Performance analysis of a hybrid MPI/OpenMP application on multi-core clusters

Chorley, Martin; Walker, David W.

doi:10.1016/j.jocs.2010.05.001

Cited by 69 publications

(30 citation statements)

References 18 publications

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“…The simultaneous exploitation of different levels of parallelism is also pursued by Chorley and Walker [18], and in addition to already referenced work also by Williams et al and Pohl et al for the LBM [19,20].…”

Section: Related Workmentioning

confidence: 96%

A simulation suite for Lattice-Boltzmann based real-time CFD applications exploiting multi-level parallelism on modern multi- and many-core architectures

Geveler

Ribbrock

Mallach

et al. 2011

Journal of Computational Science

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We present a software approach to hardware-oriented numerics which builds upon an augmented, previously published set of open-source libraries facilitating portable code development and optimisation on a wide range of modern computer architectures. In order to maximise efficiency, we exploit all levels of parallelism, including vectorisation within CPU cores, the Cell BE and GPUs, shared memory thread-level parallelism between cores, and parallelism between heterogeneous distributed memory resources in clusters. To evaluate and validate our approach, we implement a collection of modular building blocks for the easy and fast assembly and development of CFD applications based on the shallow water equations: We combine the Lattice-Boltzmann method with fluid-structure interaction techniques in order to achieve real-time simulations targeting interactive virtual environments. Our results demonstrate that recent multi-core CPUs outperform the Cell BE, while GPUs are significantly faster than conventional multi-threaded SSE code. In addition, we verify good scalability properties of our application on small clusters.

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Section: Related Workmentioning

confidence: 96%

A simulation suite for Lattice-Boltzmann based real-time CFD applications exploiting multi-level parallelism on modern multi- and many-core architectures

Geveler

Ribbrock

Mallach

et al. 2011

Journal of Computational Science

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show abstract

“…Most current discussions in local sequence alignment focus on multicore architectures with shared memory such as divide and conquer techniques [16][17][18], striped SW [19][20][21][22], Instruction-set Processor (ASIP) architecture [23], data compression [24,25], genome assembly (re-sequence) algorithms [26,27], and Symmetric Multi-Processing (SMP) architecture [28,29]. This section discusses in detail these algorithms along with their advantage and disadvantage.…”

Section: Fig 3: Dual Core and Quad Core In Multicores Platformsmentioning

confidence: 99%

“…Numerous experiments have established test-bed for comparing three models to parallelize the SW algorithm including pure MPI, pure OpenMP, and a hybrid model using MPI/OpenMP [28,29]. Furthermore, evaluations and measurements for the performance of a hybrid model are tested.…”

Section: Symmetric Multi-processing (Smp) Architecturementioning

confidence: 99%

Shared Memory and Hardware Utilizations for the Parallelization of Local Sequences Alignment using SW Algorithm: A Review

Eltayeeb¹,

Latiff²,

Isnin³

2015

IJCA

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It is becoming increasingly difficult to ignore the importance of aligning DNA and Protein sequences to infer properties of new sequences from well-known reference sequences established and sorted in genetics databanks. Many studies in recent years have focused on different implementations of Sequences Alignment Problems (SAP). However, researcher confused with the ambiguous classification of the SAP. This paper is set out mainly to review, investigate, and analysis current trends in shared memory and hardware implementation of local SAP using Smith-Waterman algorithm. The literatures are addressing and evaluating in order to highlight their advantages and disadvantages.

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“…The performance of the algorithms is approaching their limit, though their use is not recommended for clinical practice [9] yet. However, the developments in the field High-performance computing can advance the spread of such methods [10] [11].…”

Section: Introductionmentioning

confidence: 99%

A two-phase decision support framework for the automatic screening of digital fundus images

Antal

Hajdú

Maros-Szabo

et al. 2012

Journal of Computational Science

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In this paper we give a brief review on the present status of automated detection systems describe for the screening of diabetic retinopathy. We further detail an enhanced detection procedure that consists of two steps. First, a pre-screening algorithm is considered to classify the input digital fundus images based on the severity of abnormalities. If an image is found to be seriously abnormal, it will not be analysed further with robust lesion detector algorithms. As a further improvement, we introduce a novel feature extraction approach based on clinical observations. The second step of the proposed method detects regions of interest with possible lesions on the images that previously passed the pre-screening step. These regions will serve as input to the specific lesion detectors for detailed analysis. This procedure can increase the computational performance of a screening system. Experimental results show that both two steps of the proposed approach are capable to efficiently * Corresponding author exclude a large amount of data from further processing, thus, to decrease the computational burden of the automatic screening system.

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Performance analysis of a hybrid MPI/OpenMP application on multi-core clusters

Cited by 69 publications

References 18 publications

A simulation suite for Lattice-Boltzmann based real-time CFD applications exploiting multi-level parallelism on modern multi- and many-core architectures

A simulation suite for Lattice-Boltzmann based real-time CFD applications exploiting multi-level parallelism on modern multi- and many-core architectures

Shared Memory and Hardware Utilizations for the Parallelization of Local Sequences Alignment using SW Algorithm: A Review

A two-phase decision support framework for the automatic screening of digital fundus images

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