Présentation d'une technique de parallélisation d'un logiciel de PIV 2D-2C utilisée sur super calculateur

International audienceDe nombreux algorithmes de vélocimétrie par images de particules ont été proposés ces dernières années pour améliorer la précision des résultats spatiaux et temporels. Des techniques comme la méthode multi grille avec déformation des images, très coûteuses en temps de calcul ont bénéficié de l’évolution de la puissance de calcul des ordinateurs pour être implémentées. Mais ces algorithmes sont généralement développés pour être exécutés en séquentiel sur un seul cœur d’un ordinateur et ne profitent pas de la totalité de la puissance de la machine, en particulier des supercalculateurs. Dans cet article, la technique de parallélisation à mémoire distribuée sera adaptée à un logiciel de traitement de données issues de la PIV 2D-2C développé à l’Institut de Mécanique des Fluides de Toulouse. Des tests de performance HPC sur le supercalculateur EOS du centre de Calcul de Midi-Pyrénées (CALMIP) ont montré des gains de temps de calcul proche de n pour un calcul lancé sur n cœurs. Un calcul sur le quart des cœurs du nouveau supercalculateur de CALMIP OLYMPE, soit sur 3240 cœurs a été réalisé sur une séquence d’environ 200 000 images de résolution 1280 par 800 pixels. Le calcul en séquentiel sur un cœur a été estimé à 127 jours, en parallèle sur 3240 cœurs ce calcul a duré une heure

VITAE : VIrTual brAin pErfusion

VITAE is an ERC funded software project aimed at providing full brain simulations of cerebral blood flow and solute exchange between blood and the neural tissue. The endgoal is to understand fine scale interactions between the architecture of the microvascular network in the brain and its functions (blood supply, oxygen and nutrient delivery, waste removal). This may indeed help unveil potential causes of cerebral disease like Alzheimer’s Disease. In the actual state of the art, full scale brain simulations are something new. First, acquiring input anatomical data of the blood vessel network is difficult and is an active domain of research. Next, simulation by itself is a CPU intensive Computational Fluid Dynamic problem requiring both inversion of large matrices and manipulation of large amounts of data. The current milestone is capable of running pressure resolution in a full mouse brain composed of about 5 millions of microvessels in one second on 1024 processor cores. The software written in C++ fully supports parallelized IO and graph partitioning to optimize the placement of vertices and reduce computing times. The next challenge is to run simulations taking the complex behavior of blood into account, which requires to run the pressure solver from one hundred to several thousand times. This will require to improve significantly the convergence time. Acknowledgements: ERC Funded Project: Proof of Concept (PoC), ERC-2018-PoC A. Sauvé, J.-D. Julien, M. Berg, M. Peyrounette, P. Elyakime, Y. Davit, M. Pigou, S. Lorthoi

Turbulent structure inside and above shallow to deep canopies

Multi-plane PIV measurements were performed in an open-channel flume filled with elongated prisms of height k and width l to investigate the effect of the deepening of the canopy on the flow structure. Velocity measurements were performed both inside the canopy and above it. Analysis of the spatial convergence for the double-averaged quantities shows that for canopy flow investigations (z k). Three canopy aspect ratios, k/l = [1, 3, 6] were investigated for a fixed modified-submergence ratio β = (h - k)=l = 3 where h is the water depth. As the canopy deepens, the hydraulic roughness decreases and the velocity near the bottom of the canopy becomes gradually constant, as expected for deep canopies. We show how the highly converged (both in space and time) profiles of double-averaged longitudinal velocity and total shear stress can be used to calculate the vertical distribution of drag in the canopy. With this methodology, values of the drag coefficient CD(z) can be calculated, and are found to be always close to unity, even in the upper part of the canopy

Shallow flow over a bed with a lateral change of roughness

River beds frequently exhibit a lateral variation of roughness. For example, in the case of an overflowing river, the main channel has a smoother topography compared to the adjacent floodplains where vegetation and land occupation yield an important hydraulic roughness. The lateral difference in roughness can induce a high lateral velocity gradient within the river cross- section that gives birth to a mixing layer. This mixing layer leads to fluid and momentum transfers between the two adjacent beds. To understand such mix- ing processes in rivers is important for predicting stage-discharge relationships and the velocity distribution within the cross-section. In order to address these issues in the context of a shallow water flow with a water depth h of the same order as the roughness elements of the bed, experiments were undertaken in a 26 m long and 1.1 m wide glass-walled open-channel flume. One half-side of the bed was covered with an array of cubes of height k arranged in a square configuration, the other side with smooth glass. Three different levels of cube submergence h/k were examined (h/k = 0.8, 1.5 and 2). The experiments and measurements were designed to yield the flow in the complete volume of the interstices across the cube array. To achieve this, 2C-3D linear-scanning PIV measurements with zero-parallax optics were developed and set up. The mea- surements revealed the complexity of the flow structure around the interface between the rough and smooth beds. The results show that the ability of the mixing layer to exchange momentum is highly dependent on the level of the cube submergence h/k

Shallow flow over a bed with a lateral change of roughness

River beds frequently exhibit a lateral variation of roughness. For example, in the case of an overflowing river, the main channel has a smoother topography compared to the adjacent floodplains where vegetation and land occupation yield an important hydraulic roughness. The lateral difference in roughness can induce a high lateral velocity gradient within the river cross- section that gives birth to a mixing layer. This mixing layer leads to fluid and momentum transfers between the two adjacent beds. To understand such mix- ing processes in rivers is important for predicting stage-discharge relationships and the velocity distribution within the cross-section. In order to address these issues in the context of a shallow water flow with a water depth h of the same order as the roughness elements of the bed, experiments were undertaken in a 26 m long and 1.1 m wide glass-walled open-channel flume. One half-side of the bed was covered with an array of cubes of height k arranged in a square configuration, the other side with smooth glass. Three different levels of cube submergence h/k were examined (h/k = 0.8, 1.5 and 2). The experiments and measurements were designed to yield the flow in the complete volume of the interstices across the cube array. To achieve this, 2C-3D linear-scanning PIV measurements with zero-parallax optics were developed and set up. The mea- surements revealed the complexity of the flow structure around the interface between the rough and smooth beds. The results show that the ability of the mixing layer to exchange momentum is highly dependent on the level of the cube submergence h/k

Habitat and species diversity indicators in relation fo farm managment parameters

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