K. Keahey and D. Gannon, Developing and Evaluating Abstractions for Distributed Supercomputing, Journal of Cluster Computing, special issue on High Performance Distributed Computing, Vol. 1, No. 1, May 1998. Home/Search Document Details and Download
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Code Coupling using Parallel CORBA Objects - René, Priol (Correct)
....between codes running on different machines, communication paradigms such as RPC or distributed objects, offer a much more attractive solution since the transfer of control is implemented by remote invocation that is as simple as calling a function or a method. We advocate an approach, like others [4], that consists in merging several communication paradigms in a coherentway. This approach is based on the use of two communication paradigms: distributed objects (CORBA) and message passing (MPI) 1 The one acting as a bridge for the communication between differentmachines 2 Usually through a ....
K. Keahey and D. Gannon. Developing and Evaluating Abstractions for Distributed Supercomputing. Cluster Computing, 1(1):69--79, May 1998.
Algorithms and Tools for (Distributed) Heterogeneous.. - Mehaut, Robert (1999) (Correct)
....the communications that will take place during the execution. On the computational grid, many programming paradigms are yet to be found In software engineering, object oriented language and methodologies have received a lot of attention. Standards such as Java and Corba are very promising. See [53] for a metacomputing approach based on Corba. In a near future, e cient implementations of Java may well represent a viable alternative to Fortran for scienti c computations (see http: www.javagrande.org) In the framework of metacomputing, with strongly heterogeneous environments, ....
K. Keahey nd D. Gannon. Developing and evaluating abstractions for distributed supercomputing. Cluster Computing, 1:69-79, 1998.
Programming the Grid: Distributed Software.. - Gannon, Bramley.. (2002) (7 citations) Self-citation (Gannon) (Correct)
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K. Keahey and D. Gannon, Developing and Evaluating Abstractions for Distributed Supercomputing, Journal of Cluster Computing, special issue on High Performance Distributed Computing, Vol. 1, No. 1, May 1998.
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