yogesh Simmhan, Beth Plale, "Realization of Dynamically Adaptive Weather Analysis and Forecasting in LEAD", In Dynamic Data Driven Applications Systems Workshop (DDDAS) in conjunction with ICCS (Invited), Beijing, China, 2007,

Lavanya Ramakrishnan, Laura Grit, Adriana Iamnitchi, David Irwin, Aydan Yumerefendi, Jeff Chase, "Toward a Doctrine of Containment: Grid Hosting with Adaptive Resource Control", Proceedings of the ACM/IEEE SC2006 Conference on High Performance Computing, Networking, Storage and Analysis, Tampa, Florida, Tampa, Florida, 2006,

Lavanya Ramakrishnan, Mark S.C Reed, Jeffrey L. Tilson, Daniel A. Reed, "Grid Portals for Bioinformatics", Second International Workshop on Grid Computing Environments (GCE), Held in conjunction with ACM/IEEE Conference for High Performance Computing, Networking, Storage and Analysis, Tampa, Florida, 2006,

Lavanya Ramakrishnan, Brian O. Blanton, Howard M. Lander, Richard A. Luettich, Jr, Daniel A. Reed, Steven R. Thorpe, "Real-time Storm Surge Ensemble Modeling in a Grid Environment", Second International Workshop on Grid Computing Environments (GCE), Held in conjunction ACM/IEEE Conference for High Performance Computing, Networking, Storage and Analysis, Tampa, Florida, 2006,

Timothy J. Smith, Lavanya Ramakrishnan, "Joint Policy Management and Auditing in Virtual Organizations.", Grid Computing, Phoenix, Arizona, 2003, 117-124,

Lavanya Ramakrishnan, Helen Nell Rehn, Jay, Rachana Ananthakrishnan, Madhusudhan, Aleksander Slominski, Kay Connelly Von Welch, Dennis Gannon, Randall Bramley, Hampton, "An Authorization Framework for a Grid Based Common Architecture", Proceedings of the 3rd International Workshop on Grid Baltimore, Maryland, Springer Press, 2002, 169--180,

Book Chapters

L Ramakrishnan, D Ghoshal, V Hendrix, E Feller, P Mantha, C Morin, "Storage and Data Life Cycle Management in Cloud Environments with FRIEDA.", Cloud Computing for Data-Intensive Applications, (Springer: 2014) Pages: 357--378

Lavanya Ramakrishnan, Adam Scovel, Iwona Sakrejda, Susan Coghlan, Shane Canon, Anping Liu, Devarshi Ghoshal, Krishna Muriki, Nicholas J. Wright, "Magellan - A Testbed to Explore Cloud Computing for Science", On the Road to Exascale Computing: Contemporary Architectures in High Performance Computing, (Chapman & Hall/CRC Press: 2013)

Lavanya Ramakrishnan, Iwona Sakrejda, Richard Shane Canon and Nicholas Wright, "CAMP", On the Road to Exascale Computing: Contemporary Architectures in High Performance Computing, (Chapman & Hall/CRC Press: 2013)

Robert J. Fowler, Todd Gamblin, Gopi Kandaswamy, Anirban Mandal, Allan K. Porterfield, Lavanya Ramakrishnan, Daniel A. Reed, "Challenges of Scale: When All Computing Becomes Grid Computing", High Performance Computing and Grids in Action, (IOS Press: 2008)

Dennis Gannon, Rachana Ananthakrishnan, Sriram, Madhusudhan Govindaraju, Lavanya, Aleksander Slominski, "Grid Web Services and Application Factories", Grid Computing: Making the Global Infrastructure a Reality, (Wiley: 2003)

Presentation/Talks

Cheah You-Wei, Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, Bringing Data Science to Qualitative Analysis, 2018 IEEE 14th International Conference on e-Science, Pages: 325-326 2018, doi: 10.1109/eScience.2018.00076

Reports

Drew Paine, Sarah Poon, Lavanya Ramakrishnan, "Investigating User Experiences with Data Abstractions on High Performance Computing Systems", June 29, 2021, LBNL LBNL-2001374,

Scientific exploration generates expanding volumes of data that commonly require High Performance Computing (HPC) systems to facilitate research. HPC systems are complex ecosystems of hardware and software that frequently are not user friendly. The Usable Data Abstractions (UDA) project set out to build usable software for scientific workflows in HPC environments by undertaking multiple rounds of qualitative user research. Qualitative research investigates how individuals accomplish their work and our interview-based study surfaced a variety of insights about the experiences of working in and with HPC ecosystems. This report examines multiple facets to the experiences of scientists and developers using and supporting HPC systems. We discuss how stakeholders grasp the design and configuration of these systems, the impacts of abstraction layers on their ability to successfully do work, and the varied perceptions of time that shape this work. Examining the adoption of the Cori HPC at NERSC we explore the anticipations and lived experiences of users interacting with this system's novel storage feature, the Burst Buffer. We present lessons learned from across these insights to illustrate just some of the challenges HPC facilities and their stakeholders need to account for when procuring and supporting these essential scientific resources to ensure their usability and utility to a variety of scientific practices.

Drew Paine, Lavanya Ramakrishnan, "Understanding Interactive and Reproducible Computing With Jupyter Tools at Facilities", LBNL Technical Report, October 31, 2020, LBNL LBNL-2001355,

Increasingly Jupyter tools are being adopted and incorporated into High Performance Computing (HPC) and scientific user facilities. Adopting Jupyter tools enables more interactive and reproducible computational work at facilities across data life cycles. As the volume, variety, and scope of data grow, scientists need to be able to analyze and share results in user friendly ways. Human-centered research highlights design challenges around computational notebooks, and our qualitative user study shifts focus to better characterize how Jupyter tools are being used in HPC and science user facilities today. We conducted twenty-nine interviews, and obtained 103 survey responses from NERSC Jupyter users, to better understand the increasing role of interactive computing tools in DOE sponsored scientific work. We examine a range of issues that emerge using and supporting Jupyter in HPC ecosystems, including: how Jupyter is being used by scientists in HPC and user facility ecosystems; how facilities are purposefully supporting Jupyter in their ecosystems; feedback NERSC users have about the facility’s deployment, and, discuss features NERSC indicated would be helpful. We offer a variety of takeaways for staff supporting Jupyter at facilities, Project Jupyter and related open source communities, and funding agencies supporting interactive computing work.

Drew Paine, Devarshi Ghoshal, Lavanya Ramakrishnan, "Investigating Scientific Data Change with User Research Methods", August 20, 2020, LBNL LBNL-2001347,

Scientific datasets are continually expanding and changing due to fluctuations with instruments, quality assessment and quality control processes, and modifications to software pipelines. Datasets include minimal information about these changes or their effects requiring scientists manually assess modifications through a number of labor intensive and ad-hoc steps. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists systematically identify and make decisions around data changes. Currently, there is a lack of understanding, and common practices, for identifying and evaluating changes in datasets since systematically measuring and managing data change is under explored in scientific work. We are conducting user research to address this need by exploring scientist's conceptualizations, behaviors, needs, and motivations when dealing with changing datasets. Our user research utilizes multiple methods to produce foundational, generative insights and evaluate research products produced by our team. In this paper, we detail our user research process and outline our findings about data change that emerge from our studies. Our work illustrates how scientific software teams can push beyond just usability testing user interfaces or tools to better probe the underlying ideas they are developing solutions to address.

E. Masanet, A. Shehabi, L. Ramakrishnan, J. Liang, X. Ma, B. Walker, V. Hendrix, P Mantha, "The Energy Efficiency Potential of Cloud-Based Software: A U.S.Case Study", 2013, LBNL 6298E,

Posters

P. Linton, W. Melodia, A. Lazar, D. Agarwal, L. Bianchi, D. Ghoshal, K. Wu, G. Pastorello, L. Ramakrishnan, "Identifying Time Series Similarity in Large-Scale Earth System Datasets", The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), 2019,

V Hendrix, J Li, K Jackson, L Ramakrishnan, Y Ryu, K Beattie, C Morin, D Skinner, C van Ingen, D Agarwal, "Community Access to MODIS Satellite Reprojection and Reduction Pipeline and Data Sets", AGU Fall Meeting, 2012,

Others

MB Simmonds, WJ Riley, DA Agarwal, X Chen, S Cholia, R Crystal-Ornelas, ET Coon, D Dwivedi, VC Hendrix, M Huang, A Jan, Z Kakalia, J Kumar, CD Koven, L Li, M Melara, L Ramakrishnan, DM Ricciuto, AP Walker, W Zhi, Q Zhu, C Varadharajan, Guidelines for Publicly Archiving Terrestrial Model Data to Enhance Usability, Intercomparison, and Synthesis, Data Science Journal, 2022, doi: 10.5334/dsj-2022-003

J Müller, B Faybishenko, D Agarwal, S Bailey, C Jiang, Y Ryu, C Tull, L Ramakrishnan, Assessing data change in scientific datasets, Concurrency and Computation: Practice and Experience, 2021, doi: 10.1002/cpe.6245

Payton Linton, William Melodia, Alina Lazar, Deborah Agarwal, Ludovico Bianchi, Devarshi Ghoshal, Gilberto Pastorello, Lavanya Ramakrishnan, Kesheng Wu, Understanding Data Similarity in Large-Scale Scientific Datasets, 2019 IEEE International Conference on Big Data (Big Data), Pages: 4525--4531 2019,

GP Rodrigo Álvarez, P-O Östberg, E Elmroth, L Ramakrishnan, A2L2, Proceedings of the 8th International Workshop on Virtualization Technologies in Distributed Computing - VTDC 15, 2015, doi: 10.1145/2755979.2755983