68P05 Data structures
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In high accuracy numerical simulations and optimal control of time-dependent processes, often both many time steps and fine spatial discretizations are needed. Adjoint gradient computation, or post-processing of simulation results, requires the storage of the solution trajectories over the whole time, if necessary together with the adaptively refined spatial grids. In this paper we discuss various techniques to reduce the memory requirements, focusing first on the storage of the solution data, which typically are double precision floating point values. We highlight advantages and disadvantages of the different approaches. Moreover, we present an algorithm for the efficient storage of adaptively refined, hierarchic grids, and the integration with the compressed storage of solution data.
Molecular dynamics simulations of possible ligands for proteins yield large amounts of data in the form of trajectories which are further processed in order to find metastable conformations. These conformations can then be used for docking between ligand and protein. Around this core computation procedure lots of other data have to be managed. It should also be possible for external users not involved in program development to perform computations. As a paradigm for other fields where a similar constitution of program usage and data processing is found we present a software architecture for data generation, access and management. Requirements for this system include: Ease of use, graphical user interface, persistent storage of data concerning molecules, users, programs, program parameters, metadata, and results. A mere storage in the file system would render a quick overview of data more or less impossible. On the other hand, storing large amounts of binary data in a database doesn't yield any advantage concerning speed of access. Therefore, a hybrid approach combining file system and database is appropriate. The system should be easily extensible by inserting new applications which can be controlled and whose results can be collected and stored. The software system described here consists of different components, the presentation layer (graphical user interface), the business logic, the persistence layer (relational database plus file system), and an interface to the compute cluster (batch system for parallel processing). We will discuss the alternatives and take a closer look at the components.