PyFR: Bringing Next Generation Computational Fluid Dynamics to GPU Platforms
|
|
- Darleen McCormick
- 8 years ago
- Views:
Transcription
1 PyFR: Bringing Next Generation Computational Fluid Dynamics to GPU Platforms P. E. Vincent! Department of Aeronautics Imperial College London! 25 th March 2014
2 Overview Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary
3 Motivation Current industry standard CFD tools have limited capabilities
4 Motivation Technology is decades old and designed for solving steady flow problems (using RANS approach)
5 Motivation Technology is decades old and designed for solving steady flow problems (using RANS approach)
6 Motivation Need to expand the industrial CFD envelope
7 Motivation Its not just me who thinks this [1]! [1] Murray Cross, Airbus, Technology Product Leader - Future Simulations (2012)
8 Motivation Objective of our research is to advance industrial CFD capabilities from their current RANS plateau
9 Motivation We aim to develop the de facto industry standard technology for affordable (and hence industrially relevant) high-fidelity scale-resolving simulations of unsteady flow phenomena within the vicinity of complex geometric configurations
10 Motivation Achieved by intelligently leveraging benefits of (and synergies between) high-order Flux Reconstruction (FR) methods for unstructured grids and massively-parallel Many-Core Hardware platforms
11 Motivation Flux Reconstruction + Many-Core Hardware
12 Flux Reconstruction Flux Reconstruction (FR) approach to high-order methods was first proposed by Huynh in 2007 [2] High-order accurate in space Works on unstructured grids [2] H. T. Huynh. A flux reconstruction approach to high-order schemes including discontinuous Galerkin methods. AIAA Paper
13 Flux Reconstruction What does high-order mean?
14 Flux Reconstruction What does high-order mean? Order N accuracy implies error of order h N High-order typically refers to N > 2
15 Flux Reconstruction Why is high-order useful?
16 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 0 t = 0
17 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 0 t = 0
18 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 1 t = 1
19 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 2 t = 2
20 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 3 t = 3
21 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 4 t = 4
22 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 5 t = 5
23 Motivation Introduction Flux Theory Reconstruction PyFR Results Many-Core Summary Hardware PyFR Results Summary Flux Introduction Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 20 t = 20
24 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 40 t = 40
25 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 60 t = 60
26 Flux Reconstruction Why is high-order useful? 2 nd Order (25,600 DOF) 4 th Order (25,600 DOF) t = 180 t = 180
27 Flux Reconstruction What does unstructured mean?
28 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 0 t = 0
29 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 1 t = 1
30 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 2 t = 2
31 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 3 t = 3
32 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 4 t = 4
33 Flux Reconstruction What does unstructured mean? Unstructured 4th Order Structured 4th Order t = 5 t = 5
34 Flux Reconstruction Why is unstructured useful?
35 Flux Reconstruction Why is unstructured useful?
36 Flux Reconstruction Also Unifying (can cast various known + new schemes within FR framework) Significant element locality Abundance of structured compute
37 Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary Many-Core Hardware Multi-core CPUs now ubiquitous (with 10 s of cores per device)
38 Many-Core Hardware Many-core accelerators a hot topic (100s -1000s cores per device) Nvidia K40
39 Many-Core Hardware Many-core accelerators a hot topic (100s -1000s cores per device) Nvidia K40 Intel Phi AMD S10000
40 Many-Core Hardware Rapid evolution of hardware Need to exploit massive parallelism Temporal and spatial data locality is important Limited memory per device Exposed to complex memory hierarchy
41 Many-Core Hardware So, several challenges...
42 Many-Core Hardware But significant compute available if it can be harnessed
43 PyFR Flux Reconstruction PyFR + Many-Core Hardware
44 PyFR Features (v current stable release) Governing Equations Spatial Discretisation Compressible Euler Compressible Navier Stokes Arbitrary order FR on mixed unstructured grids (tris, quads, hexes) Temporal Discretisation Range of explicit Runge-Kutta schemes Platforms Precision Input Output CPU clusters (C-OpenMP-MPI) Nvidia GPU clusters (CUDA-MPI) Single Double Gmsh Paraview
45 PyFR Python Outer Layer (Hardware Independent) Python Outer Layer (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels
46 PyFR Need to generate the Hardware Specific Kernels Python Outer Layer (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels
47 PyFR Templated Kernels (Hardware Independent) Python Outer Layer (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels Templated Kernels (Hardware Independent) Point-wise non-linear kernels (flux function, Riemann solver) Matrix multiply kernels
48 PyFR Passed through Mako Derived Templating Engine Python Outer Layer (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels Templated Kernels (Hardware Independent) Point-wise non-linear kernels (flux function, Riemann solver) Matrix multiply kernels Mako Derived Templating Engine Generates hardware specific kernel code Deals with device level parallelism
49 Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary PyFR Generates Hardware Specific Kernels Python Outer Layer (Hardware Independent) Templated Kernels (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels C/OpenMP Hardware Specific Kernels CUDA Hardware Specific Kernels Point-wise non-linear kernels (flux function, Riemann solver) Matrix multiply kernels OpenCL Hardware Specific Kernels Mako Derived Templating Engine Generates hardware specific kernel code Deals with device level parallelism
50 Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary PyFR These can now be called Python Outer Layer (Hardware Independent) Templated Kernels (Hardware Independent) Setup Distributed memory parallelism Outer for loop and calls to Hardware Specific Kernels C/OpenMP Hardware Specific Kernels CUDA Hardware Specific Kernels Point-wise non-linear kernels (flux function, Riemann solver) Matrix multiply kernels OpenCL Hardware Specific Kernels Mako Derived Templating Engine Generates hardware specific kernel code Deals with device level parallelism
51 PyFR ~5,000 lines of code
52 PyFR Speed critical kernel is sgemm/dgemm In first instance we can drop in vendor BLAS (cublas etc.) But can we do better than this
53 Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary Results Unstructured 5th orderataccurate Macurved = 0.2inRe element space = 3900 hexahedral mesh Cylinder
54 Results T106c turbine blade Ma = 0.65 Re = 80,000
55 Results Unstructured curved element hexahedral mesh
56 Results 4th order accurate in space
57 Results Good agreement with experimental data Isentropic Mach Number Chord
58 Results c.f. RANS result from leading commercial software Isentropic Mach Number Chord
59 Results Double ~500,000 1x10 4th Unstructured Flow ~100 order over hours precision RK4 accurate a deployed hexahedral time-steps 4 x K20c in spoiler space GPUs meshma in = a desktop 0.3 Re = workstation 10,000
60 Results 3D Navier-Stokes weak scaling over M2090s (Emerald) PyFR Ideal
61 Results 3D Navier-Stokes strong scaling over M2090s (Emerald) PyFR Ideal
62 Motivation Flux Reconstruction Many-Core Hardware PyFR Results Summary Results 1.3 billion DOF on 184 x M2090 GPUs (Emerald)
63 Summary Objective of research is to advance industrial CFD capabilities from their current RANS plateau
64 Summary We aim to develop the de facto industry standard technology for affordable (and hence industrially relevant) high-fidelity scale-resolving simulations of unsteady flow phenomena within the vicinity of complex geometric configurations
65 Summary Achieved by intelligently leveraging benefits of (and synergies between) High-Order Flux Reconstruction (FR) methods for unstructured grids and massively-parallel Many-Core Hardware platforms
66 Summary Web:
67 PhD Students Freddie Witherden (Imperial College) Antony Farrington (Imperial College) George Ntemos (Imperial College) Harry Davis (Imperial College)
68 Emerald The authors would like to acknowledge the work presented here made use of the EMERALD HPC facility provided by the Centre for Innovation
69 Funding Early Career Fellowship Platform Grant UK Turbulence Consortium 4 x PhD Studentships Hardware Donations
70 Questions Web:
Imperial College London
Imperial College London Department of Computing GiMMiK - Generating Bespoke Matrix Multiplication Kernels for Various Hardware Accelerators; Applications in High-Order Computational Fluid Dynamics Author:
More informationTurbomachinery CFD on many-core platforms experiences and strategies
Turbomachinery CFD on many-core platforms experiences and strategies Graham Pullan Whittle Laboratory, Department of Engineering, University of Cambridge MUSAF Colloquium, CERFACS, Toulouse September 27-29
More informationGPU System Architecture. Alan Gray EPCC The University of Edinburgh
GPU System Architecture EPCC The University of Edinburgh Outline Why do we want/need accelerators such as GPUs? GPU-CPU comparison Architectural reasons for GPU performance advantages GPU accelerated systems
More informationAccelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing
Accelerating Simulation & Analysis with Hybrid GPU Parallelization and Cloud Computing Innovation Intelligence Devin Jensen August 2012 Altair Knows HPC Altair is the only company that: makes HPC tools
More informationAccelerating CFD using OpenFOAM with GPUs
Accelerating CFD using OpenFOAM with GPUs Authors: Saeed Iqbal and Kevin Tubbs The OpenFOAM CFD Toolbox is a free, open source CFD software package produced by OpenCFD Ltd. Its user base represents a wide
More informationOptimizing a 3D-FWT code in a cluster of CPUs+GPUs
Optimizing a 3D-FWT code in a cluster of CPUs+GPUs Gregorio Bernabé Javier Cuenca Domingo Giménez Universidad de Murcia Scientific Computing and Parallel Programming Group XXIX Simposium Nacional de la
More informationComputational Modeling of Wind Turbines in OpenFOAM
Computational Modeling of Wind Turbines in OpenFOAM Hamid Rahimi hamid.rahimi@uni-oldenburg.de ForWind - Center for Wind Energy Research Institute of Physics, University of Oldenburg, Germany Outline Computational
More informationGPU Acceleration of the SENSEI CFD Code Suite
GPU Acceleration of the SENSEI CFD Code Suite Chris Roy, Brent Pickering, Chip Jackson, Joe Derlaga, Xiao Xu Aerospace and Ocean Engineering Primary Collaborators: Tom Scogland, Wu Feng (Computer Science)
More informationC3.8 CRM wing/body Case
C3.8 CRM wing/body Case 1. Code description XFlow is a high-order discontinuous Galerkin (DG) finite element solver written in ANSI C, intended to be run on Linux-type platforms. Relevant supported equation
More information2013 Code_Saturne User Group Meeting. EDF R&D Chatou, France. 9 th April 2013
2013 Code_Saturne User Group Meeting EDF R&D Chatou, France 9 th April 2013 Thermal Comfort in Train Passenger Cars Contact For further information please contact: Brian ANGEL Director RENUDA France brian.angel@renuda.com
More informationAerodynamic Department Institute of Aviation. Adam Dziubiński CFD group FLUENT
Adam Dziubiński CFD group IoA FLUENT Content Fluent CFD software 1. Short description of main features of Fluent 2. Examples of usage in CESAR Analysis of flow around an airfoil with a flap: VZLU + ILL4xx
More informationHPC Deployment of OpenFOAM in an Industrial Setting
HPC Deployment of OpenFOAM in an Industrial Setting Hrvoje Jasak h.jasak@wikki.co.uk Wikki Ltd, United Kingdom PRACE Seminar: Industrial Usage of HPC Stockholm, Sweden, 28-29 March 2011 HPC Deployment
More informationBBIPED: BCAM-Baltogar Industrial Platform for Engineering design
BBIPED: BCAM-Baltogar Industrial Platform for Engineering design Carmen Alonso-Montes, Imanol García, Ali Ramezani, Lakhdar Remaki BCAM Basque Center for Applied Mathematics (Bilbao), Spain Motivation
More informationHigh Performance Computing in CST STUDIO SUITE
High Performance Computing in CST STUDIO SUITE Felix Wolfheimer GPU Computing Performance Speedup 18 16 14 12 10 8 6 4 2 0 Promo offer for EUC participants: 25% discount for K40 cards Speedup of Solver
More informationHIGH PERFORMANCE CONSULTING COURSE OFFERINGS
Performance 1(6) HIGH PERFORMANCE CONSULTING COURSE OFFERINGS LEARN TO TAKE ADVANTAGE OF POWERFUL GPU BASED ACCELERATOR TECHNOLOGY TODAY 2006 2013 Nvidia GPUs Intel CPUs CONTENTS Acronyms and Terminology...
More informationGraphical Processing Units to Accelerate Orthorectification, Atmospheric Correction and Transformations for Big Data
Graphical Processing Units to Accelerate Orthorectification, Atmospheric Correction and Transformations for Big Data Amanda O Connor, Bryan Justice, and A. Thomas Harris IN52A. Big Data in the Geosciences:
More informationNext Generation GPU Architecture Code-named Fermi
Next Generation GPU Architecture Code-named Fermi The Soul of a Supercomputer in the Body of a GPU Why is NVIDIA at Super Computing? Graphics is a throughput problem paint every pixel within frame time
More informationHPC Wales Skills Academy Course Catalogue 2015
HPC Wales Skills Academy Course Catalogue 2015 Overview The HPC Wales Skills Academy provides a variety of courses and workshops aimed at building skills in High Performance Computing (HPC). Our courses
More informationDesign and Optimization of a Portable Lattice Boltzmann Code for Heterogeneous Architectures
Design and Optimization of a Portable Lattice Boltzmann Code for Heterogeneous Architectures E Calore, S F Schifano, R Tripiccione Enrico Calore INFN Ferrara, Italy Perspectives of GPU Computing in Physics
More informationA GPU COMPUTING PLATFORM (SAGA) AND A CFD CODE ON GPU FOR AEROSPACE APPLICATIONS
A GPU COMPUTING PLATFORM (SAGA) AND A CFD CODE ON GPU FOR AEROSPACE APPLICATIONS SUDHAKARAN.G APCF, AERO, VSSC, ISRO 914712564742 g_suhakaran@vssc.gov.in THOMAS.C.BABU APCF, AERO, VSSC, ISRO 914712565833
More informationXFlow CFD results for the 1st AIAA High Lift Prediction Workshop
XFlow CFD results for the 1st AIAA High Lift Prediction Workshop David M. Holman, Dr. Monica Mier-Torrecilla, Ruddy Brionnaud Next Limit Technologies, Spain THEME Computational Fluid Dynamics KEYWORDS
More informationGPGPU accelerated Computational Fluid Dynamics
t e c h n i s c h e u n i v e r s i t ä t b r a u n s c h w e i g Carl-Friedrich Gauß Faculty GPGPU accelerated Computational Fluid Dynamics 5th GACM Colloquium on Computational Mechanics Hamburg Institute
More informationThe Value of High-Performance Computing for Simulation
White Paper The Value of High-Performance Computing for Simulation High-performance computing (HPC) is an enormous part of the present and future of engineering simulation. HPC allows best-in-class companies
More informationMedical Image Processing on the GPU. Past, Present and Future. Anders Eklund, PhD Virginia Tech Carilion Research Institute andek@vtc.vt.
Medical Image Processing on the GPU Past, Present and Future Anders Eklund, PhD Virginia Tech Carilion Research Institute andek@vtc.vt.edu Outline Motivation why do we need GPUs? Past - how was GPU programming
More informationPerformance Comparison of a Vertical Axis Wind Turbine using Commercial and Open Source Computational Fluid Dynamics based Codes
Performance Comparison of a Vertical Axis Wind Turbine using Commercial and Open Source Computational Fluid Dynamics based Codes Taimoor Asim 1, Rakesh Mishra 1, Sree Nirjhor Kaysthagir 1, Ghada Aboufares
More informationProgramming models for heterogeneous computing. Manuel Ujaldón Nvidia CUDA Fellow and A/Prof. Computer Architecture Department University of Malaga
Programming models for heterogeneous computing Manuel Ujaldón Nvidia CUDA Fellow and A/Prof. Computer Architecture Department University of Malaga Talk outline [30 slides] 1. Introduction [5 slides] 2.
More informationME6130 An introduction to CFD 1-1
ME6130 An introduction to CFD 1-1 What is CFD? Computational fluid dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically
More informationA Load Balancing Tool for Structured Multi-Block Grid CFD Applications
A Load Balancing Tool for Structured Multi-Block Grid CFD Applications K. P. Apponsah and D. W. Zingg University of Toronto Institute for Aerospace Studies (UTIAS), Toronto, ON, M3H 5T6, Canada Email:
More informationCurrent Status and Challenges in CFD at the DLR Institute of Aerodynamics and Flow Technology
Current Status and Challenges in CFD at the DLR Institute of Aerodynamics and Flow Technology N. Kroll, C.-C. Rossow DLR, Institute of Aerodynamics and Flow Technology DLR Institute of Aerodynamics and
More informationHardware-Aware Analysis and. Presentation Date: Sep 15 th 2009 Chrissie C. Cui
Hardware-Aware Analysis and Optimization of Stable Fluids Presentation Date: Sep 15 th 2009 Chrissie C. Cui Outline Introduction Highlights Flop and Bandwidth Analysis Mehrstellen Schemes Advection Caching
More informationDesign and Optimization of OpenFOAM-based CFD Applications for Hybrid and Heterogeneous HPC Platforms
Design and Optimization of OpenFOAM-based CFD Applications for Hybrid and Heterogeneous HPC Platforms Amani AlOnazi, David E. Keyes, Alexey Lastovetsky, Vladimir Rychkov Extreme Computing Research Center,
More informationMultiphase Flow - Appendices
Discovery Laboratory Multiphase Flow - Appendices 1. Creating a Mesh 1.1. What is a geometry? The geometry used in a CFD simulation defines the problem domain and boundaries; it is the area (2D) or volume
More informationExperiences Extending the CFD Solver of the PDE Framework Peano
Experiences Extending the CFD Solver of the PDE Framework Peano T. Neckel, M. Lieb, R. Sangl TUM, Department of Informatics, Chair of Scientific Computing in Computer Science P. Schoeffel, F. Weyermann
More informationTHE CFD SIMULATION OF THE FLOW AROUND THE AIRCRAFT USING OPENFOAM AND ANSA
THE CFD SIMULATION OF THE FLOW AROUND THE AIRCRAFT USING OPENFOAM AND ANSA Adam Kosík Evektor s.r.o., Czech Republic KEYWORDS CFD simulation, mesh generation, OpenFOAM, ANSA ABSTRACT In this paper we describe
More informationCFD Applications using CFD++ Paul Batten & Vedat Akdag
CFD Applications using CFD++ Paul Batten & Vedat Akdag Metacomp Products available under Altair Partner Program CFD++ Introduction Accurate multi dimensional polynomial framework Robust on wide variety
More informationSimulation Platform Overview
Simulation Platform Overview Build, compute, and analyze simulations on demand www.rescale.com CASE STUDIES Companies in the aerospace and automotive industries use Rescale to run faster simulations Aerospace
More informationwww.xenon.com.au STORAGE HIGH SPEED INTERCONNECTS HIGH PERFORMANCE COMPUTING VISUALISATION GPU COMPUTING
www.xenon.com.au STORAGE HIGH SPEED INTERCONNECTS HIGH PERFORMANCE COMPUTING GPU COMPUTING VISUALISATION XENON Accelerating Exploration Mineral, oil and gas exploration is an expensive and challenging
More informationRecent Advances in HPC for Structural Mechanics Simulations
Recent Advances in HPC for Structural Mechanics Simulations 1 Trends in Engineering Driving Demand for HPC Increase product performance and integrity in less time Consider more design variants Find the
More informationAeroFluidX: A Next Generation GPU-Based CFD Solver for Engineering Applications
AeroFluidX: A Next Generation GPU-Based CFD Solver for Engineering Applications Dr. Bjoern Landmann Dr. Kerstin Wieczorek Stefan Bachschuster 18.03.2015 FluiDyna GmbH, Lichtenbergstr. 8, 85748 Garching
More informationHPC with Multicore and GPUs
HPC with Multicore and GPUs Stan Tomov Electrical Engineering and Computer Science Department University of Tennessee, Knoxville CS 594 Lecture Notes March 4, 2015 1/18 Outline! Introduction - Hardware
More informationNumerical simulation of maneuvering combat aircraft
Numerical simulation of maneuvering combat aircraft Andreas Schütte DLR - German Aerospace Center Institute of Aerodynamics and Flow Technology Oct. 14 th 2005, Stuttgart Folie 1 > HLRS 2005 > A. Schütte
More informationFINE TM /Marine. CFD Suite for Marine Applications. Advanced Development for Better Products. www.numeca.com
FINE TM /Marine CFD Suite for Marine Applications Advanced Development for Better Products www.numeca.com FINE TM /Marine FINE /Marine is a unique integrated CFD software environment for the simulation
More informationThe Influence of Aerodynamics on the Design of High-Performance Road Vehicles
The Influence of Aerodynamics on the Design of High-Performance Road Vehicles Guido Buresti Department of Aerospace Engineering University of Pisa (Italy) 1 CONTENTS ELEMENTS OF AERODYNAMICS AERODYNAMICS
More informationTitelmasterformat durch Klicken bearbeiten
Titelmasterformat durch Klicken bearbeiten ANSYS AIM Product simulation for every engineer Erke Wang CADFEM GmbH Georg Scheuerer ANSYS Germany GmbH Christof Gebhardt CADFEM GmbH All products involve multiple
More informationHow To Write A Program For The Pd Framework
Enhanced divergence-free elements for efficient incompressible flow simulations in the PDE framework Peano, Miriam Mehl, Christoph Zenger, Fakultät für Informatik TU München Germany Outline Derivation
More informationO.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM. Darmstadt, 27.06.2012
O.F.Wind Wind Site Assessment Simulation in complex terrain based on OpenFOAM Darmstadt, 27.06.2012 Michael Ehlen IB Fischer CFD+engineering GmbH Lipowskystr. 12 81373 München Tel. 089/74118743 Fax 089/74118749
More informationIntroduction to GP-GPUs. Advanced Computer Architectures, Cristina Silvano, Politecnico di Milano 1
Introduction to GP-GPUs Advanced Computer Architectures, Cristina Silvano, Politecnico di Milano 1 GPU Architectures: How do we reach here? NVIDIA Fermi, 512 Processing Elements (PEs) 2 What Can It Do?
More informationCFD Lab Department of Engineering The University of Liverpool
Development of a CFD Method for Aerodynamic Analysis of Large Diameter Horizontal Axis wind turbines S. Gomez-Iradi, G.N. Barakos and X. Munduate 2007 joint meeting of IEA Annex 11 and Annex 20 Risø National
More informationPushing the limits. Turbine simulation for next-generation turbochargers
Pushing the limits Turbine simulation for next-generation turbochargers KWOK-KAI SO, BENT PHILLIPSEN, MAGNUS FISCHER Computational fluid dynamics (CFD) has matured and is now an indispensable tool for
More informationExtension of the OpenFOAM CFD tool set for modelling multiphase flow
Extension of the OpenFOAM CFD tool set for modelling multiphase flow Ridhwaan Suliman Johan Heyns Oliver Oxtoby Advanced Computational Methods Research Group, CSIR South Africa CHPC National Meeting, Durban,
More informationPart I Courses Syllabus
Part I Courses Syllabus This document provides detailed information about the basic courses of the MHPC first part activities. The list of courses is the following 1.1 Scientific Programming Environment
More informationExperiences on using GPU accelerators for data analysis in ROOT/RooFit
Experiences on using GPU accelerators for data analysis in ROOT/RooFit Sverre Jarp, Alfio Lazzaro, Julien Leduc, Yngve Sneen Lindal, Andrzej Nowak European Organization for Nuclear Research (CERN), Geneva,
More informationWrite a technical report Present your results Write a workshop/conference paper (optional) Could be a real system, simulation and/or theoretical
Identify a problem Review approaches to the problem Propose a novel approach to the problem Define, design, prototype an implementation to evaluate your approach Could be a real system, simulation and/or
More informationEnterprise HPC & Cloud Computing for Engineering Simulation. Barbara Hutchings Director, Strategic Partnerships ANSYS, Inc.
Enterprise HPC & Cloud Computing for Engineering Simulation Barbara Hutchings Director, Strategic Partnerships ANSYS, Inc. Historical Perspective Evolution of Computing for Simulation Pendulum swing: Centralized
More informationAerodynamic Simulation. Viscous CFD Code Validation
Aerodynamic Simulation using STAR-CCM+ Viscous CFD Code Validation 19 March 2013 CD-adapco STAR-CCM+ Code Validation Efforts Kenneth E. Xiques CRM Solutions 4092 Memorial Pkwy SW, Suite 200 Huntsville,
More informationExpress Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology
Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology Dimitrios Sofialidis Technical Manager, SimTec Ltd. Mechanical Engineer, PhD PRACE Autumn School 2013 - Industry
More informationModeling Rotor Wakes with a Hybrid OVERFLOW-Vortex Method on a GPU Cluster
Modeling Rotor Wakes with a Hybrid OVERFLOW-Vortex Method on a GPU Cluster Mark J. Stock, Ph.D., Adrin Gharakhani, Sc.D. Applied Scientific Research, Santa Ana, CA Christopher P. Stone, Ph.D. Computational
More informationwalberla: A software framework for CFD applications on 300.000 Compute Cores
walberla: A software framework for CFD applications on 300.000 Compute Cores J. Götz (LSS Erlangen, jan.goetz@cs.fau.de), K. Iglberger, S. Donath, C. Feichtinger, U. Rüde Lehrstuhl für Informatik 10 (Systemsimulation)
More informationAdvanced discretisation techniques (a collection of first and second order schemes); Innovative algorithms and robust solvers for fast convergence.
New generation CFD Software APUS-CFD APUS-CFD is a fully interactive Arbitrary Polyhedral Unstructured Solver. APUS-CFD is a new generation of CFD software for modelling fluid flow and heat transfer in
More informationACCELERATING COMMERCIAL LINEAR DYNAMIC AND NONLINEAR IMPLICIT FEA SOFTWARE THROUGH HIGH- PERFORMANCE COMPUTING
ACCELERATING COMMERCIAL LINEAR DYNAMIC AND Vladimir Belsky Director of Solver Development* Luis Crivelli Director of Solver Development* Matt Dunbar Chief Architect* Mikhail Belyi Development Group Manager*
More informationFrom CFD to computational finance (and back again?)
computational finance p. 1/17 From CFD to computational finance (and back again?) Mike Giles mike.giles@maths.ox.ac.uk Oxford University Mathematical Institute Oxford-Man Institute of Quantitative Finance
More information5x in 5 hours Porting SEISMIC_CPML using the PGI Accelerator Model
5x in 5 hours Porting SEISMIC_CPML using the PGI Accelerator Model C99, C++, F2003 Compilers Optimizing Vectorizing Parallelizing Graphical parallel tools PGDBG debugger PGPROF profiler Intel, AMD, NVIDIA
More informationComputational Fluid Dynamics in Automotive Applications
Computational Fluid Dynamics in Automotive Applications Hrvoje Jasak h.jasak@wikki.co.uk Wikki Ltd, United Kingdom FSB, University of Zagreb, Croatia 1/15 Outline Objective Review the adoption of Computational
More informationComputational Fluid Dynamics Research Projects at Cenaero (2011)
Computational Fluid Dynamics Research Projects at Cenaero (2011) Cenaero (www.cenaero.be) is an applied research center focused on the development of advanced simulation technologies for aeronautics. Located
More informationGraphical Processing Units to Accelerate Orthorectification, Atmospheric Correction and Transformations for Big Data
Graphical Processing Units to Accelerate Orthorectification, Atmospheric Correction and Transformations for Big Data Amanda O Connor, Bryan Justice, and A. Thomas Harris IN52A. Big Data in the Geosciences:
More informationStream Processing on GPUs Using Distributed Multimedia Middleware
Stream Processing on GPUs Using Distributed Multimedia Middleware Michael Repplinger 1,2, and Philipp Slusallek 1,2 1 Computer Graphics Lab, Saarland University, Saarbrücken, Germany 2 German Research
More informationUnleashing the Performance Potential of GPUs for Atmospheric Dynamic Solvers
Unleashing the Performance Potential of GPUs for Atmospheric Dynamic Solvers Haohuan Fu haohuan@tsinghua.edu.cn High Performance Geo-Computing (HPGC) Group Center for Earth System Science Tsinghua University
More informationEvaluation of CUDA Fortran for the CFD code Strukti
Evaluation of CUDA Fortran for the CFD code Strukti Practical term report from Stephan Soller High performance computing center Stuttgart 1 Stuttgart Media University 2 High performance computing center
More informationNVIDIA CUDA GETTING STARTED GUIDE FOR MICROSOFT WINDOWS
NVIDIA CUDA GETTING STARTED GUIDE FOR MICROSOFT WINDOWS DU-05349-001_v6.0 February 2014 Installation and Verification on TABLE OF CONTENTS Chapter 1. Introduction...1 1.1. System Requirements... 1 1.2.
More informationCFD analysis for road vehicles - case study
CFD analysis for road vehicles - case study Dan BARBUT*,1, Eugen Mihai NEGRUS 1 *Corresponding author *,1 POLITEHNICA University of Bucharest, Faculty of Transport, Splaiul Independentei 313, 060042, Bucharest,
More informationOverview of HPC Resources at Vanderbilt
Overview of HPC Resources at Vanderbilt Will French Senior Application Developer and Research Computing Liaison Advanced Computing Center for Research and Education June 10, 2015 2 Computing Resources
More informationCooling and thermal efficiently in
Cooling and thermal efficiently in the datacentre George Brown HPC Systems Engineer Viglen Overview Viglen Overview Products and Technologies Looking forward Company Profile IT hardware manufacture, reseller
More informationMONTE-CARLO SIMULATION OF AMERICAN OPTIONS WITH GPUS. Julien Demouth, NVIDIA
MONTE-CARLO SIMULATION OF AMERICAN OPTIONS WITH GPUS Julien Demouth, NVIDIA STAC-A2 BENCHMARK STAC-A2 Benchmark Developed by banks Macro and micro, performance and accuracy Pricing and Greeks for American
More informationTrends in High-Performance Computing for Power Grid Applications
Trends in High-Performance Computing for Power Grid Applications Franz Franchetti ECE, Carnegie Mellon University www.spiral.net Co-Founder, SpiralGen www.spiralgen.com This talk presents my personal views
More informationComputational Fluid Dynamics. Department of Aerospace Engineering, IIT Bombay
Computational Fluid Dynamics Department of Aerospace Engineering, IIT Bombay Expertise Core CFD and CEM Algorithm development Hypersonics, internal and external flows Grid generation: IITZeus Particle
More informationGPU Hardware and Programming Models. Jeremy Appleyard, September 2015
GPU Hardware and Programming Models Jeremy Appleyard, September 2015 A brief history of GPUs In this talk Hardware Overview Programming Models Ask questions at any point! 2 A Brief History of GPUs 3 Once
More informationCFD modelling of floating body response to regular waves
CFD modelling of floating body response to regular waves Dr Yann Delauré School of Mechanical and Manufacturing Engineering Dublin City University Ocean Energy Workshop NUI Maynooth, October 21, 2010 Table
More informationCustomer Training Material. Lecture 2. Introduction to. Methodology ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved.
Lecture 2 Introduction to CFD Methodology Introduction to ANSYS FLUENT L2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions,
More informationHigh Performance. CAEA elearning Series. Jonathan G. Dudley, Ph.D. 06/09/2015. 2015 CAE Associates
High Performance Computing (HPC) CAEA elearning Series Jonathan G. Dudley, Ph.D. 06/09/2015 2015 CAE Associates Agenda Introduction HPC Background Why HPC SMP vs. DMP Licensing HPC Terminology Types of
More informationFire Simulations in Civil Engineering
Contact: Lukas Arnold l.arnold@fz- juelich.de Nb: I had to remove slides containing input from our industrial partners. Sorry. Fire Simulations in Civil Engineering 07.05.2013 Lukas Arnold Fire Simulations
More informationAcceleration of a CFD Code with a GPU
Acceleration of a CFD Code with a GPU Dennis C. Jespersen ABSTRACT The Computational Fluid Dynamics code Overflow includes as one of its solver options an algorithm which is a fairly small piece of code
More informationCase Study on Productivity and Performance of GPGPUs
Case Study on Productivity and Performance of GPGPUs Sandra Wienke wienke@rz.rwth-aachen.de ZKI Arbeitskreis Supercomputing April 2012 Rechen- und Kommunikationszentrum (RZ) RWTH GPU-Cluster 56 Nvidia
More informationMarine CFD applications using OpenFOAM
Marine CFD applications using OpenFOAM Andrea Penza, CINECA 27/03/2014 Contents Background at CINECA: LRC experience CFD skills Automatic workflow Reliability workflow OpenFOAM solvers for marine CFD analysis
More informationComputational Fluid Dynamics
Aerodynamics Computational Fluid Dynamics Industrial Use of High Fidelity Numerical Simulation of Flow about Aircraft Presented by Dr. Klaus Becker / Aerodynamic Strategies Contents Aerodynamic Vision
More informationGPU File System Encryption Kartik Kulkarni and Eugene Linkov
GPU File System Encryption Kartik Kulkarni and Eugene Linkov 5/10/2012 SUMMARY. We implemented a file system that encrypts and decrypts files. The implementation uses the AES algorithm computed through
More informationIntroduction to CFD Analysis
Introduction to CFD Analysis 2-1 What is CFD? Computational Fluid Dynamics (CFD) is the science of predicting fluid flow, heat and mass transfer, chemical reactions, and related phenomena by solving numerically
More informationMixed Precision Iterative Refinement Methods Energy Efficiency on Hybrid Hardware Platforms
Mixed Precision Iterative Refinement Methods Energy Efficiency on Hybrid Hardware Platforms Björn Rocker Hamburg, June 17th 2010 Engineering Mathematics and Computing Lab (EMCL) KIT University of the State
More informationIntroduction GPU Hardware GPU Computing Today GPU Computing Example Outlook Summary. GPU Computing. Numerical Simulation - from Models to Software
GPU Computing Numerical Simulation - from Models to Software Andreas Barthels JASS 2009, Course 2, St. Petersburg, Russia Prof. Dr. Sergey Y. Slavyanov St. Petersburg State University Prof. Dr. Thomas
More informationABSTRACT FOR THE 1ST INTERNATIONAL WORKSHOP ON HIGH ORDER CFD METHODS
1 ABSTRACT FOR THE 1ST INTERNATIONAL WORKSHOP ON HIGH ORDER CFD METHODS Sreenivas Varadan a, Kentaro Hara b, Eric Johnsen a, Bram Van Leer b a. Department of Mechanical Engineering, University of Michigan,
More informationCFD Based Air Flow and Contamination Modeling of Subway Stations
CFD Based Air Flow and Contamination Modeling of Subway Stations Greg Byrne Center for Nonlinear Science, Georgia Institute of Technology Fernando Camelli Center for Computational Fluid Dynamics, George
More informationHPC Cluster Decisions and ANSYS Configuration Best Practices. Diana Collier Lead Systems Support Specialist Houston UGM May 2014
HPC Cluster Decisions and ANSYS Configuration Best Practices Diana Collier Lead Systems Support Specialist Houston UGM May 2014 1 Agenda Introduction Lead Systems Support Specialist Cluster Decisions Job
More informationOn-Demand Supercomputing Multiplies the Possibilities
Microsoft Windows Compute Cluster Server 2003 Partner Solution Brief Image courtesy of Wolfram Research, Inc. On-Demand Supercomputing Multiplies the Possibilities Microsoft Windows Compute Cluster Server
More informationCS2101a Foundations of Programming for High Performance Computing
CS2101a Foundations of Programming for High Performance Computing Marc Moreno Maza & Ning Xie University of Western Ontario, London, Ontario (Canada) CS2101 Plan 1 Course Overview 2 Hardware Acceleration
More informationGPUs for Scientific Computing
GPUs for Scientific Computing p. 1/16 GPUs for Scientific Computing Mike Giles mike.giles@maths.ox.ac.uk Oxford-Man Institute of Quantitative Finance Oxford University Mathematical Institute Oxford e-research
More informationOpenFOAM Optimization Tools
OpenFOAM Optimization Tools Henrik Rusche and Aleks Jemcov h.rusche@wikki-gmbh.de and a.jemcov@wikki.co.uk Wikki, Germany and United Kingdom OpenFOAM Optimization Tools p. 1 Agenda Objective Review optimisation
More informationIntroduction to CFD Analysis
Introduction to CFD Analysis Introductory FLUENT Training 2006 ANSYS, Inc. All rights reserved. 2006 ANSYS, Inc. All rights reserved. 2-2 What is CFD? Computational fluid dynamics (CFD) is the science
More informationST810 Advanced Computing
ST810 Advanced Computing Lecture 17: Parallel computing part I Eric B. Laber Hua Zhou Department of Statistics North Carolina State University Mar 13, 2013 Outline computing Hardware computing overview
More informationAeroacoustic simulation based on linearized Euler equations and stochastic sound source modelling
Aeroacoustic simulation based on linearized Euler equations and stochastic sound source modelling H. Dechipre a, M. Hartmann a, J. W Delfs b and R. Ewert b a Volkswagen AG, Brieffach 1777, 38436 Wolfsburg,
More informationAdvanced CFD Methods 1
Advanced CFD Methods 1 Prof. Patrick Jenny, FS 2014 Date: 15.08.14, Time: 13:00, Student: Federico Danieli Summary The exam took place in Prof. Jenny s office, with his assistant taking notes on the answers.
More informationParallel Large-Scale Visualization
Parallel Large-Scale Visualization Aaron Birkland Cornell Center for Advanced Computing Data Analysis on Ranger January 2012 Parallel Visualization Why? Performance Processing may be too slow on one CPU
More information