The comparison of two domain repartitioning methods used for parallel discrete element computations of the hopper discharge

Markauskas, Darius; Kačeniauskas, Arnas

doi:10.1016/j.advengsoft.2014.12.002

Cited by 20 publications

(14 citation statements)

References 32 publications

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“…Moving particles dynamically change the workload configuration, making parallelization of DEM software much more difficult and challenging. Domain decomposition is considered one of the most efficient coarse-grain strategies for scientific and engineering computations; therefore, it was implemented in the developed DEM code [16,44]. The recursive coordinate bisection (RCB) method from the Zoltan library [48] was used for domain partitioning because it is highly effective for particle simulations [16,48].…”

Section: Parallel Implementationmentioning

confidence: 99%

“…Domain decomposition is considered one of the most efficient coarse-grain strategies for scientific and engineering computations; therefore, it was implemented in the developed DEM code [16,44]. The recursive coordinate bisection (RCB) method from the Zoltan library [48] was used for domain partitioning because it is highly effective for particle simulations [16,48]. The RCB method recursively divides the computational domain into nearly equal subdomains by cutting planes orthogonal to the coordinate axes, according to particle coordinates and workload weights.…”

Section: Parallel Implementationmentioning

confidence: 99%

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Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

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The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS.

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Section: Parallel Implementationmentioning

confidence: 99%

Section: Parallel Implementationmentioning

confidence: 99%

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021

Self Cite

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“…Topological schemes of domain decomposition, such as the multilevel k-way graph partitioning, were previously used for large-scale DEM models. Due to their more complex adaptation to DEM, those methods present lower parallel performance than geometric-based methods (Markauskas and Kacěniauskas, 2015). Hendrickson and Devine (2000) point geometric methods of decomposition as being well suited to particle simulations.…”

Section: Dlbmentioning

confidence: 99%

“…These methods work well when the interaction graph does not change frequently or for shared memory systems. However, due to the lack of constant connectivity inherent of this meshfree method, geometric schemes of domain decomposition perform better for distributed-memory systems (Markauskas and Kacěniauskas, 2015). Usually, simple geometric shapes delimit each subdomain, such as that adopted in the recursive coordinate bisection (RCB) (Fleissner and Eberhard, 2008).…”

Section: Introductionmentioning

confidence: 99%

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A hybrid parallel DEM approach with workload balancing based on HSFC

Cintra

Willmersdorf

Lyra

et al. 2016

Engineering Computations

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Purpose -The purpose of this paper is to present a methodology of hybrid parallelization applied to the discrete element method that combines message-passing interface and OpenMP to improve computational performance. The scheme is based on mapping procedures based on Hilbert spacefilling curves (HSFC). Design/methodology/approach -The methodology uses domain decomposition strategies to distribute the computation of large-scale models in a cluster. It also partitions the workload of each subdomain among threads. This additional procedure aims to reach higher computational performance by adjusting the usage of message-passing artefacts and threads. The main objective is to reduce the communication among processes. The work division by threads employs HSFC in order to improve data locality and to avoid related overheads. Numerical simulations presented in this work permit to evaluate the proposed method in terms of parallel performance for models that contain up to 3.2 million particles. Findings -Distinct partitioning algorithms were used in order to evaluate the local decomposition scheme, including the recursive coordinate bisection method and a topological scheme based on METIS. The results show that the hybrid implementations reach better computational performance than those based on message passing only, including a good control of load balancing among threads. Case studies present good scalability and parallel efficiencies. Originality/value -The proposed approach defines a configurable execution environment for numerical models and introduces a combined scheme that improves data locality and iterative workload balancing.

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Particle-scale computational approaches to model dry and saturated granular flows of non-Brownian, non-cohesive, and non-spherical rigid bodies

Wachs

2019

Acta Mech

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The comparison of two domain repartitioning methods used for parallel discrete element computations of the hopper discharge

Cited by 20 publications

References 32 publications

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

A hybrid parallel DEM approach with workload balancing based on HSFC

Particle-scale computational approaches to model dry and saturated granular flows of non-Brownian, non-cohesive, and non-spherical rigid bodies

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