Adaptive Refinement Tree (ART) code. N-Body: Parallelization using OpenMP and MPI

Size: px
Start display at page:

Download "Adaptive Refinement Tree (ART) code. N-Body: Parallelization using OpenMP and MPI"

Transcription

1 Adaptive Refinement Tree (ART) code N-Body: Parallelization using OpenMP and MPI 1

2 Family of codes N-body: OpenMp N-body: MPI+OpenMP N-body+hydro+cooling+SF: OpenMP N-body+hydro+cooling+SF: MPI 2

3 History: Particle-Mesh (PM): 1980, Klypin & Shandarin Adaptive Mesh Refinement (AMR) with irregular mesh: 1996, Khokhlov N-body ART: 1997, Kravtsov, Klypin, Khokhlov Hydro OpenMP: 2000 Kravtsov, Khokhlov Hydro MPI: 2005 Rudd, Kravtsov Radiative Transfer: , Gnedin, Kravtsov 3

4 Adaptive Refinement: Mesh is refined where the density exceeds a given threshold. Other quantity (such as jumps in pressure) can be used as additional condition for refinement. Refinement field defines how refinement is done. Each cell can be split into 8 new cells, each having twice smaller size. This is ideal for tracing anisotropic structures such as filaments. Adjacent cells can differ not more than by one level Time-step decreases by factor two with each level 4

5 Adaptive Refinement Zero-level Mesh 5

6 First-level Adaptive Refinement 5

7 Adaptive Refinement 5

8 Second-level Adaptive Refinement 5

9 Second-level Adaptive Refinement 5

10 Adaptive Refinement 5

11 Third-level Adaptive Refinement 5

12 Adaptive Refinement 5

13 Smoothing of the Refinement Field is required to reduce the noise in the mesh structure. 6

14 Smoothing of the Refinement Field is required to reduce the noise in the mesh structure. 6

15 Time stepping Scale of the time-step (actually step in the expansion parameter) is defined by the time-step at the zerolevel mesh On each subsequent level of refinement the time-time step decreases by factor two. For a particle moving with a constant speed the fraction of a cell, which it crosses per one time-step is independent on the level of refinement at which the particle moves. Courant condition : particles should not move more than a fraction of a cell per step. It is a global (refinement level independent) condition In practice, maximum particle displacement is of a cell. 7

16 Time stepping Refinement structure is rebuild every zerolevel time step. 8

17 Domain decomposition Used one way or another in MPI codes Rectangular domains Filling curves Load balancing and adaptive domains are issues to handle 9

18 ART: MPI The whole domain of integration is split into non-overlapping covering set of parallelepipeds Boundaries of the parallelepipeds can move in order to equalize the load balance Each domain is handled by one MPI task. Data (coordinates and velocities) of each domain are stored in separate directories 10

19 Example of domain decomposition Nx =3 Ny =4 System with 11 degrees of freedom Boundaries in y- direction may not be aligned All boundaries in x-direction are aligned 11

20 Simple idea how to split domains to get equal load For each domain we have cpu spend on previous time-step Assume that cpu is evenly distributed inside a domain Need to change positions of boundaries so that each domain will have the same cpu density of CPU Distribution of total cpu for all domains with the same x-boundaries

21 Solve 1d linear problem and then apply it to all directions CPU(x) 1 2/3 1/3 13

22 Solve 1d linear problem and then apply it to all directions CPU(x) 1 2/3 1/3 13

23 Solve 1d linear problem and then apply it to all directions It works fine when the cpu-density of domains are not too different CPU(x) 1 2/3 1/3 13

24 Fine tuning of boundary adjustment Case of two boundaries in 1d. Each boundary can have 3 positions: xold-dx, xold, xold+dx. We have 9 possible combinations. Estimate total cpu for each combination and chose the best density of CPU

25 Primary particles inside buffer zone are sent to the domain. xt At larger distances each domain creates large particles and sends them to other domains 15

26 16

27 OpenMP Each domain is handled by OpenMP After making one zero-level step (many steps on high levels), Get cpu timing and redistribute domain boundaries large particles are discarded. Primary particles, which left their domain are sent to their new domain. Primary particles, which come to the domain, are received Receive particles from buffer zone Create, send/receive large particles. Ready to go. 17

28 18

29 19

30 Load balancing 20

Asynchronous OpenCL/MPI numerical simulations of conservation laws

Asynchronous OpenCL/MPI numerical simulations of conservation laws Asynchronous OpenCL/MPI numerical simulations of conservation laws Philippe HELLUY 1,3, Thomas STRUB 2. 1 IRMA, Université de Strasbourg, 2 AxesSim, 3 Inria Tonus, France IWOCL 2015, Stanford Conservation

More information

Computational Astrophysics 5 Higher-order and AMR schemes

Computational Astrophysics 5 Higher-order and AMR schemes Computational Astrophysics 5 Higher-order and AMR schemes Oscar Agertz Outline - The Godunov Method - Second-order scheme with MUSCL - Slope limiters and TVD schemes - Characteristics tracing and 2D slopes.

More information

Cosmology Simulations with Enzo

Cosmology Simulations with Enzo Cosmology Simulations with Enzo John Wise (Georgia Tech) Enzo Workshop 17 Oct 2013 Outline Introduction to unigrid cosmology simulations Introduction to nested grid cosmology simulations Using different

More information

Adaptive Mesh Refinement

Adaptive Mesh Refinement Aleander Knebe, Universidad Autonoma de Madrid Adaptive Mesh Refinement AMR codes Poisson s equation ΔΦ( ) = 4πGρ( ) Poisson s equation F ( ) = m Φ( ) ΔΦ( ) = 4πGρ( ) particle approach F ( Gm i ) = i m

More information

SOLIDWORKS Flow Simulation Options

SOLIDWORKS Flow Simulation Options SOLIDWORKS Flow Simulation Options SOLIDWORKS Flow Simulation includes an options dialogue window that allows for defining default options to use for a new project. Some of the options included are unit

More information

The Swift simulation code

The Swift simulation code The Swift simulation code ICC, Durham! : Intro to SPH Bert VandenBroucke: GIZMO Pedro Gonnet: Task-based parallelism Matthieu Schaller: Swift 1 Cosmological hydrodynamical simulations Eagle in Durham 2

More information

Development of a Computational Framework for Block-Based AMR Simulations

Development of a Computational Framework for Block-Based AMR Simulations Procedia Computer Science Volume 29, 2014, Pages 2351 2359 ICCS 2014. 14th International Conference on Computational Science Development of a Computational Framework for Block-Based AMR Simulations Hideyuki

More information

A Scalable Adaptive Mesh Refinement Framework For Parallel Astrophysics Applications

A Scalable Adaptive Mesh Refinement Framework For Parallel Astrophysics Applications A Scalable Adaptive Mesh Refinement Framework For Parallel Astrophysics Applications James Bordner, Michael L. Norman San Diego Supercomputer Center University of California, San Diego 15th SIAM Conference

More information

Adaptive Mesh Astrophysical Fluid Simulations on GPU. San Jose 10/2/2009 Peng Wang, NVIDIA

Adaptive Mesh Astrophysical Fluid Simulations on GPU. San Jose 10/2/2009 Peng Wang, NVIDIA Adaptive Mesh Astrophysical Fluid Simulations on GPU San Jose 10/2/2009 Peng Wang, NVIDIA Overview Astrophysical motivation & the Enzo code Finite volume method and adaptive mesh refinement (AMR) CUDA

More information

Splotch: High Performance Visualization using MPI, OpenMP and CUDA

Splotch: High Performance Visualization using MPI, OpenMP and CUDA Splotch: High Performance Visualization using MPI, OpenMP and CUDA Klaus Dolag (Munich University Observatory) Martin Reinecke (MPA, Garching) Claudio Gheller (CSCS, Switzerland), Marzia Rivi (CINECA,

More information

GEOMETRY MODELING & GRID GENERATION

GEOMETRY MODELING & GRID GENERATION GEOMETRY MODELING & GRID GENERATION Dr.D.Prakash Senior Assistant Professor School of Mechanical Engineering SASTRA University, Thanjavur OBJECTIVE The objectives of this discussion are to relate experiences

More information

GAMER : a GPU-accelerated Adaptive-MEsh-Refinement Code for Astrophysics GPU 與自適性網格於天文模擬之應用與效能

GAMER : a GPU-accelerated Adaptive-MEsh-Refinement Code for Astrophysics GPU 與自適性網格於天文模擬之應用與效能 GAMER : a GPU-accelerated Adaptive-MEsh-Refinement Code for Astrophysics GPU 與自適性網格於天文模擬之應用與效能 Hsi-Yu Schive ( 薛熙于 ), Tzihong Chiueh ( 闕志鴻 ), Yu-Chih Tsai ( 蔡御之 ), Ui-Han Zhang ( 張瑋瀚 ) Graduate Institute

More information

RASCAS LEO MICHEL-DANSAC, JEREMY BLAIZOT, THIBAULT GAREL, ANNE VERHAMME. (aka MCLya v.2.0)

RASCAS LEO MICHEL-DANSAC, JEREMY BLAIZOT, THIBAULT GAREL, ANNE VERHAMME. (aka MCLya v.2.0) RASCAS (aka MCLya v.2.0) A massively parallel code for line transfer in AMR simulations. LEO MICHEL-DANSAC, JEREMY BLAIZOT, THIBAULT GAREL, ANNE VERHAMME INTRO SCIENCE MOTIVATIONS LAEs, EoR, LABs, (MUSE,

More information

Best Practices: Volume Meshing Kynan Maley

Best Practices: Volume Meshing Kynan Maley Best Practices: Volume Meshing Kynan Maley Volume Meshing Volume meshing is the basic tool that allows the creation of the space discretization needed to solve most of the CAE equations for: CFD Stress

More information

Intro to Parallel Computing

Intro to Parallel Computing Outline Intro to Parallel Computing Remi Lehe Lawrence Berkeley National Laboratory Modern parallel architectures Parallelization between nodes: MPI Parallelization within one node: OpenMP Why use parallel

More information

arxiv:astro-ph/ v3 29 Jul 1997

arxiv:astro-ph/ v3 29 Jul 1997 Astrophys.J.Supplement 111, 73, 1997 ADAPTIVE REFINEMENT TREE A NEW HIGH-RESOLUTION N-BODY CODE FOR COSMOLOGICAL SIMULATIONS Andrey V. Kravtsov, and Anatoly A. Klypin Astronomy Department, New Mexico State

More information

PiTP Summer School 2009

PiTP Summer School 2009 PiTP Summer School 2009 Plan for my lectures Volker Springel Lecture 1 Basics of collisionless dynamics and the N-body approach Lecture 2 Gravitational solvers suitable for collisionless dynamics, parallelization

More information

Multigrid Pattern. I. Problem. II. Driving Forces. III. Solution

Multigrid Pattern. I. Problem. II. Driving Forces. III. Solution Multigrid Pattern I. Problem Problem domain is decomposed into a set of geometric grids, where each element participates in a local computation followed by data exchanges with adjacent neighbors. The grids

More information

Velocity and Concentration Properties of Porous Medium in a Microfluidic Device

Velocity and Concentration Properties of Porous Medium in a Microfluidic Device Velocity and Concentration Properties of Porous Medium in a Microfluidic Device Rachel Freeman Department of Chemical Engineering University of Washington ChemE 499 Undergraduate Research December 14,

More information

ALE and AMR Mesh Refinement Techniques for Multi-material Hydrodynamics Problems

ALE and AMR Mesh Refinement Techniques for Multi-material Hydrodynamics Problems ALE and AMR Mesh Refinement Techniques for Multi-material Hydrodynamics Problems A. J. Barlow, AWE. ICFD Workshop on Mesh Refinement Techniques 7th December 2005 Acknowledgements Thanks to Chris Powell,

More information

Hybrid OpenMP-MPI Turbulent boundary Layer code over 32k cores

Hybrid OpenMP-MPI Turbulent boundary Layer code over 32k cores Hybrid OpenMP-MPI Turbulent boundary Layer code over 32k cores T/NT INTERFACE y/ x/ z/ 99 99 Juan A. Sillero, Guillem Borrell, Javier Jiménez (Universidad Politécnica de Madrid) and Robert D. Moser (U.

More information

Project 2 Solution. General Procedure for Model Setup

Project 2 Solution. General Procedure for Model Setup Project 2 Solution MAE598 Applied Computational Fluid Dynamics Shashank Kunjibettu General Procedure for Model Setup Step 1: Model the given component using design modeler Step 2: Meshing is done for the

More information

HARNESSING IRREGULAR PARALLELISM: A CASE STUDY ON UNSTRUCTURED MESHES. Cliff Woolley, NVIDIA

HARNESSING IRREGULAR PARALLELISM: A CASE STUDY ON UNSTRUCTURED MESHES. Cliff Woolley, NVIDIA HARNESSING IRREGULAR PARALLELISM: A CASE STUDY ON UNSTRUCTURED MESHES Cliff Woolley, NVIDIA PREFACE This talk presents a case study of extracting parallelism in the UMT2013 benchmark for 3D unstructured-mesh

More information

RAMSES on the GPU: An OpenACC-Based Approach

RAMSES on the GPU: An OpenACC-Based Approach RAMSES on the GPU: An OpenACC-Based Approach Claudio Gheller (ETHZ-CSCS) Giacomo Rosilho de Souza (EPFL Lausanne) Romain Teyssier (University of Zurich) Markus Wetzstein (ETHZ-CSCS) PRACE-2IP project EU

More information

BioIRC solutions. CFDVasc manual

BioIRC solutions. CFDVasc manual BioIRC solutions CFDVasc manual Main window of application is consisted from two parts: toolbar - which consist set of button for accessing variety of present functionalities image area area in which is

More information

Parallel Algorithm Design. Parallel Algorithm Design p. 1

Parallel Algorithm Design. Parallel Algorithm Design p. 1 Parallel Algorithm Design Parallel Algorithm Design p. 1 Overview Chapter 3 from Michael J. Quinn, Parallel Programming in C with MPI and OpenMP Another resource: http://www.mcs.anl.gov/ itf/dbpp/text/node14.html

More information

Part I: Theoretical Background and Integration-Based Methods

Part I: Theoretical Background and Integration-Based Methods Large Vector Field Visualization: Theory and Practice Part I: Theoretical Background and Integration-Based Methods Christoph Garth Overview Foundations Time-Varying Vector Fields Numerical Integration

More information

A4. Intro to Parallel Computing

A4. Intro to Parallel Computing Self-Consistent Simulations of Beam and Plasma Systems Steven M. Lund, Jean-Luc Vay, Rémi Lehe and Daniel Winklehner Colorado State U., Ft. Collins, CO, 13-17 June, 2016 A4. Intro to Parallel Computing

More information

v Map Module Operations SMS Tutorials Prerequisites Requirements Time Objectives

v Map Module Operations SMS Tutorials Prerequisites Requirements Time Objectives v. 12.3 SMS 12.3 Tutorial Objectives This tutorial describes the fundamental tools in the Map module of the SMS. This tutorial provides information that is useful when constructing any type of geometric

More information

Experiences with ENZO on the Intel Many Integrated Core Architecture

Experiences with ENZO on the Intel Many Integrated Core Architecture Experiences with ENZO on the Intel Many Integrated Core Architecture Dr. Robert Harkness National Institute for Computational Sciences April 10th, 2012 Overview ENZO applications at petascale ENZO and

More information

1.992, 2.993, 3.04, 10.94, , Introduction to Modeling and Simulation Prof. F.-J. Ulm Spring FE Modeling Example Using ADINA

1.992, 2.993, 3.04, 10.94, , Introduction to Modeling and Simulation Prof. F.-J. Ulm Spring FE Modeling Example Using ADINA 1.992, 2.993, 3.04, 10.94, 18.996, 22.091 Introduction to Modeling and Simulation Prof. F.-J. Ulm Spring 2002 FE Modeling Example Using ADINA H Hgρ w ργ H = B = 10 m g = 9.81 m/s 2 ρ = 2400 kg/m 3 ρ w

More information

Adaptive-Mesh-Refinement Hydrodynamic GPU Computation in Astrophysics

Adaptive-Mesh-Refinement Hydrodynamic GPU Computation in Astrophysics Adaptive-Mesh-Refinement Hydrodynamic GPU Computation in Astrophysics H. Y. Schive ( 薛熙于 ) Graduate Institute of Physics, National Taiwan University Leung Center for Cosmology and Particle Astrophysics

More information

Computational Fluid Dynamics with the Lattice Boltzmann Method KTH SCI, Stockholm

Computational Fluid Dynamics with the Lattice Boltzmann Method KTH SCI, Stockholm Computational Fluid Dynamics with the Lattice Boltzmann Method KTH SCI, Stockholm March 17 March 21, 2014 Florian Schornbaum, Martin Bauer, Simon Bogner Chair for System Simulation Friedrich-Alexander-Universität

More information

Load Balancing and Data Migration in a Hybrid Computational Fluid Dynamics Application

Load Balancing and Data Migration in a Hybrid Computational Fluid Dynamics Application Load Balancing and Data Migration in a Hybrid Computational Fluid Dynamics Application Esteban Meneses Patrick Pisciuneri Center for Simulation and Modeling (SaM) University of Pittsburgh University of

More information

Presented by: Terry L. Wilmarth

Presented by: Terry L. Wilmarth C h a l l e n g e s i n D y n a m i c a l l y E v o l v i n g M e s h e s f o r L a r g e - S c a l e S i m u l a t i o n s Presented by: Terry L. Wilmarth Parallel Programming Laboratory and Center for

More information

simulation framework for piecewise regular grids

simulation framework for piecewise regular grids WALBERLA, an ultra-scalable multiphysics simulation framework for piecewise regular grids ParCo 2015, Edinburgh September 3rd, 2015 Christian Godenschwager, Florian Schornbaum, Martin Bauer, Harald Köstler

More information

Using GADGET-2 for cosmological simulations - Background -

Using GADGET-2 for cosmological simulations - Background - Using GADGET-2 for cosmological simulations - Background - 3 Phases of Running a Cosmological Simulation I. Generate Initial Conditions II. Run Simulation Performing a numerical integral III.Analysis Halo

More information

Lecture 5. Applications: N-body simulation, sorting, stencil methods

Lecture 5. Applications: N-body simulation, sorting, stencil methods Lecture 5 Applications: N-body simulation, sorting, stencil methods Announcements Quiz #1 in section on 10/13 Midterm: evening of 10/30, 7:00 to 8:20 PM In Assignment 2, the following variation is suggested

More information

Scientific Computing at Million-way Parallelism - Blue Gene/Q Early Science Program

Scientific Computing at Million-way Parallelism - Blue Gene/Q Early Science Program Scientific Computing at Million-way Parallelism - Blue Gene/Q Early Science Program Implementing Hybrid Parallelism in FLASH Christopher Daley 1 2 Vitali Morozov 1 Dongwook Lee 2 Anshu Dubey 1 2 Jonathon

More information

Dynamic load balancing in OSIRIS

Dynamic load balancing in OSIRIS Dynamic load balancing in OSIRIS R. A. Fonseca 1,2 1 GoLP/IPFN, Instituto Superior Técnico, Lisboa, Portugal 2 DCTI, ISCTE-Instituto Universitário de Lisboa, Portugal Maintaining parallel load balance

More information

Contribution to GMGW 1

Contribution to GMGW 1 Contribution to GMGW 1 Rocco Nastasia, Saurabh Tendulkar, Mark Beall Simmetrix Inc., Clifton Park, NY 12065 Riccardo Balin, Scott Wurst, Ryan Skinner, Kenneth E. Jansen Department of Aerospace Engineering

More information

Praktikum 2014 Parallele Programmierung Universität Hamburg Dept. Informatics / Scientific Computing. October 23, FluidSim.

Praktikum 2014 Parallele Programmierung Universität Hamburg Dept. Informatics / Scientific Computing. October 23, FluidSim. Praktikum 2014 Parallele Programmierung Universität Hamburg Dept. Informatics / Scientific Computing October 23, 2014 Paul Bienkowski Author 2bienkow@informatik.uni-hamburg.de Dr. Julian Kunkel Supervisor

More information

Parallel Multigrid on Cartesian Meshes with Complex Geometry +

Parallel Multigrid on Cartesian Meshes with Complex Geometry + Parallel Multigrid on Cartesian Meshes with Complex Geometry + Marsha Berger a and Michael Aftosmis b and Gedas Adomavicius a a Courant Institute, New York University, 251 Mercer St., New York, NY 10012

More information

Fault tolerant issues in large scale applications

Fault tolerant issues in large scale applications Fault tolerant issues in large scale applications Romain Teyssier George Lake, Ben Moore, Joachim Stadel and the other members of the project «Cosmology at the petascale» SPEEDUP 2010 1 Outline Computational

More information

ExaFMM. Fast multipole method software aiming for exascale systems. User's Manual. Rio Yokota, L. A. Barba. November Revision 1

ExaFMM. Fast multipole method software aiming for exascale systems. User's Manual. Rio Yokota, L. A. Barba. November Revision 1 ExaFMM Fast multipole method software aiming for exascale systems User's Manual Rio Yokota, L. A. Barba November 2011 --- Revision 1 ExaFMM User's Manual i Revision History Name Date Notes Rio Yokota,

More information

Data Partitioning. Figure 1-31: Communication Topologies. Regular Partitions

Data Partitioning. Figure 1-31: Communication Topologies. Regular Partitions Data In single-program multiple-data (SPMD) parallel programs, global data is partitioned, with a portion of the data assigned to each processing node. Issues relevant to choosing a partitioning strategy

More information

c Fluent Inc. May 16,

c Fluent Inc. May 16, Tutorial 1. Office Ventilation Introduction: This tutorial demonstrates how to model an office shared by two people working at computers, using Airpak. In this tutorial, you will learn how to: Open a new

More information

Lecture overview. Visualisatie BMT. Vector algorithms. Vector algorithms. Time animation. Time animation

Lecture overview. Visualisatie BMT. Vector algorithms. Vector algorithms. Time animation. Time animation Visualisatie BMT Lecture overview Vector algorithms Tensor algorithms Modeling algorithms Algorithms - 2 Arjan Kok a.j.f.kok@tue.nl 1 2 Vector algorithms Vector 2 or 3 dimensional representation of direction

More information

Vector Visualization. CSC 7443: Scientific Information Visualization

Vector Visualization. CSC 7443: Scientific Information Visualization Vector Visualization Vector data A vector is an object with direction and length v = (v x,v y,v z ) A vector field is a field which associates a vector with each point in space The vector data is 3D representation

More information

Efficient Meshing in Sonnet

Efficient Meshing in Sonnet Efficient Meshing in Sonnet Purpose of this document: In this document, we will discuss efficient meshing in Sonnet, based on a wide variety of application examples. It will be shown how manual changes

More information

Automatic Partiicle Tracking Software USE ER MANUAL Update: May 2015

Automatic Partiicle Tracking Software USE ER MANUAL Update: May 2015 Automatic Particle Tracking Software USER MANUAL Update: May 2015 File Menu The micrograph below shows the panel displayed when a movie is opened, including a playback menu where most of the parameters

More information

3D ADI Method for Fluid Simulation on Multiple GPUs. Nikolai Sakharnykh, NVIDIA Nikolay Markovskiy, NVIDIA

3D ADI Method for Fluid Simulation on Multiple GPUs. Nikolai Sakharnykh, NVIDIA Nikolay Markovskiy, NVIDIA 3D ADI Method for Fluid Simulation on Multiple GPUs Nikolai Sakharnykh, NVIDIA Nikolay Markovskiy, NVIDIA Introduction Fluid simulation using direct numerical methods Gives the most accurate result Requires

More information

Introduction to ANSYS ICEM CFD

Introduction to ANSYS ICEM CFD Lecture 4 Volume Meshing 14. 0 Release Introduction to ANSYS ICEM CFD 1 2011 ANSYS, Inc. March 21, 2012 Introduction to Volume Meshing To automatically create 3D elements to fill volumetric domain Generally

More information

Lecture 4: Locality and parallelism in simulation I

Lecture 4: Locality and parallelism in simulation I Lecture 4: Locality and parallelism in simulation I David Bindel 6 Sep 2011 Logistics Distributed memory machines Each node has local memory... and no direct access to memory on other nodes Nodes communicate

More information

Problem description. The FCBI-C element is used in the fluid part of the model.

Problem description. The FCBI-C element is used in the fluid part of the model. Problem description This tutorial illustrates the use of ADINA for analyzing the fluid-structure interaction (FSI) behavior of a flexible splitter behind a 2D cylinder and the surrounding fluid in a channel.

More information

T6: Position-Based Simulation Methods in Computer Graphics. Jan Bender Miles Macklin Matthias Müller

T6: Position-Based Simulation Methods in Computer Graphics. Jan Bender Miles Macklin Matthias Müller T6: Position-Based Simulation Methods in Computer Graphics Jan Bender Miles Macklin Matthias Müller Jan Bender Organizer Professor at the Visual Computing Institute at Aachen University Research topics

More information

APPLIED COMPUTATIONAL FLUID DYNAMICS-PROJECT-3

APPLIED COMPUTATIONAL FLUID DYNAMICS-PROJECT-3 APPLIED COMPUTATIONAL FLUID DYNAMICS-PROJECT-3 BY SAI CHAITANYA MANGAVELLI Common Setup Data: 1) Mesh Proximity and Curvature with Refinement of 2. 2) Double Precision and second order for methods in Solver.

More information

An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids

An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids R. Elliot English, Linhai Qiu, Yue Yu, Ronald Fedkiw Stanford University, 353 Serra Mall Room 27, Stanford,

More information

Direct Numerical Simulation of Turbulent Boundary Layers at High Reynolds Numbers.

Direct Numerical Simulation of Turbulent Boundary Layers at High Reynolds Numbers. Direct Numerical Simulation of Turbulent Boundary Layers at High Reynolds Numbers. G. Borrell, J.A. Sillero and J. Jiménez, Corresponding author: guillem@torroja.dmt.upm.es School of Aeronautics, Universidad

More information

Team 194: Aerodynamic Study of Airflow around an Airfoil in the EGI Cloud

Team 194: Aerodynamic Study of Airflow around an Airfoil in the EGI Cloud Team 194: Aerodynamic Study of Airflow around an Airfoil in the EGI Cloud CFD Support s OpenFOAM and UberCloud Containers enable efficient, effective, and easy access and use of MEET THE TEAM End-User/CFD

More information

SPEED-UP GEARBOX SIMULATIONS BY INTEGRATING SCORG. Dr. Christine Klier, Sahand Saheb-Jahromi, Ludwig Berger*

SPEED-UP GEARBOX SIMULATIONS BY INTEGRATING SCORG. Dr. Christine Klier, Sahand Saheb-Jahromi, Ludwig Berger* SPEED-UP GEARBOX SIMULATIONS BY INTEGRATING SCORG Dr. Christine Klier, Sahand Saheb-Jahromi, Ludwig Berger* CFD SCHUCK ENGINEERING Engineering Services in computational fluid Dynamics (CFD) 25 employees

More information

Speedup Altair RADIOSS Solvers Using NVIDIA GPU

Speedup Altair RADIOSS Solvers Using NVIDIA GPU Innovation Intelligence Speedup Altair RADIOSS Solvers Using NVIDIA GPU Eric LEQUINIOU, HPC Director Hongwei Zhou, Senior Software Developer May 16, 2012 Innovation Intelligence ALTAIR OVERVIEW Altair

More information

Software and Performance Engineering for numerical codes on GPU clusters

Software and Performance Engineering for numerical codes on GPU clusters Software and Performance Engineering for numerical codes on GPU clusters H. Köstler International Workshop of GPU Solutions to Multiscale Problems in Science and Engineering Harbin, China 28.7.2010 2 3

More information

Over Two Decades of IntegrationBased, Geometric Vector Field. Visualization

Over Two Decades of IntegrationBased, Geometric Vector Field. Visualization Over Two Decades of IntegrationBased, Geometric Vector Field Visualization Tony McLoughlin1, 1, Ronald Peikert2, Frits H. Post3, and Min Chen1 1 The Visual and Interactive Computing Group Computer Science

More information

Abstract. Die Geometry. Introduction. Mesh Partitioning Technique for Coextrusion Simulation

Abstract. Die Geometry. Introduction. Mesh Partitioning Technique for Coextrusion Simulation OPTIMIZATION OF A PROFILE COEXTRUSION DIE USING A THREE-DIMENSIONAL FLOW SIMULATION SOFTWARE Kim Ryckebosh 1 and Mahesh Gupta 2, 3 1. Deceuninck nv, BE-8830 Hooglede-Gits, Belgium 2. Michigan Technological

More information

Using the Discrete Ordinates Radiation Model

Using the Discrete Ordinates Radiation Model Tutorial 6. Using the Discrete Ordinates Radiation Model Introduction This tutorial illustrates the set up and solution of flow and thermal modelling of a headlamp. The discrete ordinates (DO) radiation

More information

HPC Computer Aided CINECA

HPC Computer Aided CINECA HPC Computer Aided Engineering @ CINECA Raffaele Ponzini Ph.D. CINECA SuperComputing Applications and Innovation Department SCAI 16-18 June 2014 Segrate (MI), Italy Outline Open-source CAD and Meshing

More information

Parallel Algorithms: Adaptive Mesh Refinement (AMR) method and its implementation

Parallel Algorithms: Adaptive Mesh Refinement (AMR) method and its implementation Parallel Algorithms: Adaptive Mesh Refinement (AMR) method and its implementation Massimiliano Guarrasi m.guarrasi@cineca.it Super Computing Applications and Innovation Department AMR - Introduction Solving

More information

An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids

An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids An adaptive discretization of incompressible flow using a multitude of moving Cartesian grids R. Elliot English, Linhai Qiu,YueYu, Ronald Fedkiw Stanford University, 353 Serra Mall Room 27, Stanford, CA

More information

Objectives Build a 3D mesh and a FEMWATER flow model using the conceptual model approach. Run the model and examine the results.

Objectives Build a 3D mesh and a FEMWATER flow model using the conceptual model approach. Run the model and examine the results. v. 10.0 GMS 10.0 Tutorial Build a FEMWATER model to simulate flow Objectives Build a 3D mesh and a FEMWATER flow model using the conceptual model approach. Run the model and examine the results. Prerequisite

More information

Reporting Mesh Statistics

Reporting Mesh Statistics Chapter 15. Reporting Mesh Statistics The quality of a mesh is determined more effectively by looking at various statistics, such as maximum skewness, rather than just performing a visual inspection. Unlike

More information

Use 6DOF solver to calculate motion of the moving body. Create TIFF files for graphic visualization of the solution.

Use 6DOF solver to calculate motion of the moving body. Create TIFF files for graphic visualization of the solution. Introduction The purpose of this tutorial is to provide guidelines and recommendations for setting up and solving a moving deforming mesh (MDM) case along with the six degree of freedom (6DOF) solver and

More information

Introduction to Parallel Programming for Multicore/Manycore Clusters Part II-3: Parallel FVM using MPI

Introduction to Parallel Programming for Multicore/Manycore Clusters Part II-3: Parallel FVM using MPI Introduction to Parallel Programming for Multi/Many Clusters Part II-3: Parallel FVM using MPI Kengo Nakajima Information Technology Center The University of Tokyo 2 Overview Introduction Local Data Structure

More information

Designing Parallel Programs. This review was developed from Introduction to Parallel Computing

Designing Parallel Programs. This review was developed from Introduction to Parallel Computing Designing Parallel Programs This review was developed from Introduction to Parallel Computing Author: Blaise Barney, Lawrence Livermore National Laboratory references: https://computing.llnl.gov/tutorials/parallel_comp/#whatis

More information

Cost Estimation Algorithms for Dynamic Load Balancing of AMR Simulations

Cost Estimation Algorithms for Dynamic Load Balancing of AMR Simulations Cost Estimation Algorithms for Dynamic Load Balancing of AMR Simulations Justin Luitjens, Qingyu Meng, Martin Berzins, John Schmidt, et al. Thanks to DOE for funding since 1997, NSF since 2008, TACC, NICS

More information

Particles. The Center for Astrophysical Thermonuclear Flashes. Chris Daley

Particles. The Center for Astrophysical Thermonuclear Flashes. Chris Daley The Center for Astrophysical Thermonuclear Flashes Particles Chris Daley An Advanced Simulation & Computing (ASC) Academic Strategic Alliances Program (ASAP) Center at Particle flavors Passive particles

More information

Finite Volume Discretization on Irregular Voronoi Grids

Finite Volume Discretization on Irregular Voronoi Grids Finite Volume Discretization on Irregular Voronoi Grids C.Huettig 1, W. Moore 1 1 Hampton University / National Institute of Aerospace Folie 1 The earth and its terrestrial neighbors NASA Colin Rose, Dorling

More information

Simulating Smoke with an Octree Data Structure and Ray Marching

Simulating Smoke with an Octree Data Structure and Ray Marching Simulating Smoke with an Octree Data Structure and Ray Marching Edward Eisenberger Maria Montenegro Abstract We present a method for simulating and rendering smoke using an Octree data structure and Monte

More information

Ateles performance assessment report

Ateles performance assessment report Ateles performance assessment report Document Information Reference Number Author Contributor(s) Date Application Service Level Keywords AR-4, Version 0.1 Jose Gracia (USTUTT-HLRS) Christoph Niethammer,

More information

CMSC 714 Lecture 6 MPI vs. OpenMP and OpenACC. Guest Lecturer: Sukhyun Song (original slides by Alan Sussman)

CMSC 714 Lecture 6 MPI vs. OpenMP and OpenACC. Guest Lecturer: Sukhyun Song (original slides by Alan Sussman) CMSC 714 Lecture 6 MPI vs. OpenMP and OpenACC Guest Lecturer: Sukhyun Song (original slides by Alan Sussman) Parallel Programming with Message Passing and Directives 2 MPI + OpenMP Some applications can

More information

Michela Mapelli. N-body techniques for astrophysics: Lecture 6 GAS

Michela Mapelli. N-body techniques for astrophysics: Lecture 6 GAS Michela Mapelli N-body techniques for astrophysics: Lecture 6 GAS PhD School in Astrophysics, University of Padova November 19-30, 2018 OUTLINE of this lecture: 1 Equations of gas 2 Mesh codes/ Adaptive

More information

Mixed Mode MPI / OpenMP Programming

Mixed Mode MPI / OpenMP Programming Mixed Mode MPI / OpenMP Programming L.A. Smith Edinburgh Parallel Computing Centre, Edinburgh, EH9 3JZ 1 Introduction Shared memory architectures are gradually becoming more prominent in the HPC market,

More information

New Technologies in CST STUDIO SUITE CST COMPUTER SIMULATION TECHNOLOGY

New Technologies in CST STUDIO SUITE CST COMPUTER SIMULATION TECHNOLOGY New Technologies in CST STUDIO SUITE 2016 Outline Design Tools & Modeling Antenna Magus Filter Designer 2D/3D Modeling 3D EM Solver Technology Cable / Circuit / PCB Systems Multiphysics CST Design Tools

More information

7. Stochastic Fractals

7. Stochastic Fractals Stochastic Fractals Christoph Traxler Fractals-Stochastic 1 Stochastic Fractals Simulation of Brownian motion Modelling of natural phenomena, like terrains, clouds, waves,... Modelling of microstructures,

More information

Recent Advances in Modelling Wind Parks in STAR CCM+ Steve Evans

Recent Advances in Modelling Wind Parks in STAR CCM+ Steve Evans Recent Advances in Modelling Wind Parks in STAR CCM+ Steve Evans Introduction Company STAR-CCM+ Agenda Wind engineering at CD-adapco STAR-CCM+ & EnviroWizard Developments for Offshore Simulation CD-adapco:

More information

300 N All lengths in meters. Step load applied at time 0.0.

300 N All lengths in meters. Step load applied at time 0.0. Problem description In this problem, we subject the beam structure of problem 1 to an impact load as shown. 300 N 0.02 0.02 1 All lengths in meters. Step load applied at time 0.0. E = 2.07 10 11 N/m 2

More information

Preliminary Experiences with the Uintah Framework on on Intel Xeon Phi and Stampede

Preliminary Experiences with the Uintah Framework on on Intel Xeon Phi and Stampede Preliminary Experiences with the Uintah Framework on on Intel Xeon Phi and Stampede Qingyu Meng, Alan Humphrey, John Schmidt, Martin Berzins Thanks to: TACC Team for early access to Stampede J. Davison

More information

Voronoi Diagram. Xiao-Ming Fu

Voronoi Diagram. Xiao-Ming Fu Voronoi Diagram Xiao-Ming Fu Outlines Introduction Post Office Problem Voronoi Diagram Duality: Delaunay triangulation Centroidal Voronoi tessellations (CVT) Definition Applications Algorithms Outlines

More information

Metafor FE Software. 2. Operator split. 4. Rezoning methods 5. Contact with friction

Metafor FE Software. 2. Operator split. 4. Rezoning methods 5. Contact with friction ALE simulations ua sus using Metafor eao 1. Introduction 2. Operator split 3. Convection schemes 4. Rezoning methods 5. Contact with friction 1 Introduction EULERIAN FORMALISM Undistorted mesh Ideal for

More information

Enzo-P / Cello. Scalable Adaptive Mesh Refinement for Astrophysics and Cosmology. San Diego Supercomputer Center. Department of Physics and Astronomy

Enzo-P / Cello. Scalable Adaptive Mesh Refinement for Astrophysics and Cosmology. San Diego Supercomputer Center. Department of Physics and Astronomy Enzo-P / Cello Scalable Adaptive Mesh Refinement for Astrophysics and Cosmology James Bordner 1 Michael L. Norman 1 Brian O Shea 2 1 University of California, San Diego San Diego Supercomputer Center 2

More information

Direct Rendering. Direct Rendering Goals

Direct Rendering. Direct Rendering Goals May 2, 2005 Goals General Goals Small memory footprint Fast rendering High-quality results identical to those of Saffron V1 using distance-based anti-aliasing and alignment zones Goals Specific Goals Avoid

More information

Compressible Flow in a Nozzle

Compressible Flow in a Nozzle SPC 407 Supersonic & Hypersonic Fluid Dynamics Ansys Fluent Tutorial 1 Compressible Flow in a Nozzle Ahmed M Nagib Elmekawy, PhD, P.E. Problem Specification Consider air flowing at high-speed through a

More information

iric Software Changing River Science River2D Tutorials

iric Software Changing River Science River2D Tutorials iric Software Changing River Science River2D Tutorials iric Software Changing River Science Confluence of the Colorado River, Blue River and Indian Creek, Colorado, USA 1 TUTORIAL 1: RIVER2D STEADY SOLUTION

More information

NOISE PROPAGATION FROM VIBRATING STRUCTURES

NOISE PROPAGATION FROM VIBRATING STRUCTURES NOISE PROPAGATION FROM VIBRATING STRUCTURES Abstract R. Helfrich, M. Spriegel (INTES GmbH, Germany) Noise and noise exposure are becoming more important in product development due to environmental legislation.

More information

Performance of the hybrid MPI/OpenMP version of the HERACLES code on the Curie «Fat nodes» system

Performance of the hybrid MPI/OpenMP version of the HERACLES code on the Curie «Fat nodes» system Performance of the hybrid MPI/OpenMP version of the HERACLES code on the Curie «Fat nodes» system Edouard Audit, Matthias Gonzalez, Pierre Kestener and Pierre-François Lavallé The HERACLES code Fixed grid

More information

ECG782: Multidimensional Digital Signal Processing

ECG782: Multidimensional Digital Signal Processing Professor Brendan Morris, SEB 3216, brendan.morris@unlv.edu ECG782: Multidimensional Digital Signal Processing Spring 2014 TTh 14:30-15:45 CBC C313 Lecture 10 Segmentation 14/02/27 http://www.ee.unlv.edu/~b1morris/ecg782/

More information

SolidWorks Flow Simulation 2014

SolidWorks Flow Simulation 2014 An Introduction to SolidWorks Flow Simulation 2014 John E. Matsson, Ph.D. SDC PUBLICATIONS Better Textbooks. Lower Prices. www.sdcpublications.com Powered by TCPDF (www.tcpdf.org) Visit the following websites

More information

An In-place Algorithm for Irregular All-to-All Communication with Limited Memory

An In-place Algorithm for Irregular All-to-All Communication with Limited Memory An In-place Algorithm for Irregular All-to-All Communication with Limited Memory Michael Hofmann and Gudula Rünger Department of Computer Science Chemnitz University of Technology, Germany {mhofma,ruenger}@cs.tu-chemnitz.de

More information

FLUID SIMULATION. Kristofer Schlachter

FLUID SIMULATION. Kristofer Schlachter FLUID SIMULATION Kristofer Schlachter The Equations Incompressible Navier-Stokes: @u @t = (r u)u 1 rp + vr2 u + F Incompressibility condition r u =0 Breakdown @u @t The derivative of velocity with respect

More information

Verification and Validation in CFD and Heat Transfer: ANSYS Practice and the New ASME Standard

Verification and Validation in CFD and Heat Transfer: ANSYS Practice and the New ASME Standard Verification and Validation in CFD and Heat Transfer: ANSYS Practice and the New ASME Standard Dimitri P. Tselepidakis & Lewis Collins ASME 2012 Verification and Validation Symposium May 3 rd, 2012 1 Outline

More information