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We explore the interplay between architectures and algorithm design in the context of shared-memory platforms and a specific graph problem of central importance in scientific and high-performance computing, distance-1 graph coloring.
This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters.
The solver is parallelized for distributed memory platforms using domain decomposition and message passing interface (MPI) and salient features of the parallel algorithm are presented.
SAVR is portable across platforms and has been parallelized to run on both shared and distributed memory platforms.
Therefore, this paper proposes the development of a new sequential resampling algorithm that can be used for various memory platforms with the use of integrated sampling of traditional variant resampling and traditional resampling.
In this work, we showed good results when mapping our BSP/CGM algorithms to shared memory platforms.
The lightweight parallel execution layer (LPEL) [24] is an execution layer that supports stream programs on shared memory platforms.
It is well known that this model is suitable for designing parallel algorithms for distributed memory platforms.
Significant research has been conducted in collective communication operations, in particular in MPI broadcast, on distributed memory platforms.
Fig. 5 Simulation of RMSE with typical requirement memory platform; the AMSSDR and rounding copy resampling have a common type of RMSE Fig. 6 Simulation of RMSE with low requirement memory platform; The AMSSDR and systematic resampling have same common of RMSE.
Fig. 7 Simulation with typical requirement memory platform; the AMSSDR and rounding copy resampling have a common type of sample size Fig. 8 Simulation with low requirement memory platform; the AMSSDR and systematic resampling have a common type of sample size.
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