Results from the Early Science High Speed Combus:on and Detona:on Project

Size: px
Start display at page:

Download "Results from the Early Science High Speed Combus:on and Detona:on Project"

Transcription

1 Results from the Early Science High Speed Combus:on and Detona:on Project Alexei Khokhlov, University of Chicago Joanna Aus:n, University of Illinois Charles Bacon, Argonne Na:onal Laboratory Andrew Knisely, University of Illinois Ben Clifford, Argonne Na:onal Laboratory Joe Bernstein, Argonne Na:onal Laboratory

2 Overview Science Technology Scaling challenges Current :mings

3 The Science Direct Numerical Simula:on of the deflagra:on- to- detona:on transi:on (DDT) in hydrogen- oxygen gaseous mixtures for hydrogen safety, funded by ASCR and BES The plan: Shock bifurca:on of a reflected shock Auto- igni:on, strong and weak 0.1atm, 6- micron resolu:on of 1m, 2.5cmx2.5cm pipe to model flame accelera:on and predict run distance to detona:on

4 Code structure Physics modules, Ini:al/boundary condi:ons of a problem run on top of ALLA ALLA: a Navier- Stokes fluid dynamics solver that runs on top of FTT FTT: Fully threaded tree library FTT library provides mesh, AMR, global parallel iterators, visualiza:on, I/O

5 Code features 3- d reac:ve flow Navier- Stokes with 8- species and 19 reac:on kine:cs H2- O2 burning, mul:- species NASA7 equa:on of state, mul:- species temperature dependent viscosity, mass and heat conduc:on, and radia:ve cooling Adap:ve mesh refinement on a regular rectangular grid

6 Scaling challenges, BG/P Moving to GPFS from Lustre, different I/O strategy required Change from one file per rank to a single file with MPI- I/O Improved checkpoint :me by 41x, mostly due to the reduc:on in metadata overhead (~28x faster) The remainder was due to MPI- I/O enforcing aligned writes, another ~1.5 :mes faster Data acquired using the Darshan library

7 Scaling challenges, BG/P (II) Lower memory per node led to the use of OpenMP App couldn t run in 4 or 2 ranks per node, leading to three idle cores in SMP mode The AMR code (FTT) executes work func:ons from the physics code (ALLA) using a global iterator Pugng openmp around the fluid dynamics work- func:on call results in a 3x speedup This got us scaling up to 32 racks of BG/P

8 Reflected shock tube valida:on

9 Shock bifurca:on angle The agreement of these structures 3D, accurate equa:on of state, viscosity, and heat conduc:on For instance elimina:ng heat conduc:on changes angle 1 by 8 degrees, and angle 2 by 4 degrees

10 Turbulence

11 Strong igni:on

12 Weak igni:on

13 Reducing communica:ons overheads At this point, the computa:onal side of the code was scaling well, and the efficiency losses at higher rank counts were due to the AMR refinement and rebalance steps

14 Balance :mer speedup On 128K cores, balance decisions were taking 64 seconds/call due to serial repeated work - got this under 1 second Also, the ghost pakern set post- refine was taking a long :me a rewrite to MPI one- sided sped this up to the point where mesh refinement was down to 10% of the cost of a run

15 Remaining challenges The point- to- point ghost data exchanges now consume a lot of :me, exhibi:ng a load imbalance between ranks Needs to be addressed more thoroughly in the rebalance heuris:c BG/P had one thread/core; BG/Q goes up to four Need new strategy for fine- grained OpenMP

16 Adding fine- grained OpenMP Currently the code passes all cells through work func:ons, one aoer the other. In order to take advantage of caching, we will create work- func:on sets that will operate over the cells in cache at the :me

17 Single- node scaling on Q Thread count Time per step Efficiency (68) 62 (64) (48) 34 (45) (40) 24 (27) (41) 11 (13) Parenthe:cal numbers come aoer increasing the size of the array of cells passed to the work func:ons high rank counts were gegng not enough work per thread from the original segng

18 20 step :mes (includes 5x refine/ balance) BG/Q BG/P Node count Time Efficiency Node count Time Efficiency

19 Main loop :mes BG/P - > BG/Q speedup = 2.5x/core, 9.2x/node BG/Q Node count Time Efficiency BG/P Node count Time Efficiency

20 Scaling plots

21 Next step DDT in a long pipe Tube length ~ 1 meter Cross- sec:on ~ 2.5 cm x 2.5 cm N cells ~ 10,000,000,000 N :me steps ~ 140,000 Numerical resolu:on ~ 6 microns

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

Introducing Overdecomposition to Existing Applications: PlasComCM and AMPI

Introducing Overdecomposition to Existing Applications: PlasComCM and AMPI Introducing Overdecomposition to Existing Applications: PlasComCM and AMPI Sam White Parallel Programming Lab UIUC 1 Introduction How to enable Overdecomposition, Asynchrony, and Migratability in existing

More information

TiDA: High Level Programming Abstrac8ons for Data Locality Management

TiDA: High Level Programming Abstrac8ons for Data Locality Management h#p://parcorelab.ku.edu.tr TiDA: High Level Programming Abstrac8ons for Data Locality Management Didem Unat, Muhammed Nufail Farooqi, Burak Bastem Koç University, Turkey Tan Nguyen, Weiqun Zhang, George

More information

Heterogeneous CPU+GPU Molecular Dynamics Engine in CHARMM

Heterogeneous CPU+GPU Molecular Dynamics Engine in CHARMM Heterogeneous CPU+GPU Molecular Dynamics Engine in CHARMM 25th March, GTC 2014, San Jose CA AnE- Pekka Hynninen ane.pekka.hynninen@nrel.gov NREL is a na*onal laboratory of the U.S. Department of Energy,

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

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

Tutorial II Using the adap3ve mesh refinement & spherical shell geometry. Juliane Dannberg

Tutorial II Using the adap3ve mesh refinement & spherical shell geometry. Juliane Dannberg Tutorial II Using the adap3ve mesh refinement & spherical shell geometry Juliane Dannberg Overview At the end of this tutorial, you should be able to: Set up a model with Earth- like geometry and temperature

More information

Simulation-time data analysis and I/O acceleration at extreme scale with GLEAN

Simulation-time data analysis and I/O acceleration at extreme scale with GLEAN Simulation-time data analysis and I/O acceleration at extreme scale with GLEAN Venkatram Vishwanath, Mark Hereld and Michael E. Papka Argonne Na

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

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

Flow and Heat Transfer in a Mixing Elbow

Flow and Heat Transfer in a Mixing Elbow Flow and Heat Transfer in a Mixing Elbow Objectives The main objectives of the project are to learn (i) how to set up and perform flow simulations with heat transfer and mixing, (ii) post-processing and

More information

Op#mizing PGAS overhead in a mul#-locale Chapel implementa#on of CoMD

Op#mizing PGAS overhead in a mul#-locale Chapel implementa#on of CoMD Op#mizing PGAS overhead in a mul#-locale Chapel implementa#on of CoMD Riyaz Haque and David F. Richards This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore

More information

Danesh TaNi & Amit Amritkar

Danesh TaNi & Amit Amritkar GenIDLEST Co- Design Danesh TaNi & Amit Amritkar Collaborators Wu- chun Feng, Paul Sathre, Kaixi Hou, Sriram Chivukula, Hao Wang, Eric de Sturler, Kasia Swirydowicz Virginia Tech AFOSR- BRI Workshop Feb

More information

Unstructured Finite Volume Code on a Cluster with Mul6ple GPUs per Node

Unstructured Finite Volume Code on a Cluster with Mul6ple GPUs per Node Unstructured Finite Volume Code on a Cluster with Mul6ple GPUs per Node Keith Obenschain & Andrew Corrigan Laboratory for Computa;onal Physics and Fluid Dynamics Naval Research Laboratory Washington DC,

More information

Concurrency-Optimized I/O For Visualizing HPC Simulations: An Approach Using Dedicated I/O Cores

Concurrency-Optimized I/O For Visualizing HPC Simulations: An Approach Using Dedicated I/O Cores Concurrency-Optimized I/O For Visualizing HPC Simulations: An Approach Using Dedicated I/O Cores Ma#hieu Dorier, Franck Cappello, Marc Snir, Bogdan Nicolae, Gabriel Antoniu 4th workshop of the Joint Laboratory

More information

Do You Know What Your I/O Is Doing? (and how to fix it?) William Gropp

Do You Know What Your I/O Is Doing? (and how to fix it?) William Gropp Do You Know What Your I/O Is Doing? (and how to fix it?) William Gropp www.cs.illinois.edu/~wgropp Messages Current I/O performance is often appallingly poor Even relative to what current systems can achieve

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

Preliminary Spray Cooling Simulations Using a Full-Cone Water Spray

Preliminary Spray Cooling Simulations Using a Full-Cone Water Spray 39th Dayton-Cincinnati Aerospace Sciences Symposium Preliminary Spray Cooling Simulations Using a Full-Cone Water Spray Murat Dinc Prof. Donald D. Gray (advisor), Prof. John M. Kuhlman, Nicholas L. Hillen,

More information

Introduction to C omputational F luid Dynamics. D. Murrin

Introduction to C omputational F luid Dynamics. D. Murrin Introduction to C omputational F luid Dynamics D. Murrin Computational fluid dynamics (CFD) is the science of predicting fluid flow, heat transfer, mass transfer, chemical reactions, and related phenomena

More information

Performance and Optimization Abstractions for Large Scale Heterogeneous Systems in the Cactus/Chemora Framework

Performance and Optimization Abstractions for Large Scale Heterogeneous Systems in the Cactus/Chemora Framework Performance and Optimization Abstractions for Large Scale Heterogeneous Systems in the Cactus/Chemora Framework Erik Schne+er Perimeter Ins1tute for Theore1cal Physics XSCALE 2013, Boulder, CO, 2013-08-

More information

Modeling and Simulation of Single Phase Fluid Flow and Heat Transfer in Packed Beds

Modeling and Simulation of Single Phase Fluid Flow and Heat Transfer in Packed Beds Modeling and Simulation of Single Phase Fluid Flow and Heat Transfer in Packed Beds by:- Balaaji Mahadevan Shaurya Sachdev Subhanshu Pareek Amol Deshpande Birla Institute of Technology and Science, Pilani

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

CRAY User Group Mee'ng May 2010

CRAY User Group Mee'ng May 2010 Applica'on Accelera'on on Current and Future Cray Pla4orms Alice Koniges, NERSC, Berkeley Lab David Eder, Lawrence Livermore Na'onal Laboratory (speakers) Robert Preissl, Jihan Kim (NERSC LBL), Aaron Fisher,

More information

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

Adaptive Refinement Tree (ART) code. N-Body: Parallelization using OpenMP and MPI Adaptive Refinement Tree (ART) code N-Body: Parallelization using OpenMP and MPI 1 Family of codes N-body: OpenMp N-body: MPI+OpenMP N-body+hydro+cooling+SF: OpenMP N-body+hydro+cooling+SF: MPI 2 History:

More information

Fluent User Services Center

Fluent User Services Center Solver Settings 5-1 Using the Solver Setting Solver Parameters Convergence Definition Monitoring Stability Accelerating Convergence Accuracy Grid Independence Adaption Appendix: Background Finite Volume

More information

Tutorial 1. Introduction to Using FLUENT: Fluid Flow and Heat Transfer in a Mixing Elbow

Tutorial 1. Introduction to Using FLUENT: Fluid Flow and Heat Transfer in a Mixing Elbow Tutorial 1. Introduction to Using FLUENT: Fluid Flow and Heat Transfer in a Mixing Elbow Introduction This tutorial illustrates the setup and solution of the two-dimensional turbulent fluid flow and heat

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

Preliminary Evalua.on of ABAQUS, FLUENT, and in- house GPU code Performance on Blue Waters

Preliminary Evalua.on of ABAQUS, FLUENT, and in- house GPU code Performance on Blue Waters Blue Water Symposium, University of Illinois, Urbana, IL, May 12-15, 2014 Preliminary Evalua.on of ABAQUS, FLUENT, and in- house GPU code Performance on Blue Waters B. G. Thomas 1, L. C. Hibbeler 1, K.

More information

Adaptive Mesh Refinement in Titanium

Adaptive Mesh Refinement in Titanium Adaptive Mesh Refinement in Titanium http://seesar.lbl.gov/anag Lawrence Berkeley National Laboratory April 7, 2005 19 th IPDPS, April 7, 2005 1 Overview Motivations: Build the infrastructure in Titanium

More information

Outline. In Situ Data Triage and Visualiza8on

Outline. In Situ Data Triage and Visualiza8on In Situ Data Triage and Visualiza8on Kwan- Liu Ma University of California at Davis Outline In situ data triage and visualiza8on: Issues and strategies Case study: An earthquake simula8on Case study: A

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

Introduction to parallel Computing

Introduction to parallel Computing Introduction to parallel Computing VI-SEEM Training Paschalis Paschalis Korosoglou Korosoglou (pkoro@.gr) (pkoro@.gr) Outline Serial vs Parallel programming Hardware trends Why HPC matters HPC Concepts

More information

Implemen'ng BCs in Legion- S3D

Implemen'ng BCs in Legion- S3D Implemen'ng BCs in Legion- S3D Hemanth Kolla Sandia Na0onal Laboratories Legion Bootcamp December 7 th, 2015 Stanford, CA Background S3D is an explicit finite difference PDE solver for turbulent combus0on:

More information

Systems Software for Scalable Applications (or) Super Faster Stronger MPI (and friends) for Blue Waters Applications

Systems Software for Scalable Applications (or) Super Faster Stronger MPI (and friends) for Blue Waters Applications Systems Software for Scalable Applications (or) Super Faster Stronger MPI (and friends) for Blue Waters Applications William Gropp University of Illinois, Urbana- Champaign Pavan Balaji, Rajeev Thakur

More information

MPI & OpenMP Mixed Hybrid Programming

MPI & OpenMP Mixed Hybrid Programming MPI & OpenMP Mixed Hybrid Programming Berk ONAT İTÜ Bilişim Enstitüsü 22 Haziran 2012 Outline Introduc/on Share & Distributed Memory Programming MPI & OpenMP Advantages/Disadvantages MPI vs. OpenMP Why

More information

AcuSolve Performance Benchmark and Profiling. October 2011

AcuSolve Performance Benchmark and Profiling. October 2011 AcuSolve Performance Benchmark and Profiling October 2011 Note The following research was performed under the HPC Advisory Council activities Participating vendors: Intel, Dell, Mellanox, Altair Compute

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

Oh, Exascale! The effect of emerging architectures on scien1fic discovery. Kenneth Moreland, Sandia Na1onal Laboratories

Oh, Exascale! The effect of emerging architectures on scien1fic discovery. Kenneth Moreland, Sandia Na1onal Laboratories Photos placed in horizontal posi1on with even amount of white space between photos and header Oh, $#*@! Exascale! The effect of emerging architectures on scien1fic discovery Ultrascale Visualiza1on Workshop,

More information

Transport Simulations beyond Petascale. Jing Fu (ANL)

Transport Simulations beyond Petascale. Jing Fu (ANL) Transport Simulations beyond Petascale Jing Fu (ANL) A) Project Overview The project: Peta- and exascale algorithms and software development (petascalable codes: Nek5000, NekCEM, NekLBM) Science goals:

More information

Microscale Modeling of Abla1ve Thermal Protec1on System Materials

Microscale Modeling of Abla1ve Thermal Protec1on System Materials Microscale Modeling of Abla1ve Thermal Protec1on System Materials Eric Stern, Graham Candler, Tom Schwartzentruber, Ioannis Nompelis, Michael Barnhardt 1 1 Abla1on Modeling Engineering material response

More information

COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF ORIFICE PLATE METERING SITUATIONS UNDER ABNORMAL CONFIGURATIONS

COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF ORIFICE PLATE METERING SITUATIONS UNDER ABNORMAL CONFIGURATIONS COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF ORIFICE PLATE METERING SITUATIONS UNDER ABNORMAL CONFIGURATIONS Dr W. Malalasekera Version 3.0 August 2013 1 COMPUTATIONAL FLUID DYNAMICS ANALYSIS OF ORIFICE PLATE

More information

Solving Partial Differential Equations on Overlapping Grids

Solving Partial Differential Equations on Overlapping Grids **FULL TITLE** ASP Conference Series, Vol. **VOLUME**, **YEAR OF PUBLICATION** **NAMES OF EDITORS** Solving Partial Differential Equations on Overlapping Grids William D. Henshaw Centre for Applied Scientific

More information

Achieving Efficient Strong Scaling with PETSc Using Hybrid MPI/OpenMP Optimisation

Achieving Efficient Strong Scaling with PETSc Using Hybrid MPI/OpenMP Optimisation Achieving Efficient Strong Scaling with PETSc Using Hybrid MPI/OpenMP Optimisation Michael Lange 1 Gerard Gorman 1 Michele Weiland 2 Lawrence Mitchell 2 Xiaohu Guo 3 James Southern 4 1 AMCG, Imperial College

More information

NUMERICAL 3D TRANSONIC FLOW SIMULATION OVER A WING

NUMERICAL 3D TRANSONIC FLOW SIMULATION OVER A WING Review of the Air Force Academy No.3 (35)/2017 NUMERICAL 3D TRANSONIC FLOW SIMULATION OVER A WING Cvetelina VELKOVA Department of Technical Mechanics, Naval Academy Nikola Vaptsarov,Varna, Bulgaria (cvetelina.velkova1985@gmail.com)

More information

Scalability of Uintah Past Present and Future

Scalability of Uintah Past Present and Future DOE for funding the CSAFE project (97-10), DOE NETL, DOE NNSA NSF for funding via SDCI and PetaApps, INCITE, XSEDE Scalability of Uintah Past Present and Future Martin Berzins Qingyu Meng John Schmidt,

More information

CS 475: Parallel Programming Introduction

CS 475: Parallel Programming Introduction CS 475: Parallel Programming Introduction Wim Bohm, Sanjay Rajopadhye Colorado State University Fall 2014 Course Organization n Let s make a tour of the course website. n Main pages Home, front page. Syllabus.

More information

Introduction to ANSYS CFX

Introduction to ANSYS CFX Workshop 03 Fluid flow around the NACA0012 Airfoil 16.0 Release Introduction to ANSYS CFX 2015 ANSYS, Inc. March 13, 2015 1 Release 16.0 Workshop Description: The flow simulated is an external aerodynamics

More information

Turbulent Premixed Combustion with Flamelet Generated Manifolds in COMSOL Multiphysics

Turbulent Premixed Combustion with Flamelet Generated Manifolds in COMSOL Multiphysics Turbulent Premixed Combustion with Flamelet Generated Manifolds in COMSOL Multiphysics Rob J.M Bastiaans* Eindhoven University of Technology *Corresponding author: PO box 512, 5600 MB, Eindhoven, r.j.m.bastiaans@tue.nl

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

NUMERICAL VISCOSITY. Convergent Science White Paper. COPYRIGHT 2017 CONVERGENT SCIENCE. All rights reserved.

NUMERICAL VISCOSITY. Convergent Science White Paper. COPYRIGHT 2017 CONVERGENT SCIENCE. All rights reserved. Convergent Science White Paper COPYRIGHT 2017 CONVERGENT SCIENCE. All rights reserved. This document contains information that is proprietary to Convergent Science. Public dissemination of this document

More information

Implementation of an integrated efficient parallel multiblock Flow solver

Implementation of an integrated efficient parallel multiblock Flow solver Implementation of an integrated efficient parallel multiblock Flow solver Thomas Bönisch, Panagiotis Adamidis and Roland Rühle adamidis@hlrs.de Outline Introduction to URANUS Why using Multiblock meshes

More information

NASA Rotor 67 Validation Studies

NASA Rotor 67 Validation Studies NASA Rotor 67 Validation Studies ADS CFD is used to predict and analyze the performance of the first stage rotor (NASA Rotor 67) of a two stage transonic fan designed and tested at the NASA Glenn center

More information

NUMERICAL INVESTIGATION OF THE FLOW BEHAVIOR INTO THE INLET GUIDE VANE SYSTEM (IGV)

NUMERICAL INVESTIGATION OF THE FLOW BEHAVIOR INTO THE INLET GUIDE VANE SYSTEM (IGV) University of West Bohemia» Department of Power System Engineering NUMERICAL INVESTIGATION OF THE FLOW BEHAVIOR INTO THE INLET GUIDE VANE SYSTEM (IGV) Publication was supported by project: Budování excelentního

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

Parallel Mesh Partitioning in Alya

Parallel Mesh Partitioning in Alya Available online at www.prace-ri.eu Partnership for Advanced Computing in Europe Parallel Mesh Partitioning in Alya A. Artigues a *** and G. Houzeaux a* a Barcelona Supercomputing Center ***antoni.artigues@bsc.es

More information

Porting and Optimisation of UM on ARCHER. Karthee Sivalingam, NCAS-CMS. HPC Workshop ECMWF JWCRP

Porting and Optimisation of UM on ARCHER. Karthee Sivalingam, NCAS-CMS. HPC Workshop ECMWF JWCRP Porting and Optimisation of UM on ARCHER Karthee Sivalingam, NCAS-CMS HPC Workshop ECMWF JWCRP Acknowledgements! NCAS-CMS Bryan Lawrence Jeffrey Cole Rosalyn Hatcher Andrew Heaps David Hassell Grenville

More information

Integra(ng an open source dynamic river model in hydrology modeling frameworks

Integra(ng an open source dynamic river model in hydrology modeling frameworks Integra(ng an open source dynamic river model in hydrology modeling frameworks Simula(on of Guadalupe and San Antonio River basin during a flood event with 1.3 x 10 5 computa(onal nodes at 100 m resolu(on.

More information

Carlo Cavazzoni, HPC department, CINECA

Carlo Cavazzoni, HPC department, CINECA Introduction to Shared memory architectures Carlo Cavazzoni, HPC department, CINECA Modern Parallel Architectures Two basic architectural scheme: Distributed Memory Shared Memory Now most computers have

More information

Numerical Simulation Study on Aerodynamic Characteristics of the High Speed Train under Crosswind

Numerical Simulation Study on Aerodynamic Characteristics of the High Speed Train under Crosswind 2017 2nd International Conference on Industrial Aerodynamics (ICIA 2017) ISBN: 978-1-60595-481-3 Numerical Simulation Study on Aerodynamic Characteristics of the High Speed Train under Crosswind Fan Zhao,

More information

CFD in COMSOL Multiphysics

CFD in COMSOL Multiphysics CFD in COMSOL Multiphysics Christian Wollblad Copyright 2017 COMSOL. Any of the images, text, and equations here may be copied and modified for your own internal use. All trademarks are the property of

More information

Peta-Scale Simulations with the HPC Software Framework walberla:

Peta-Scale Simulations with the HPC Software Framework walberla: Peta-Scale Simulations with the HPC Software Framework walberla: Massively Parallel AMR for the Lattice Boltzmann Method SIAM PP 2016, Paris April 15, 2016 Florian Schornbaum, Christian Godenschwager,

More information

Parallel I/O Libraries and Techniques

Parallel I/O Libraries and Techniques Parallel I/O Libraries and Techniques Mark Howison User Services & Support I/O for scientifc data I/O is commonly used by scientific applications to: Store numerical output from simulations Load initial

More information

Hybrid programming with MPI and OpenMP On the way to exascale

Hybrid programming with MPI and OpenMP On the way to exascale Institut du Développement et des Ressources en Informatique Scientifique www.idris.fr Hybrid programming with MPI and OpenMP On the way to exascale 1 Trends of hardware evolution Main problematic : how

More information

Fusion PIC Code Performance Analysis on the Cori KNL System. T. Koskela*, J. Deslippe*,! K. Raman**, B. Friesen*! *NERSC! ** Intel!

Fusion PIC Code Performance Analysis on the Cori KNL System. T. Koskela*, J. Deslippe*,! K. Raman**, B. Friesen*! *NERSC! ** Intel! Fusion PIC Code Performance Analysis on the Cori KNL System T. Koskela*, J. Deslippe*,! K. Raman**, B. Friesen*! *NERSC! ** Intel! tkoskela@lbl.gov May 18, 2017-1- Outline Introduc3on to magne3c fusion

More information

Unstructured Grid Numbering Schemes for GPU Coalescing Requirements

Unstructured Grid Numbering Schemes for GPU Coalescing Requirements Unstructured Grid Numbering Schemes for GPU Coalescing Requirements Andrew Corrigan 1 and Johann Dahm 2 Laboratories for Computational Physics and Fluid Dynamics Naval Research Laboratory 1 Department

More information

Uncertainty Analysis: Parameter Estimation. Jackie P. Hallberg Coastal and Hydraulics Laboratory Engineer Research and Development Center

Uncertainty Analysis: Parameter Estimation. Jackie P. Hallberg Coastal and Hydraulics Laboratory Engineer Research and Development Center Uncertainty Analysis: Parameter Estimation Jackie P. Hallberg Coastal and Hydraulics Laboratory Engineer Research and Development Center Outline ADH Optimization Techniques Parameter space Observation

More information

Enzo-P / Cello. Formation of the First Galaxies. San Diego Supercomputer Center. Department of Physics and Astronomy

Enzo-P / Cello. Formation of the First Galaxies. San Diego Supercomputer Center. Department of Physics and Astronomy Enzo-P / Cello Formation of the First Galaxies James Bordner 1 Michael L. Norman 1 Brian O Shea 2 1 University of California, San Diego San Diego Supercomputer Center 2 Michigan State University Department

More information

Introduction to Parallel Programming

Introduction to Parallel Programming Introduction to Parallel Programming Linda Woodard CAC 19 May 2010 Introduction to Parallel Computing on Ranger 5/18/2010 www.cac.cornell.edu 1 y What is Parallel Programming? Using more than one processor

More information

Improving Uintah s Scalability Through the Use of Portable

Improving Uintah s Scalability Through the Use of Portable Improving Uintah s Scalability Through the Use of Portable Kokkos-Based Data Parallel Tasks John Holmen1, Alan Humphrey1, Daniel Sunderland2, Martin Berzins1 University of Utah1 Sandia National Laboratories2

More information

Tools zur Op+mierung eingebe2eter Mul+core- Systeme. Bernhard Bauer

Tools zur Op+mierung eingebe2eter Mul+core- Systeme. Bernhard Bauer Tools zur Op+mierung eingebe2eter Mul+core- Systeme Bernhard Bauer Agenda Mo+va+on So.ware Engineering & Mul5core Think Parallel Models Added Value Tooling Quo Vadis? The Mul5core Era Moore s Law: The

More information

Modeling Evaporating Liquid Spray

Modeling Evaporating Liquid Spray Tutorial 16. Modeling Evaporating Liquid Spray Introduction In this tutorial, FLUENT s air-blast atomizer model is used to predict the behavior of an evaporating methanol spray. Initially, the air flow

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

Performance Issues in Parallelization Saman Amarasinghe Fall 2009

Performance Issues in Parallelization Saman Amarasinghe Fall 2009 Performance Issues in Parallelization Saman Amarasinghe Fall 2009 Today s Lecture Performance Issues of Parallelism Cilk provides a robust environment for parallelization It hides many issues and tries

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

Introduction to Computational Fluid Dynamics Mech 122 D. Fabris, K. Lynch, D. Rich

Introduction to Computational Fluid Dynamics Mech 122 D. Fabris, K. Lynch, D. Rich Introduction to Computational Fluid Dynamics Mech 122 D. Fabris, K. Lynch, D. Rich 1 Computational Fluid dynamics Computational fluid dynamics (CFD) is the analysis of systems involving fluid flow, heat

More information

Parallel Computing for Reacting Flows Using Adaptive Grid Refinement

Parallel Computing for Reacting Flows Using Adaptive Grid Refinement Contemporary Mathematics Volume 218, 1998 B 0-8218-0988-1-03054-5 Parallel Computing for Reacting Flows Using Adaptive Grid Refinement Robbert L. Verweij, Aris Twerda, and Tim W.J. Peeters 1. Introduction

More information

Shape optimisation using breakthrough technologies

Shape optimisation using breakthrough technologies Shape optimisation using breakthrough technologies Compiled by Mike Slack Ansys Technical Services 2010 ANSYS, Inc. All rights reserved. 1 ANSYS, Inc. Proprietary Introduction Shape optimisation technologies

More information

PERFORMANCE OF PARALLEL IO ON LUSTRE AND GPFS

PERFORMANCE OF PARALLEL IO ON LUSTRE AND GPFS PERFORMANCE OF PARALLEL IO ON LUSTRE AND GPFS David Henty and Adrian Jackson (EPCC, The University of Edinburgh) Charles Moulinec and Vendel Szeremi (STFC, Daresbury Laboratory Outline Parallel IO problem

More information

AcuSolve Performance Benchmark and Profiling. October 2011

AcuSolve Performance Benchmark and Profiling. October 2011 AcuSolve Performance Benchmark and Profiling October 2011 Note The following research was performed under the HPC Advisory Council activities Participating vendors: AMD, Dell, Mellanox, Altair Compute

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

Tutorial 2. Modeling Periodic Flow and Heat Transfer

Tutorial 2. Modeling Periodic Flow and Heat Transfer Tutorial 2. Modeling Periodic Flow and Heat Transfer Introduction: Many industrial applications, such as steam generation in a boiler or air cooling in the coil of an air conditioner, can be modeled as

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

Acknowledgments. Amdahl s Law. Contents. Programming with MPI Parallel programming. 1 speedup = (1 P )+ P N. Type to enter text

Acknowledgments. Amdahl s Law. Contents. Programming with MPI Parallel programming. 1 speedup = (1 P )+ P N. Type to enter text Acknowledgments Programming with MPI Parallel ming Jan Thorbecke Type to enter text This course is partly based on the MPI courses developed by Rolf Rabenseifner at the High-Performance Computing-Center

More information

Introduction to MPI. EAS 520 High Performance Scientific Computing. University of Massachusetts Dartmouth. Spring 2014

Introduction to MPI. EAS 520 High Performance Scientific Computing. University of Massachusetts Dartmouth. Spring 2014 Introduction to MPI EAS 520 High Performance Scientific Computing University of Massachusetts Dartmouth Spring 2014 References This presentation is almost an exact copy of Dartmouth College's Introduction

More information

Verification of Laminar and Validation of Turbulent Pipe Flows

Verification of Laminar and Validation of Turbulent Pipe Flows 1 Verification of Laminar and Validation of Turbulent Pipe Flows 1. Purpose ME:5160 Intermediate Mechanics of Fluids CFD LAB 1 (ANSYS 18.1; Last Updated: Aug. 1, 2017) By Timur Dogan, Michael Conger, Dong-Hwan

More information

Project #3 MAE 598 Applied CFD

Project #3 MAE 598 Applied CFD Project #3 MAE 598 Applied CFD 16 November 2017 H.P. Huang 1 Task 1 (a) Task 1a was to perform a transient analysis of a 2-D chamber that is initially filled with air, and has water flowing through the

More information

Isotropic Porous Media Tutorial

Isotropic Porous Media Tutorial STAR-CCM+ User Guide 3927 Isotropic Porous Media Tutorial This tutorial models flow through the catalyst geometry described in the introductory section. In the porous region, the theoretical pressure drop

More information

A Study of High Performance Computing and the Cray SV1 Supercomputer. Michael Sullivan TJHSST Class of 2004

A Study of High Performance Computing and the Cray SV1 Supercomputer. Michael Sullivan TJHSST Class of 2004 A Study of High Performance Computing and the Cray SV1 Supercomputer Michael Sullivan TJHSST Class of 2004 June 2004 0.1 Introduction A supercomputer is a device for turning compute-bound problems into

More information

Parallel Visualiza,on At TACC

Parallel Visualiza,on At TACC Parallel Visualiza,on At TACC Visualiza,on Problems * With thanks to Sean Ahern for the metaphor Huge problems: Data cannot be moved off system where it is computed Visualiza,on requires equivalent resources

More information

Hybrid Space-Time Parallel Solution of Burgers Equation

Hybrid Space-Time Parallel Solution of Burgers Equation Hybrid Space-Time Parallel Solution of Burgers Equation Rolf Krause 1 and Daniel Ruprecht 1,2 Key words: Parareal, spatial parallelization, hybrid parallelization 1 Introduction Many applications in high

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

Parallel Mesh Multiplication for Code_Saturne

Parallel Mesh Multiplication for Code_Saturne Parallel Mesh Multiplication for Code_Saturne Pavla Kabelikova, Ales Ronovsky, Vit Vondrak a Dept. of Applied Mathematics, VSB-Technical University of Ostrava, Tr. 17. listopadu 15, 708 00 Ostrava, Czech

More information

Vincent C. Betro, R. Glenn Brook, & Ryan C. Hulguin XSEDE Xtreme Scaling Workshop Chicago, IL July 15-16, 2012

Vincent C. Betro, R. Glenn Brook, & Ryan C. Hulguin XSEDE Xtreme Scaling Workshop Chicago, IL July 15-16, 2012 Vincent C. Betro, R. Glenn Brook, & Ryan C. Hulguin XSEDE Xtreme Scaling Workshop Chicago, IL July 15-16, 2012 Outline NICS and AACE Architecture Overview Resources Native Mode Boltzmann BGK Solver Native/Offload

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

Modeling Unsteady Compressible Flow

Modeling Unsteady Compressible Flow Tutorial 4. Modeling Unsteady Compressible Flow Introduction In this tutorial, FLUENT s density-based implicit solver is used to predict the timedependent flow through a two-dimensional nozzle. As an initial

More information

Computational Fluid Dynamics (CFD) Simulation in Air Duct Channels Using STAR CCM+

Computational Fluid Dynamics (CFD) Simulation in Air Duct Channels Using STAR CCM+ Available onlinewww.ejaet.com European Journal of Advances in Engineering and Technology, 2017,4 (3): 216-220 Research Article ISSN: 2394-658X Computational Fluid Dynamics (CFD) Simulation in Air Duct

More information

Investigation of cross flow over a circular cylinder at low Re using the Immersed Boundary Method (IBM)

Investigation of cross flow over a circular cylinder at low Re using the Immersed Boundary Method (IBM) Computational Methods and Experimental Measurements XVII 235 Investigation of cross flow over a circular cylinder at low Re using the Immersed Boundary Method (IBM) K. Rehman Department of Mechanical Engineering,

More information

Liszt, a language for PDE solvers

Liszt, a language for PDE solvers Liszt, a language for PDE solvers Zachary DeVito, Niels Joubert, Francisco Palacios, Stephen Oakley, Montserrat Medina, Mike Barrientos, Erich Elsen, Frank Ham, Alex Aiken, Karthik Duraisamy, Eric Darve,

More information

CFD Analysis of a Fully Developed Turbulent Flow in a Pipe with a Constriction and an Obstacle

CFD Analysis of a Fully Developed Turbulent Flow in a Pipe with a Constriction and an Obstacle CFD Analysis of a Fully Developed Turbulent Flow in a Pipe with a Constriction and an Obstacle C, Diyoke Mechanical Engineering Department Enugu State University of Science & Tech. Enugu, Nigeria U, Ngwaka

More information

Investigation of mixing chamber for experimental FGD reactor

Investigation of mixing chamber for experimental FGD reactor Investigation of mixing chamber for experimental FGD reactor Jan Novosád 1,a, Petra Danová 1 and Tomáš Vít 1 1 Department of Power Engineering Equipment, Faculty of Mechanical Engineering, Technical University

More information