Chandrika Sivaramakrishnan

Publications (8)0 Total impact

• Conference Proceeding: Scientist-Centered Workflow Abstractions via Generic Actors, Workflow Templates, and Context-Awareness for Groundwater Modeling and Analysis.

  George Chin Jr, Chandrika Sivaramakrishnan, Terence Critchlow, Karen Schuchardt, Anne H. H. Ngu
  01/2011
• Article: Kepler Scientific Workflow Design and Execution with Contexts.

  Anne Hee Hiong Ngu, Arwa M. Jamnagarwala, George Chin Jr, Chandrika Sivaramakrishnan, Terence Critchlow
  I. J. Comput. Appl. 01/2011; 18:133-147.
• Source

  Available from: cs.utep.edu

  Conference Proceeding: Knowledge Annotations in Scientific Workflows: An Implementation in Kepler.

  Aída Gándara, George Chin Jr, Paulo Pinheiro da Silva, Signe White, Chandrika Sivaramakrishnan, Terence Critchlow
  Scientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Portland, OR, USA, July 20-22, 2011. Proceedings; 01/2011
• Conference Proceeding: GS3: A Knowledge Management Architecture for Collaborative Geologic Sequestration Modeling.

  Ian Gorton, Gary D. Black, Karen Schuchardt, Chandrika Sivaramakrishnan, Signe K. Wurstner, Peter Hui
  43rd Hawaii International International Conference on Systems Science (HICSS-43 2010), Proceedings, 5-8 January 2010, Koloa, Kauai, HI, USA; 01/2010
• Conference Proceeding: Kepler + MeDICi.

  Jared Chase, Ian Gorton, Chandrika Sivaramakrishnan, Justin Almquist, Adam Wynne, George Chin Jr, Terence Critchlow
  01/2009
• Article: An Extensible, Scalable Architecture for Managing Bioinformatics Data and Analyses

  Anuj R. Shah, Mudita Singhal, Tara D. Gibson, Chandrika Sivaramakrishnan, Katrina M. Waters, Ian Gorton
  [show abstract] [hide abstract]
  ABSTRACT: Systems biology research demands the availability of tools and technologies that span a comprehensive range of computational capabilities, including data management, transfer, processing, integration, and interpretation. To address these needs, we have created the Bioinformatics Resource Manager (BRM), a scalable, flexible, and easy to use tool for biologists to undertake complex analyses. This paper describes the underlying software architecture of the BRM that integrates multiple commodity platforms to provide a highly extensible and scalable software infrastructure for bioinformatics. The architecture integrates a J2EE 3-tier application with an archival Experimental Data Management System, the GAGGLE framework for desktop tool integration, and the MeDICi Integration Framework for high-throughput data analysis workflows. This architecture facilitates a systems biology software solution that enables the entire spectrum of scientific activities, from experimental data access to high throughput processing and analysis of data for biologists and experimental scientists.
  eScience, IEEE International Conference on. 12/2008;
• Conference Proceeding: An Extensible, Scalable Architecture for Managing Bioinformatics Data and Analyses.

  Anuj R. Shah, Mudita Singhal, Tara D. Gibson, Chandrika Sivaramakrishnan, Katrina M. Waters, Ian Gorton
  Fourth International Conference on e-Science, e-Science 2008, 7-12 December 2008, Indianapolis, IN, USA; 01/2008
• Source

  Available from: Timothy D Scheibe

  Article: Task parallel sensitivity analysis and parameter estimation of groundwater simulations through the SALSSA framework

  Karen Schuchardt, Khushbu Agarwal, Jared Chase, Mark Rockhold, Vicky Freedman, Todd Elsethagen, Tim Scheibe, George Chin, Chandrika Sivaramakrishnan
  [show abstract] [hide abstract]
  ABSTRACT: The Support Architecture for Large-Scale Subsurface Analysis (SALSSA) provides an extensible framework, sophisticated graphical user interface, and underlying data management system that simplifies the process of running subsurface models, tracking provenance information, and analyzing the model results. Initially, SALSSA supported two styles of job control: user directed execution and monitoring of individual jobs, and load balancing of jobs across multiple machines taking advantage of many available workstations. Recent efforts in subsurface modelling have been directed at scaling simulators to take advantage of leadership class supercomputers. We describe two approaches, current progress, and plans toward enabling efficient application of the subsurface simulator codes via the SALSSA framework: automating sensitivity analysis problems through task parallelism, and task parallel parameter estimation using the PEST framework.