OpenMolGRID, a GRID Based System for Solving Large-Scale Drug Design Problems

Author(s):  
Ferenc Darvas ◽  
Ákos Papp ◽  
István Bágyi ◽  
Géza Ambrus ◽  
László Ürge
2021 ◽  
Vol 1 ◽  
pp. 3229-3238
Author(s):  
Torben Beernaert ◽  
Pascal Etman ◽  
Maarten De Bock ◽  
Ivo Classen ◽  
Marco De Baar

AbstractThe design of ITER, a large-scale nuclear fusion reactor, is intertwined with profound research and development efforts. Tough problems call for novel solutions, but the low maturity of those solutions can lead to unexpected problems. If designers keep solving such emergent problems in iterative design cycles, the complexity of the resulting design is bound to increase. Instead, we want to show designers the sources of emergent design problems, so they may be dealt with more effectively. We propose to model the interplay between multiple problems and solutions in a problem network. Each problem and solution is then connected to a dynamically changing engineering model, a graph of physical components. By analysing the problem network and the engineering model, we can (1) derive which problem has emerged from which solution and (2) compute the contribution of each design effort to the complexity of the evolving engineering model. The method is demonstrated for a sequence of problems and solutions that characterized the early design stage of an optical subsystem of ITER.


2012 ◽  
Vol 433-440 ◽  
pp. 4297-4301
Author(s):  
Hui Ru Wang ◽  
Jing Ding

For large-scale distributed interactive simulation, it is important and difficult for data to communicate among thousands of objects. The purpose of the Data Distribution Management (DDM) service performs data filter and reduces irrelevant data between federations. Grid-based algorithm can only manage to filter part of irrelevant data. Experimental results show that, compare with normal grid-based algorithms, the dynamic multicast method can minimize.


2012 ◽  
pp. 1349-1375
Author(s):  
Dang Minh Quan ◽  
Jörn Altmann ◽  
Laurence T. Yang

This chapter describes the error recovery mechanisms in the system handling the Grid-based workflow within the Service Level Agreement (SLA) context. It classifies the errors into two main categories. The first is the large-scale errors when one or several Grid sites are detached from the Grid system at a time. The second is the small-scale errors which may happen inside an RMS. For each type of error, the chapter introduces a recovery mechanism with the SLA context imposing the goal to the mechanisms. The authors believe that it is very useful to have an error recovery framework to avoid or eliminate the negative effects of the errors.


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