References of "Besseron, Xavier 50000761"
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See detailOn the performance of an overlapping-domain parallelization strategy for Eulerian-Lagrangian Multiphysics software
Pozzetti, Gabriele UL; Besseron, Xavier UL; Rousset, Alban UL et al

in AIP Conference Proceedings (in press)

In this work, a strategy for the parallelization of a two-way CFD-DEM coupling is investigated. It consists on adopting balanced overlapping partitions for the CFD and the DEM domains, that aims to reduce ... [more ▼]

In this work, a strategy for the parallelization of a two-way CFD-DEM coupling is investigated. It consists on adopting balanced overlapping partitions for the CFD and the DEM domains, that aims to reduce the memory consumption and inter-process communication between CFD and DEM. Two benchmarks are proposed to assess the consistency and scalability of this approach, coupled execution on 252 cores shows that less than 1\% of time is used to perform inter-physics data exchange. [less ▲]

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See detailComparing Broad-Phase Interaction Detection Algorithms for Multiphysics DEM Applications
Rousset, Alban UL; Mainassara Chekaraou, Abdoul Wahid UL; Liao, Yu-Chung UL et al

Scientific Conference (2017, September)

Collision detection is an ongoing source of research and optimization in many fields including video-games and numerical simulations [6, 7, 8]. The goal of collision detection is to report a geometric ... [more ▼]

Collision detection is an ongoing source of research and optimization in many fields including video-games and numerical simulations [6, 7, 8]. The goal of collision detection is to report a geometric contact when it is about to occur or has actually occurred. Unfortunately, detailed and exact collision detection for large amounts of objects represent an immense amount of computations, naivly n 2 operation with n being the number of objects [9]. To avoid and reduce these expensive computations, the collision detection is decomposed in two phases as it shown on Figure 1: the Broad-Phase and the Narrow-Phase. In this paper, we focus on Broad-Phase algorithm in a large dynamic three-dimensional environment. We studied two kinds of Broad-Phase algorithms: spatial partitioning and spatial sorting. Spatial partitioning techniques op- erate by dividing space into a number of regions that can be quickly tested against each object. Two types of spatial partitioning will be considered: grids and trees. The grid-based algorithms consist of a spatial partitioning processing by dividing space into regions and testing if objects overlap the same region of space. And this reduces the number of pairwise to test. The tree-based algorithms use a tree structure where each node spans a particular space area. This reduces the pairwise checking cost because only tree leaves are checked. The spatial sorting based algorithm consists of a sorted spatial ordering of objects. Axis-Aligned Bounding Boxes (AABBs) are projected onto x, y and z axes and put into sorted lists. By sorting projection onto axes, two objects collide if and only if they collide on the three axes. This axis sorting reduces the number of pairwise to tested by reducing the number of tests to perform to only pairs which collide on at least one axis. For this study, ten different Broad-Phase collision detection algorithms or framework have been considered. The Bullet [6], CGAL [10, 11] frameworks have been used. Concerning the implemented algorithms most of them come from papers or given implementation [less ▲]

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See detailHPC or the Cloud: a cost study over an XDEM Simulation
Emeras, Joseph; Besseron, Xavier UL; Varrette, Sébastien UL et al

in Proc. of the 7th International Supercomputing Conference in Mexico (ISUM 2016) (2016)

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See detailPerformance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware
Besseron, Xavier UL; Plugaru, Valentin UL; Mahmoudi, Amir Houshang UL et al

in Proceedings of the Fourth International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2015, February)

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing ... [more ▼]

As Cloud Computing services become ever more prominent, it appears necessary to assess the efficiency of these solutions. This paper presents a performance evaluation of the OpenStack Cloud Computing middleware using our XDEM application simulating the pyrolysis of biomass as a benchmark. We propose a systematic study based on a fully automated benchmarking framework to evaluate 3 different configurations: Native (i.e. no virtualization), OpenStack with KVM and XEN hypervisors. Our approach features the following advantages: real user application, the fair comparison using the same hardware, the large scale distributed execution, while fully automated and reproducible. Experiments has been run on two different clusters, using up to 432 cores. Results show a moderate overhead for sequential execution and a significant penalty for distributed execution under the Cloud middleware. The overhead on multiple nodes is between 10% and 30% for OpenStack/KVM and 30% and 60% for OpenStack/XEN. [less ▲]

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See detailParaMASK: a Multi-Agent System for the Efficient and Dynamic Adaptation of HPC Workloads
Guzek, Mateusz UL; Besseron, Xavier UL; Varrette, Sébastien UL et al

in 14th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2014) (2014, December)

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See detailHPC Performance and Energy-Efficiency of the OpenStack Cloud Middleware
Varrette, Sébastien UL; Plugaru, Valentin UL; Guzek, Mateusz UL et al

in Proc. of the 43rd Intl. Conf. on Parallel Processing (ICPP-2014), Heterogeneous and Unconventional Cluster Architectures and Applications Workshop (HUCAA'14) (2014, September)

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See detailHPC Performance and Energy-Efficiency of Xen, KVM and VMware Hypervisors
Varrette, Sébastien UL; Guzek, Mateusz UL; Plugaru, Valentin UL et al

in Proc. of the 25th Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2013) (2013, October)

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization ... [more ▼]

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting green approaches with higher energy efficiency. In particular, virtualization is emerging as the prominent approach to mutualize the energy consumed by a single server running multiple VMs instances. Even today, it remains unclear whether the overhead induced by virtualization and the corresponding hypervisor middleware suits an environment as high-demanding as an HPC platform. In this paper, we analyze from an HPC perspective the three most widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi and compare them with a baseline environment running in native mode. We performed our experiments on the Grid’5000 platform by measuring the results of the reference HPL benchmark. Power measures were also performed in parallel to quantify the potential energy efficiency of the virtualized environments. In general, our study offers novel incentives toward in-house HPC platforms running without any virtualized frameworks. [less ▲]

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See detailUsing Data-flow analysis in MAS for power-aware HPC runs
Varrette, Sébastien UL; Danoy, Grégoire UL; Guzek, Mateusz UL et al

in Proc. of the IEEE Intl. Conf. on High Performance Computing and Simulation (HPCS'13) (2013)

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See detailDie Extended Discrete Element Method (XDEM) für multiphysikalische Anwendungen
Peters, Bernhard UL; Besseron, Xavier UL; Dziugys, Algis et al

Scientific Conference (2013)

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See detailUnified Design for Parallel Execution of Coupled Simulations using the Discrete Particle Method
Besseron, Xavier UL; Hoffmann, Florian UL; Michael, Mark UL et al

in Proceedings of the Third International Conference on Parallel, Distributed, Grid and Cloud Computing for Engineering (2013)

This paper presents the enhanced design of the Discrete Particle Method (DPM), a simulation tool which provides high quality and fast simulations to solve a broad range industrial processes involving ... [more ▼]

This paper presents the enhanced design of the Discrete Particle Method (DPM), a simulation tool which provides high quality and fast simulations to solve a broad range industrial processes involving granular materials. It enables to resolve mechanical and thermodynamics problems through different simulation modules (motions, chemical conversion). This new design allows to transparently couple the simulation modules in parallel execution. It relies on a unified interface and timebase of the simulation modules and a flexible decomposition in cells of the simulation space. Experimental results study the behavior of the Orthogonal Recursive Bisection (ORB) partitioning algorithm. A good scalability is achieved as the parallel execution on a distributed platform provides a 17-times speedup using 64 processes. [less ▲]

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See detailDie Extended Discrete Element Method (XDEM) für multiphysikalische Anwendungen
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

Scientific Conference (2013)

A vast number of engineering applications include a continuous and discrete phase simultaneously, and therefore, cannot be solved accurately by continuous or discrete approaches only. Problems that ... [more ▼]

A vast number of engineering applications include a continuous and discrete phase simultaneously, and therefore, cannot be solved accurately by continuous or discrete approaches only. Problems that involve both a continuous and a discrete phase are important in applications as diverse as pharmaceutical industry e.g. drug production, agriculture food and processing industry, mining, construction and agricultural machinery, metals manufacturing, energy production and systems biology. A novel technique referred to as Extended Discrete Element Method (XDEM) is developed, that offers a significant advancement for coupled discrete and continuous numerical simulation concepts. XDEM treats the solid phase representing the particles and the fluidised phase usually a fluid phase or a structure as two distinguished phases that are coupled through heat, mass and momentum transfer. An outstanding feature of the numerical concept is that each particle is treated as an individual entity that is described by its thermodynamic state e.g. temperature and reaction progress and its position and orientation in time and space. The thermodynamic state includes one-dimensional and transient distributions of temperature and species within the particle and therefore, allows a detailed and accurate characterisation of the reaction progress in a fluidised bed. Thus, the proposed methodology provides a high degree of resolution ranging from scales within a particle to the continuum phase as global dimensions. These superior features as compared to traditional and pure continuum mechanics approaches are applied to predict drying of wood particles in a packed bed and impact of particles on a membrane. Pre- heated air streamed through the packed bed, and thus, heated the particles with simultaneous evaporation of moisture. Water vapour is transferred into the gas phase at the surface of the particles and transported to the exit of the reactor. A rather inhomogeneous drying process in the upper part of the reactor with higher temperatures around the circumference of the inner reactor wall was observed. The latter is due to increased porosity in conjunction with higher mass flow rates than in the centre of the reactor, and thus, augmented heat transfer. A comparison of the weight loss over time agreed well with measurements. Under the impact of falling particles the surface of a membrane deforms that conversely affects the motion of particles on the surface. Due to an increasing vertical deformation particles roll or slide down toward the bottom of the recess, where they are collected in a heap. Furthermore, during initial impacts deformation waves are predicted that propagate through the structure, and may, already indicate resonant effects already before a prototype is built. Hence, the Extended Discrete Element Method offers a high degree of resolution avoiding further empirical correlations and extends the knowledge into the underlying physics. Although most of the work load concerning CFD and FEM is arranged in the ANSYS workbench, a complete integration is intended that allows for a smooth workflow of the entire simulation environment. [less ▲]

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See detailEnhanced Thermal Process Engineering by the Extended Discrete Element Method (XDEM)
Peters, Bernhard UL; Besseron, Xavier UL; Estupinan Donoso, Alvaro Antonio UL et al

in Universal Journal of Engineering Science (2013), 1

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only ... [more ▼]

A vast number of engineering applications <br />include a continuous and discrete phase simultaneously, <br />and therefore, cannot be solved accurately by continu- <br />ous or discrete approaches only. Problems that involve <br />both a continuous and a discrete phase are important <br />in applications as diverse as pharmaceutical industry <br />e.g. drug production, agriculture food and process- <br />ing industry, mining, construction and agricultural <br />machinery, metals manufacturing, energy production <br />and systems biology. A novel technique referred to as <br />Extended Discrete Element Method (XDEM) is devel- <br />oped, that o ers a signi cant advancement for coupled <br />discrete and continuous numerical simulation concepts. <br />The Extended Discrete Element Method extends the <br />dynamics of granular materials or particles as described <br />through the classical discrete element method (DEM) to <br />additional properties such as the thermodynamic state <br />or stress/strain for each particle coupled to a continuum <br />phase such as <br />uid <br />ow or solid structures. Contrary <br />to a continuum mechanics concept, XDEM aims at <br />resolving the particulate phase through the various <br />processes attached to particles. While DEM predicts <br />the spacial-temporal position and orientation for each <br />particle, XDEM additionally estimates properties such <br />as the internal temperature and/or species distribution. <br />These predictive capabilities are further extended by an <br />interaction to <br />uid <br />ow by heat, mass and momentum <br />transfer and impact of particles on structures. [less ▲]

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See detailMonitoring and Predicting Hardware Failures in HPC Clusters with FTB-IPMI
Rajachandrasekar, Raghunath; Besseron, Xavier UL; Panda, Dhabaleswar K.

in Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum (2012)

Fault-detection and prediction in HPC clusters and Cloud-computing systems are increasingly challenging issues. Several system middleware such as job schedulers and MPI implementations provide support for ... [more ▼]

Fault-detection and prediction in HPC clusters and Cloud-computing systems are increasingly challenging issues. Several system middleware such as job schedulers and MPI implementations provide support for both reactive and proactive mechanisms to tolerate faults. These techniques rely on external components such as system logs and infrastructure monitors to provide information about hardware/software failure either through detection, or as a prediction. However, these middleware work in isolation, without disseminating the knowledge of faults encountered. In this context, we propose a light-weight multi-threaded service, namely FTB-IPMI, which provides distributed fault-monitoring using the Intelligent Platform Management Interface (IPMI) and coordinated propagation of fault information using the Fault-Tolerance Backplane (FTB). In essence, it serves as a middleman between system hardware and the software stack by translating raw hardware events to structured software events and delivering it to any interested component using a publish-subscribe framework. Fault-predictors and other decision-making engines that rely on distributed failure information can benefit from FTB-IPMI to facilitate proactive fault-tolerance mechanisms such as preemptive job migration. We have developed a fault-prediction engine within MVAPICH2, an RDMA-based MPI implementation, to demonstrate this capability. Failure predictions made by this engine are used to trigger migration of processes from failing nodes to healthy spare nodes, thereby providing resilience to the MPI application. Experimental evaluation clearly indicates that a single instance of FTB-IPMI can scale to several hundreds of nodes with a remarkably low resource-utilization footprint. A deployment of FTB-IPMI that services a cluster with 128 compute-nodes, sweeps the entire cluster and collects IPMI sensor information on CPU temperature, system voltages and fan speeds in about 0.75 seconds. The average CPU utilization of this service running on a single node is 0.35%. [less ▲]

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