Towards Efficient Decomposition and Parallelization of MPDATA on Hybrid CPU-GPU Cluster

Wyrzykowski, Roman; Szustak, Łukasz; Rojek, Krzysztof; Tomas, Adam

doi:10.1007/978-3-662-43880-0_52

Cited by 15 publications

(15 citation statements)

References 10 publications

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“…In previous works [26,35], we proved that MPDATA belongs to the group of memory-bound algorithms [13,36]. This makes MPDATA a challenging candidate for a technology such as dynamic VFS [16], which can reduce CPU energy consumption without a significant loss of performance.…”

Section: Overviewmentioning

confidence: 94%

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Modeling power consumption of 3D MPDATA and the CG method on ARM and Intel multicore architectures

2017

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We propose an approach to estimate the power consumption of algorithms, as a function of the frequency and number of cores, using only a very reduced set of real power measures. In addition, we also provide the formulation of a method to select the voltage-frequency scaling-concurrency throttling configurations that should be tested in order to obtain accurate estimations of the power dissipation. The power models and selection methodology are verified using two real scientific application: the stencil-based 3D MPDATA algorithm and the conjugate gradient (CG) method for sparse linear systems. MPDATA is a crucial component of the EULAG model, which is widely used in weather forecast simulations. The CG algorithm is the keystone for iterative solution of sparse symmetric positive definite linear systems via Krylov subspace methods. The reliability of the method is confirmed for a variety of ARM The researchers from Czestochowa University of Technology were supported by the National Science Centre, Poland, under Grant No. UMO-2015/17/D/ST6/04059. The researcher from Universidad Jaime I (UJI) was supported by the CICYT Project TIN2014-53495-R of MINECO and FEDER. This work was partially performed during a short-term scientific mission (STSM)

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Section: Overviewmentioning

confidence: 94%

“…Those readers that are more interested in the specification of MPDATA and its implementation can refer to [29,34,36].…”

Section: Overviewmentioning

confidence: 99%

Modeling power consumption of 3D MPDATA and the CG method on ARM and Intel multicore architectures

2017

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“…This approach allows to increase data locality and minimize the number of global memory transaction. Detailed description of the new GPU implementation one can find in [11]- [14].…”

Section: New C++ Implementation Of Mpdata For Cpumentioning

confidence: 99%

Adaptation of Multidimensional Positive Definite Advection Transport Algorithm to Modern High-Performance Computing Platforms

Rosa¹,

Szustak²,

Wyszogrodzki³

et al. 2015

IJMO

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The correctness and accuracy of the new implementations are examined based on a standard three-dimensional solid body rotation test case. Additionally, we focus on testing computational efficiency and scalability. In most runs and especially in simulations with larger computational grids the new codes performed better than the traditional implementation.Index Terms-MPDATA, advection solver, parallel computing.

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“…The proposed technique is based on stencil computations and is an extension of the concept described in previous studies [10]- [13]. In this paper, we assume prior knowledge about OpenCL programming and terminology.…”

Section: Adaptation Of Advection Transport Algorithm Mpdata To Gmentioning

confidence: 99%

Porting Multiscale Fluid Model EULAG to Modern Heterogeneous Architectures

Rosa¹,

Ciznicki²,

Rojek³

et al. 2014

IJAPM

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Towards Efficient Decomposition and Parallelization of MPDATA on Hybrid CPU-GPU Cluster

Cited by 15 publications

References 10 publications

Modeling power consumption of 3D MPDATA and the CG method on ARM and Intel multicore architectures

Modeling power consumption of 3D MPDATA and the CG method on ARM and Intel multicore architectures

Adaptation of Multidimensional Positive Definite Advection Transport Algorithm to Modern High-Performance Computing Platforms

Porting Multiscale Fluid Model EULAG to Modern Heterogeneous Architectures

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