Höchstleistungsrechenzentrum Stuttgart SEGL Parameter Study Slide 1 Science Experimental Grid Laboratory (SEGL) Dynamical Parameter Study in Distributed Systems Natalia Currle-Linde University of Stuttgart High-Performance Computing-Center Stuttgart (HLRS)

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 2 Overview Background & Motivation Related Work Architecture & implementation details of SEGL Usage Example Future Work

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 3 Background &Motivation Parameter studies - a great challenge Parameter studies easy to parallelize Grid Technology enables integration of resources provides a new technical basis for complex parametric investigations Problem: Administration of jobs, parameters, results …. Motivation Motivation : automatically start, execute, monitor applications efficient enable efficient execution of experiments User doesn`t need to have knowledge of specific programming language knowledge of Grid structure.

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 4 Tools for parameter investigation studies NIMROD (Monash University, Australia) Can be used to manage the execution of parameter studies across distributed computers ILAB ( NASA Ames Research Center ) Allows the generation of multi-parametric models and adds workflow management do not support dynamic parameterizations

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 5 Workflow Support: multiphysics applications, preprocessing steps, postprocessing filters,visualization, iterative search in the parameter space for optimum solutions Require: use of Grid Workflow TRIANA UNICORE BPEL4WS specification of loops criteria synchronisation points communication via message

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 6 Dynamic parameterization SEGL enables dynamical selection of parameter sets on the basis of previous and intermediate results SEGL supports creation of complex processes, which involves –several levels of parameterization –repeated processing –data archiving –conclusions and branches during the processing –synchronization of parallel branches and processes

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 7 Requirement – Hide complexity from the user Users are very sensitive to the level of automation of application preparation They must be able to define a fine - grained logical execution process formulate the parameterization rules identify the position in the input area of the parameters which are to be changed in the course of the experiment All other details should be hidden from the user.

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 8 Science Experimental Grid Laboratory System Architecture

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 9 System Architecture J2EE JBOSS Appication Server JDO (OODB) UNICORE -Adapter

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 10 Graphic language three levels Experiment is described at three levels : control flow, data flow, data repository Control flow Control flow : description of logical schema of experiments direction, condition, sequence of execution Data flow Data flow : local description of interblock computation processes standard/user-specific computation module direction of input/output data between repositoryand computation module parameterization rules Data repository Data repository : aggregation of data container application ->application server QL description ->server data base

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 11

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 12 Control Flow User defines the sequence of execution of experiment blocks Solver block simple parameter sweep Control block program object: allows changing sequence of execution according to specified criteria

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 13 Data Flow is dynamic Manipulation of data in a very fine- grained way Solver Block: computation module C replacemant module R parameterization module P data base Each module: Java object has standard structure consists of several sections Computation module : organizes preparation of input data generates job initializes/controls record of results in DB controls execution of module operation

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 14 Data Flow (variants of parameterization)

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 15 Control Flow

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 16 Power plant simulation Unit: Output Power170 MWel Firing SystemTangential, Windbox Bituminous Coal OFA retrofit for NOx-reduction in 1991 Optimized Operation Parameters required Target : Minimizing NOx and Unburned Carbon Parameters : Damper Setting CCOFA Damper Setting sep. OFA Tilting Angle sep. OFA

Höchstleistungsrechenzentrum Stuttgart Natalia Currle-LindeSEGL Parameter Study Slide 17 Conclusion & Future Work SEGL allows end-user programming of complex, computation- intensive simulation and modeling for science and engineering offers efficient way to execute scientific experiments Future work: –Globus Adapter –Investigation of Unicore Resource Broker