Evaluation of the OGF GridRPC Data Management library, and study of its integration into an International Sparse Linear Algebra Expert System

Abstract

The Data Management API for the GridRPC describes an optional API that extends the GridRPC standard. It provides a minimal subset of functions to handle a large set of data operations, among which movement, replication, migration and stickyness. We already showed that its use leads to 1) reduced time to completion of application, since useless transfers are avoided; 2) improved feasibility of some computations, depending on the availability of services and/or storage space constraints; 3) complete code portability between two GridRPC middleware; and 4) seamless interoperability, in our example between the French GridRPC middleware DIET and the Japanese middleware Ninf, distributed on French and Japanese administrative domains respectively, leading to both of them contributing to the same calculus, their respective servers sharing only data through our implementation of the GridRPC DM API. We have extended the implementation of the library and a further integration has been made available into DIET as a back-end of its data manager Dagda. We thus present how the library is used in the International Sparse Linear Algebra Expert System GridTLSE which manages entire expertises for the user, including data transfers, tasks executions, and graphical charts, to help analysing the overall execution. GridTLSE relies on DIET to distribute computations and thus can benefit from the persistency functionalities to provide scientists with faster results when their expertises require the same input matrices. In addition, with the possibility for two middleware to interact in a seamless way as long as they’re using an implementation of the GridRPC Data Management API, new architecture of different domains can easily be integrated to the expert system and thus helps the linear algebra community.