Computations based on graphs are very common problems but complexity, increasing size of analyzed graphs and a huge amount of communication make this analysis a challenging task. In this paper, we present a comparison...
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ISBN:
(纸本)9783319780542;9783319780535
Computations based on graphs are very common problems but complexity, increasing size of analyzed graphs and a huge amount of communication make this analysis a challenging task. In this paper, we present a comparison of two parallel BFS (Breath- First Search) implementations: MapReduce run on Hadoop infrastructure and in pgas (partitionedglobaladdressspace) model. the latter implementation has been developed withthe help of the PCJ (Parallel Computations in Java) - a library for parallel and distributed computations in Java. Both implementations realize the level synchronous strategy - Hadoop algorithm assumes iterative MapReduce jobs, whereas PCJ uses explicit synchronization after each level. the scalability of both solutions is similar. However, the PCJ implementation is much faster (about 100 times) than the MapReduce Hadoop solution.
Recently, the partitionedglobaladdressspace (pgas) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a pgas parallel programming language that extends base...
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ISBN:
(纸本)9781479976164
Recently, the partitionedglobaladdressspace (pgas) parallel programming model has emerged as a usable distributed memory programming model. XcalableMP (XMP) is a pgas parallel programming language that extends base languages such as C and Fortran with directives in OpenMP-like style. XMP supports a global-view model that allows programmers to define global data and to map them to a set of processors, which execute the distributed global data as a single thread. In XMP, the concept of a coarray is also employed for local-view programming. In this study, we port Gyrokinetic Toroidal Code - Princeton (GTC-P), which is a three-dimensional PIC code developed at Princeton University to study the microturbulence phenomenon in magnetically confined fusion plasmas, to XMP as an example of hybrid memory model coding withthe global-view and local-view programmingmodels. In local-view programming, the coarray notation is simple and intuitive compared with Message Passing Interface (MPI) programming while the performance is comparable to that of the MPI version. thus, because the global-view programming model is suitable for expressing the data parallelism for a field of grid space data, we implement a hybrid-view version using a global-view programming model to compute the field and a local-view programming model to compute the movement of particles. the performance is degraded by 5-25% compared withthe original MPI version, but the hybrid-view version facilitates more natural data expression for static grid space data (in global-view model) and dynamic particle data (in local-view model), and it also increases the readability of the code for higher productivity.
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