Computing in Accelerator Design and Oprn. by W. Busse, et. al.,

By W. Busse, et. al.,

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Sample text

Consequently, an experiment is represented by a data flow graph (DFG). This DFG usually contains experiment specific software entities as well as generic software entities. We will call these self-contained software entities as modules. 3. Resource management in VL-E One of the focuses of our research is the development of a resource management system for the VL-E environment. In this context, applications are presented by a set of connected by data flow independent modules that perform calculations and data processing, access data storage or control remote devices.

At Abstract This paper presents a performance comparison between important programming paradigms for distributed computing: the classical Message Passing model and the Virtual Shared Memory model. As benchmarks, three algorithms have been implemented using MPI, UPC and CORSO: (i) a classical summation formula for approximating (ii) a tree-structured sequence of matrix multiplications, and (iii) the basic structure of the eigenvector computation in a recently developed eigensolver. In many cases, especially for inhomogeneous or dynamically changing computational grids, the Virtual Shared Memory implementations lead to performance comparable to MPI implementations.

The functionality related part of the decision is done based on the data formats which have been defined for the modules input and output interfaces. At first the output format of a module has to match the input format of the subsequent one. Additionally the input format of the first module and the output format of the last have to be selected according to the specification in the visualization request. After a set of software modules has been identified for each stage of the visualization pipeline, which satisfies the functionality related constraints, the visualization planning process enters the next stage.

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