The goal of the Pandore system is to allow the execution of parallel algorithms on DMPC (Distributed Memory Parallel Computers) without having to take into account the low-level characteristics of the target distributed computer to program the algorithm. No explicit process definition and interprocess communications are needed. Parallelization is achieved through logical data organization. The Pandore system provides the user with a mean to specify data partitionning and data distribution over a domain of virtual processors for each parallel step of his algorithm. At compile time, Pandore splits the original program into parallel processes which will execute the same code over the different parts of the data, according to the given decompos...
PDDP, the Parallel Data Distribution Preprocessor, is a data parallel programming model for distribu...
p4 is a portable library of C and Fortran subroutines for programming parallel computers. It is the ...
PDDP, the parallel data distribution preprocessor, is a data parallel programming model for distribu...
The goal of the Pandore system is to allow the execution of parallel algorithms on DMPC (Distributed...
Parallelization of programs for distributed memory parallel computers is always difficult because of...
International audienceThis paper presents an environment for programming distributed memory computer...
This paper presents an environment for programming distributed memory computers using HPF-like data ...
International audienceIn this paper, we present the overall design of Pandore II, an Environment ded...
International audienceThe paper presents the parallelization process of a wave propagation applicati...
We present algorithms for the transportation of data in parallel and distributed systems that would ...
In order to achieve viable parallel processing three basic criteria must be met: (1) the system must...
International audienceIn this paper, the problem of evaluating the performance of parallel programs ...
Distributed-memory multiprocessing systems (DMS), such as Intel’s hypercubes, the Paragon, Thinking ...
Contemporary state-of-the-art runtime systems underlying widely utilized general purpose parallel pr...
PDDP, the Parallel Data Distribution Preprocessor, is a data parallel programming model for distribu...
p4 is a portable library of C and Fortran subroutines for programming parallel computers. It is the ...
PDDP, the parallel data distribution preprocessor, is a data parallel programming model for distribu...
The goal of the Pandore system is to allow the execution of parallel algorithms on DMPC (Distributed...
Parallelization of programs for distributed memory parallel computers is always difficult because of...
International audienceThis paper presents an environment for programming distributed memory computer...
This paper presents an environment for programming distributed memory computers using HPF-like data ...
International audienceIn this paper, we present the overall design of Pandore II, an Environment ded...
International audienceThe paper presents the parallelization process of a wave propagation applicati...
We present algorithms for the transportation of data in parallel and distributed systems that would ...
In order to achieve viable parallel processing three basic criteria must be met: (1) the system must...
International audienceIn this paper, the problem of evaluating the performance of parallel programs ...
Distributed-memory multiprocessing systems (DMS), such as Intel’s hypercubes, the Paragon, Thinking ...
Contemporary state-of-the-art runtime systems underlying widely utilized general purpose parallel pr...
PDDP, the Parallel Data Distribution Preprocessor, is a data parallel programming model for distribu...
p4 is a portable library of C and Fortran subroutines for programming parallel computers. It is the ...
PDDP, the parallel data distribution preprocessor, is a data parallel programming model for distribu...