Large-Scale Reservoir Simulation and Big Data Visualization
|
|
- Candace Bailey
- 8 years ago
- Views:
Transcription
1 Large-Scale Reservoir Simulation and Big Data Visualization Dr. Zhangxing John Chen NSERC/Alberta Innovates Energy Environment Solutions/Foundation CMG Chair Alberta Innovates Technology Future (icore) Chair Director, Foundation CMG/Frank-Sarah Meyer Collaboration Center, University of Calgary Slide 1
2 Outlines Motivations - Importance Simulation and Visualization Case Studies Summary Remarks Slide 2
3 Outlines Motivations - Importance Parallelization Means Case Studies Summary Remarks Slide 3
4 Motivations Accuracy Stability Robustness Speed capital savings Slide 4
5 Speed Issue 3D thermal models: with 500,000 cells geomodels and multiprocessor computers, runs take hours to weeks. For typical optimization run, 400-1,000 runs required. If done serially, hundreds to thousands of days for each optimization run required. With parallelization, optimization runtimes will drop. More geological descriptions can be added. Slide 5
6 Motivations Grid (scale) requirements Physics requirements Process requirements Slide 6
7 Grid Requirements Reservoir (rock and fluid) heterogeneity Thin moving thermal front Thin mobile solvent-rich layers ~ 1cm Discontinuity: presence of faults, fractures, and mud and shale layers Small dispersion/diffusion Local reaction (chemistry) zones Slide 7
8 Grid Requirements Rock heterogeneity Slide 8
9 Fluid heterogeneity Grid Requirements Slide 9
10 Grid Requirements Thin moving thermal and solvent fronts Slide 10
11 Grid Requirements Discontinuity: presence of faults, fractures, and mud and shale layers Slide 11
12 Grid Requirements Small dispersion/diffusion Slide 12
13 Grid Requirements Local reaction (chemistry) zones Slide 13
14 Physics Requirements Disparate data with different scales Thermal and solvent effects Mass and heat transfer Phase behavior Geomechanics Wellbore flow Slide 14
15 Process Requirements Thermal Recovery Processes - SAGD (steam assisted gravity drainage) - CSS (cyclic steam stimulation) - ISC (in situ combustion) Solvent Recovery Processes - VAPEX (vapor extraction) - SAP (solvent aided process) Slide 15
16 Business Competiveness Field management Equipment management Cost management SIMULATION TECHNOLOGY Strategy Safety Slide 16
17 Outlines Motivations - Importance Simulation and Visualization Case Studies Summary Remarks Slide 17
18 Petroleum Reservoir Simulators Black oil simulator (water flooding, fractured reservoirs) Compositional simulator (CO 2, N 2, CBM, tight and shale oil and gas) Thermal simulator (CSS, SAGD, ISC, THAI, Steam flooding) Chemical simulator (SAP+Foam) Wellbore module Geomechanical module Slide 18
19 Acceleration Means Software Acceleration Hardware Acceleration Slide 19
20 Software Acceleration Grid Management Discretization (Numerical) Methods System Solvers Parallelization (Matrices and Vectors) Software Design Slide 20
21 Grid Management The most critical modules - Type, choice of numerical methods - Partition, workload, communication - Data structure, info and data distribution - Numbering, bandwidth, and input Slide 21
22 Discretization Methods Finite difference methods Finite volume (control volume) methods Finite element methods Slide 22
23 System Solvers Preconditioners Linear Solvers A x = b Nonlinear Solvers Slide 23
24 Polynomial Approximate Inverse ILUT(p, tol) ILU(k) Preconditioners Domain Decomposition (Restricted Additive Schwarz) Algebraic Multigrid: classical and smoothed aggregation Slide 24
25 Linear Solvers GMRES, CG, BICGSTAB and GCR CGS, Orthomin and Orthodir Classical AMG Smoothed Aggregation AMG Slide 25
26 Nonlinear Solvers Newton Iterations Newton-Raphson Iterations Slide 26
27 Software Design OpenMP - Multi-core, easy to use, limited scalability MPI - communication - MPI-IO Programming languages - C, C++, Fortran, Slide 27
28 Hardware Acceleration CPUs (central processing units) GPUs (graph processing units) Slide 28
29 CPU VS GPU GPU (C2050) CPU (X5570) Cores Memory 144 GB/s 10 GB/s Float Performance 1030G (s) / 515G (d) ~20G GPU is around 10 times faster than CPU! Slide 29
30 Outlines Motivations Simulation and Visualization Case Studies Summary Remarks Slide 30
31 AMG: Example 1 Two-dimensional elliptic problem Grid size: 1,000x1,000, non-zeros: 4,996,000 Tol: 1e-6, level: 8 36 iterations GPU: 1.30s CPU: 12.26s Speedup: 9.33 Slide 31
32 AMG: Example 2 Two-dimensional elliptic problem Grid size: 1,500x1,500, non-zeros: 11,244,000 Tol: 1e-6, level: 8 31 iterations GPU: 2.58s CPU: 24.50s Speedup: 9.42 Slide 32
33 AMG: Example 3 Three-dimensional elliptic problem Grid size: 100x100x100, non-zeros: 6,940,000 Tol: 1e-6, level: 8 21 iterations GPU: 1.13s CPU: 10.80s Speedup: 9.58 Slide 33
34 AMG: Example 4 Three-dimensional elliptic problem Grid size: 130x130x130, non-zeros: 15,277,000 Tol: 1e-6, level: 8 25 iterations GPU: 3.02s CPU: 37.86s Speedup: Slide 34
35 Numerical Studies on CPUs Parallel (University of Calgary), Westgrid 528 standard nodes - 26-core Intel Xeon E5649 processors - 24 G memory InfiniBand 4X QDR, 40 Gbit/s Slide 35
36 15M Case: Example 5 GMRES + DDM Grid: 250x250x250 Unknowns: 15 million # processors Grid time (s) Overall time (s) Slide 36
37 125M Case: Example 6 GMRES + DDM Grid: 500x500x500 Unknowns: 125 million # processors Grid time (s) Overall time (s) Slide 37
38 200M Case: Example 7 GMRES + DDM Grid: 585x585x585 Unknowns: 200 million # processors Grid time (s) Overall time (s) Slide 38
39 Billion Case: Example 8 GMRES + DDM Grid size: billion (B) # processors Grid size 1 B 1B 2 B 3 B Grid time (s) Overall time (s) Slide 39
40 Stereo 3D and Immersive Visualization Immersive visualization has been shown to enable interactions that are more intuitive and that let users focus on analysis. Slide 40
41 Stereo 3D and Immersive Visualization Slide 41
42 Stereo 3D and Immersive Visualization Slide 42
43 Case Study T.Q.C. Dang, L.X. Nghiem, Z. Chen, and T.B.N. Nguyen, CO 2 low-salinity water alternating gas: A promising new approach for EOR, Journal of Petroleum Technology, January 2015, Slide 43
44 Case Study Geological Modeling Facies Modeling Clay Mapping Advanced Field Scale LSW Modeling Sensitivity Analysis History Matching Optimization Uncertainty Assessment Reservoir Simulation Flow, Ion Exchange, Geochemistry, Wettability Alteration CEC & Porosity Modeling Permeability Modeling Slide 44
45 Case Study Slide 45
46 Case Study Optimal Pattern Slide 46
47 Case Study Slide 47
48 Outlines Motivations Simulation and Visualization Case Studies Summary Remarks Slide 48
49 Summary Remarks Ultimate Goals Increasing reserves Reducing operating costs Enhancing petroleum recovery Capital savings Slide 49
50 Sponsors Slide 50
P013 INTRODUCING A NEW GENERATION OF RESERVOIR SIMULATION SOFTWARE
1 P013 INTRODUCING A NEW GENERATION OF RESERVOIR SIMULATION SOFTWARE JEAN-MARC GRATIEN, JEAN-FRANÇOIS MAGRAS, PHILIPPE QUANDALLE, OLIVIER RICOIS 1&4, av. Bois-Préau. 92852 Rueil Malmaison Cedex. France
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 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 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 informationBasin simulation for complex geological settings
Énergies renouvelables Production éco-responsable Transports innovants Procédés éco-efficients Ressources durables Basin simulation for complex geological settings Towards a realistic modeling P. Havé*,
More informationDell High-Performance Computing Clusters and Reservoir Simulation Research at UT Austin. http://www.dell.com/clustering
Dell High-Performance Computing Clusters and Reservoir Simulation Research at UT Austin Reza Rooholamini, Ph.D. Director Enterprise Solutions Dell Computer Corp. Reza_Rooholamini@dell.com http://www.dell.com/clustering
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 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 informationThe ever increasing importance of reservoir geomechanics
SPE special Interest Reservoir Group, Calgary March 26, 2014 The ever increasing importance of reservoir geomechanics Antonin (Tony) Settari TAURUS Reservoir Solutions Ltd., Calgary Professor Emeritus,
More informationReservoir Simulation
Reservoir Simulation Instructors: Duration: Level: Dr. Turgay Ertekin and Dr. Maghsood Abbaszadeh 5 days Basic - Intermediate Course Objectives and Description This five-day course is designed for participants
More informationMulticore Parallel Computing with OpenMP
Multicore Parallel Computing with OpenMP Tan Chee Chiang (SVU/Academic Computing, Computer Centre) 1. OpenMP Programming The death of OpenMP was anticipated when cluster systems rapidly replaced large
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 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 informationScientific Computing Programming with Parallel Objects
Scientific Computing Programming with Parallel Objects Esteban Meneses, PhD School of Computing, Costa Rica Institute of Technology Parallel Architectures Galore Personal Computing Embedded Computing Moore
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 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 informationParallel Programming at the Exascale Era: A Case Study on Parallelizing Matrix Assembly For Unstructured Meshes
Parallel Programming at the Exascale Era: A Case Study on Parallelizing Matrix Assembly For Unstructured Meshes Eric Petit, Loïc Thebault, Quang V. Dinh May 2014 EXA2CT Consortium 2 WPs Organization Proto-Applications
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 informationHETEROGENEOUS HPC, ARCHITECTURE OPTIMIZATION, AND NVLINK
HETEROGENEOUS HPC, ARCHITECTURE OPTIMIZATION, AND NVLINK Steve Oberlin CTO, Accelerated Computing US to Build Two Flagship Supercomputers SUMMIT SIERRA Partnership for Science 100-300 PFLOPS Peak Performance
More informationScalable Distributed Schur Complement Solvers for Internal and External Flow Computations on Many-Core Architectures
Scalable Distributed Schur Complement Solvers for Internal and External Flow Computations on Many-Core Architectures Dr.-Ing. Achim Basermann, Dr. Hans-Peter Kersken, Melven Zöllner** German Aerospace
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 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 informationMaximize Performance and Scalability of RADIOSS* Structural Analysis Software on Intel Xeon Processor E7 v2 Family-Based Platforms
Maximize Performance and Scalability of RADIOSS* Structural Analysis Software on Family-Based Platforms Executive Summary Complex simulations of structural and systems performance, such as car crash simulations,
More informationPerformance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi
Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi ICPP 6 th International Workshop on Parallel Programming Models and Systems Software for High-End Computing October 1, 2013 Lyon, France
More informationPerformance Characteristics of Large SMP Machines
Performance Characteristics of Large SMP Machines Dirk Schmidl, Dieter an Mey, Matthias S. Müller schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) Agenda Investigated Hardware Kernel Benchmark
More informationOpenMP Programming on ScaleMP
OpenMP Programming on ScaleMP Dirk Schmidl schmidl@rz.rwth-aachen.de Rechen- und Kommunikationszentrum (RZ) MPI vs. OpenMP MPI distributed address space explicit message passing typically code redesign
More informationBenchmark Tests on ANSYS Parallel Processing Technology
Benchmark Tests on ANSYS Parallel Processing Technology Kentaro Suzuki ANSYS JAPAN LTD. Abstract It is extremely important for manufacturing industries to reduce their design process period in order to
More informationHPC enabling of OpenFOAM R for CFD applications
HPC enabling of OpenFOAM R for CFD applications Towards the exascale: OpenFOAM perspective Ivan Spisso 25-27 March 2015, Casalecchio di Reno, BOLOGNA. SuperComputing Applications and Innovation Department,
More informationNumerical Calculation of Laminar Flame Propagation with Parallelism Assignment ZERO, CS 267, UC Berkeley, Spring 2015
Numerical Calculation of Laminar Flame Propagation with Parallelism Assignment ZERO, CS 267, UC Berkeley, Spring 2015 Xian Shi 1 bio I am a second-year Ph.D. student from Combustion Analysis/Modeling Lab,
More informationPerformance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware
Performance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware 1 / 17 Performance Evaluation of the XDEM framework on the OpenStack Cloud Computing Middleware X. Besseron 1 V.
More informationLarge Scale Parallel Reservoir Simulations on a Linux PC-Cluster 1
Large Scale Parallel Reservoir Simulations on a Linux PC-Cluster 1 Walid A. Habiballah and M. Ehtesham Hayder Petroleum Engineering Application Services Department Saudi Aramco, Dhahran 31311, Saudi Arabia
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 informationNexus. Reservoir Simulation Software DATA SHEET
DATA SHEET Nexus Reservoir Simulation Software OVERVIEW KEY VALUE Compute surface and subsurface fluid flow simultaneously for increased accuracy and stability Build multi-reservoir models by combining
More informationApplications to Computational Financial and GPU Computing. May 16th. Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61
F# Applications to Computational Financial and GPU Computing May 16th Dr. Daniel Egloff +41 44 520 01 17 +41 79 430 03 61 Today! Why care about F#? Just another fashion?! Three success stories! How Alea.cuBase
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 informationPrinciples of Big Data Algorithms and Application for Unconventional Oil and Gas Resources
SPE-172982-MS Principles of Big Data Algorithms and Application for Unconventional Oil and Gas Resources Avi Lin, Halliburton Copyright 2014, Society of Petroleum Engineers This paper was prepared for
More informationSpecialist Reservoir Engineering
Specialist Reservoir Engineering RPS Energy - a global energy consultancy RPS Energy is part of RPS Group, a FTSE 250 company with a turnover of $700m and 4500 employees. It is one of the world s leading
More informationDEPARTMENT OF PETROLEUM ENGINEERING Graduate Program (Version 2002)
DEPARTMENT OF PETROLEUM ENGINEERING Graduate Program (Version 2002) COURSE DESCRIPTION PETE 512 Advanced Drilling Engineering I (3-0-3) This course provides the student with a thorough understanding of
More informationGeothermal. . To reduce the CO 2 emissions a lot of effort is put in the development of large scale application of sustainable energy.
Geothermal Energy With increasing fossil fuel prices, geothermal energy is an attractive alternative energy source for district heating and industrial heating. In recent years the use of geothermal energy
More informationRESERVOIR GEOSCIENCE AND ENGINEERING
RESERVOIR GEOSCIENCE AND ENGINEERING APPLIED GRADUATE STUDIES at IFP School from September to December RGE01 Fundamentals of Geoscience I Introduction to Petroleum Geosciences, Sedimentology RGE02 Fundamentals
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 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 informationIntroduction to High Performance Cluster Computing. Cluster Training for UCL Part 1
Introduction to High Performance Cluster Computing Cluster Training for UCL Part 1 What is HPC HPC = High Performance Computing Includes Supercomputing HPCC = High Performance Cluster Computing Note: these
More informationFRIEDRICH-ALEXANDER-UNIVERSITÄT ERLANGEN-NÜRNBERG
FRIEDRICH-ALEXANDER-UNIVERSITÄT ERLANGEN-NÜRNBERG INSTITUT FÜR INFORMATIK (MATHEMATISCHE MASCHINEN UND DATENVERARBEITUNG) Lehrstuhl für Informatik 10 (Systemsimulation) Massively Parallel Multilevel Finite
More informationStoring of CO 2 offshore Norway, Criteria for evaluation of safe storage sites
Storing of CO 2 offshore Norway, Criteria for evaluation of safe storage sites Eva Halland Norwegian Petroleum Directorate Trondheim CCS Conference June 14-16, 2011 1 29.06.2011 Storing of CO 2 offshore
More informationCollecting and Analyzing Big Data for O&G Exploration and Production Applications October 15, 2013 G&G Technology Seminar
Eldad Weiss Founder and Chairman Collecting and Analyzing Big Data for O&G Exploration and Production Applications October 15, 2013 G&G Technology Seminar About Paradigm 700+ 26 700+ 29 7 15,000+ 15+ 200M+
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 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 informationDevelopment of Thermal Recovery Simulator for Hot Water Flooding
Paper ID 119 ABSTRACT Development of Thermal Recovery Simulator for Hot Water Flooding Shotaro Nihei, Masanori Kurihara Department of Resources and Environmental Engneering, Waseda University, Japan 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 informationNVIDIA CUDA Software and GPU Parallel Computing Architecture. David B. Kirk, Chief Scientist
NVIDIA CUDA Software and GPU Parallel Computing Architecture David B. Kirk, Chief Scientist Outline Applications of GPU Computing CUDA Programming Model Overview Programming in CUDA The Basics How to Get
More informationFPGA-based Multithreading for In-Memory Hash Joins
FPGA-based Multithreading for In-Memory Hash Joins Robert J. Halstead, Ildar Absalyamov, Walid A. Najjar, Vassilis J. Tsotras University of California, Riverside Outline Background What are FPGAs Multithreaded
More informationModeling and Simulation of Oil-Water Flows with Viscous Fingering in Heterogeneous Porous Media.
ACMA 2014 Modeling and Simulation of Oil-Water Flows with Viscous Fingering in Heterogeneous Porous Media. H. DJEBOURI 1, S. ZOUAOUI 1, K. MOHAMMEDI 2, and A. AIT AIDER 1 1 Laboratoire de Mécanique Structure
More informationLS-DYNA Best-Practices: Networking, MPI and Parallel File System Effect on LS-DYNA Performance
11 th International LS-DYNA Users Conference Session # LS-DYNA Best-Practices: Networking, MPI and Parallel File System Effect on LS-DYNA Performance Gilad Shainer 1, Tong Liu 2, Jeff Layton 3, Onur Celebioglu
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 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 informationSchool of Engineering Supplementary/Assessment Extension Examination List Sem 1, 2012
School of Engineering Supplementary/Assessment Extension Examination List Sem 1, 2012 Unit Code Unit Name Student ID X/DA 308572 ChE 312 Process Synthesis and Design I 14241343 X 308572 ChE 312 Process
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 informationParFUM: A Parallel Framework for Unstructured Meshes. Aaron Becker, Isaac Dooley, Terry Wilmarth, Sayantan Chakravorty Charm++ Workshop 2008
ParFUM: A Parallel Framework for Unstructured Meshes Aaron Becker, Isaac Dooley, Terry Wilmarth, Sayantan Chakravorty Charm++ Workshop 2008 What is ParFUM? A framework for writing parallel finite element
More informationScalable and High Performance Computing for Big Data Analytics in Understanding the Human Dynamics in the Mobile Age
Scalable and High Performance Computing for Big Data Analytics in Understanding the Human Dynamics in the Mobile Age Xuan Shi GRA: Bowei Xue University of Arkansas Spatiotemporal Modeling of Human Dynamics
More informationStreamline Integration using MPI-Hybrid Parallelism on a Large Multi-Core Architecture
Streamline Integration using MPI-Hybrid Parallelism on a Large Multi-Core Architecture David Camp (LBL, UC Davis), Hank Childs (LBL, UC Davis), Christoph Garth (UC Davis), Dave Pugmire (ORNL), & Kenneth
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 informationGraduate Courses in Petroleum Engineering
Graduate Courses in Petroleum Engineering PEEG 510 ADVANCED WELL TEST ANALYSIS This course will review the fundamentals of fluid flow through porous media and then cover flow and build up test analysis
More informationShale & Tight Reservoir Simulation. Jim Erdle - VP/USA & LA OCTOBER 2012
Shale & Tight Reservoir Simulation Jim Erdle - VP/USA & LA OCTOBER 2012 AGENDA How CMG s simulators are being used o Shale/Tight reservoir modelling features o Shale/Tight reservoir modelling workflows
More informationAnalysis of Oil Production Behavior for the Fractured Basement Reservoir Using Hybrid Discrete Fractured Network Approach
Advances in Petroleum Exploration and Development Vol. 5, No. 1, 2013, pp. 63-70 DOI:10.3968/j.aped.1925543820130501.1068 ISSN 1925-542X [Print] ISSN 1925-5438 [Online] www.cscanada.net www.cscanada.org
More informationEXPLORATION TECHNOLOGY REQUIRES A RADICAL CHANGE IN DATA ANALYSIS
EXPLORATION TECHNOLOGY REQUIRES A RADICAL CHANGE IN DATA ANALYSIS EMC Isilon solutions for oil and gas EMC PERSPECTIVE TABLE OF CONTENTS INTRODUCTION: THE HUNT FOR MORE RESOURCES... 3 KEEPING PACE WITH
More informationGPGPU acceleration in OpenFOAM
Carl-Friedrich Gauß Faculty GPGPU acceleration in OpenFOAM Northern germany OpenFoam User meeting Braunschweig Institute of Technology Thorsten Grahs Institute of Scientific Computing/move-csc 2nd October
More informationFAN group includes NAMVARAN UPSTREAM,
INTRODUCTION Reservoir Simulation FAN group includes NAMVARAN UPSTREAM, FOLOWRD Industrial Projects and Azmouneh Foulad Co. Which of these companies has their own responsibilities. NAMVARAN is active in
More informationIterative Solvers for Linear Systems
9th SimLab Course on Parallel Numerical Simulation, 4.10 8.10.2010 Iterative Solvers for Linear Systems Bernhard Gatzhammer Chair of Scientific Computing in Computer Science Technische Universität München
More informationOverview on Modern Accelerators and Programming Paradigms Ivan Giro7o igiro7o@ictp.it
Overview on Modern Accelerators and Programming Paradigms Ivan Giro7o igiro7o@ictp.it Informa(on & Communica(on Technology Sec(on (ICTS) Interna(onal Centre for Theore(cal Physics (ICTP) Mul(ple Socket
More informationHierarchically Parallel FE Software for Assembly Structures : FrontISTR - Parallel Performance Evaluation and Its Industrial Applications
CO-DESIGN 2012, October 23-25, 2012 Peing University, Beijing Hierarchically Parallel FE Software for Assembly Structures : FrontISTR - Parallel Performance Evaluation and Its Industrial Applications Hiroshi
More informationScaling LS-DYNA on Rescale HPC Cloud Simulation Platform
Scaling LS-DYNA on Rescale HPC Cloud Simulation Platform Joris Poort, President & CEO, Rescale, Inc. Ilea Graedel, Manager, Rescale, Inc. 1 Cloud HPC on the Rise 1.1 Background Engineering and science
More informationWhat we know: shale gas as a promising global energy resource for the future. What we need to know: the scientific challenges.
Laboratory of Soil Mechanics,Chair Gaz Naturel - Petrosvibri LMS-EPFL Prof. L. Laloui Gas Opportunities, Challenges and Achievements - «EFFICIENCE 21», Automne 2013... Geomechanics: a one-way road toward
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 informationYousef Saad University of Minnesota Computer Science and Engineering. CRM Montreal - April 30, 2008
A tutorial on: Iterative methods for Sparse Matrix Problems Yousef Saad University of Minnesota Computer Science and Engineering CRM Montreal - April 30, 2008 Outline Part 1 Sparse matrices and sparsity
More informationFast Multipole Method for particle interactions: an open source parallel library component
Fast Multipole Method for particle interactions: an open source parallel library component F. A. Cruz 1,M.G.Knepley 2,andL.A.Barba 1 1 Department of Mathematics, University of Bristol, University Walk,
More informationSPE 51885. Abstract. Copyright 1999, Society of Petroleum Engineers, Inc.
SPE 51885 A Fully Implicit Parallel EOS Compositional Simulator for Large Scale Reservoir Simulation. P. Wang, S. Balay 1, K.Sepehrnoori, J. Wheeler, J. Abate, B. Smith 1, G.A. Pope. The University of
More informationLarge-Data Software Defined Visualization on CPUs
Large-Data Software Defined Visualization on CPUs Greg P. Johnson, Bruce Cherniak 2015 Rice Oil & Gas HPC Workshop Trend: Increasing Data Size Measuring / modeling increasingly complex phenomena Rendering
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 informationAn Introduction to Parallel Computing/ Programming
An Introduction to Parallel Computing/ Programming Vicky Papadopoulou Lesta Astrophysics and High Performance Computing Research Group (http://ahpc.euc.ac.cy) Dep. of Computer Science and Engineering European
More informationThe Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System
The Uintah Framework: A Unified Heterogeneous Task Scheduling and Runtime System Qingyu Meng, Alan Humphrey, Martin Berzins Thanks to: John Schmidt and J. Davison de St. Germain, SCI Institute Justin Luitjens
More informationChapter 2 Parallel Architecture, Software And Performance
Chapter 2 Parallel Architecture, Software And Performance UCSB CS140, T. Yang, 2014 Modified from texbook slides Roadmap Parallel hardware Parallel software Input and output Performance Parallel program
More informationClusters: Mainstream Technology for CAE
Clusters: Mainstream Technology for CAE Alanna Dwyer HPC Division, HP Linux and Clusters Sparked a Revolution in High Performance Computing! Supercomputing performance now affordable and accessible Linux
More informationArchitectures for Big Data Analytics A database perspective
Architectures for Big Data Analytics A database perspective Fernando Velez Director of Product Management Enterprise Information Management, SAP June 2013 Outline Big Data Analytics Requirements Spectrum
More informationThe Application of a Black-Box Solver with Error Estimate to Different Systems of PDEs
The Application of a Black-Bo Solver with Error Estimate to Different Systems of PDEs Torsten Adolph and Willi Schönauer Forschungszentrum Karlsruhe Institute for Scientific Computing Karlsruhe, Germany
More informationInteractive comment on A parallelization scheme to simulate reactive transport in the subsurface environment with OGS#IPhreeqc by W. He et al.
Geosci. Model Dev. Discuss., 8, C1166 C1176, 2015 www.geosci-model-dev-discuss.net/8/c1166/2015/ Author(s) 2015. This work is distributed under the Creative Commons Attribute 3.0 License. Geoscientific
More informationRetargeting PLAPACK to Clusters with Hardware Accelerators
Retargeting PLAPACK to Clusters with Hardware Accelerators Manuel Fogué 1 Francisco Igual 1 Enrique S. Quintana-Ortí 1 Robert van de Geijn 2 1 Departamento de Ingeniería y Ciencia de los Computadores.
More informationDavid Rioja Redondo Telecommunication Engineer Englobe Technologies and Systems
David Rioja Redondo Telecommunication Engineer Englobe Technologies and Systems About me David Rioja Redondo Telecommunication Engineer - Universidad de Alcalá >2 years building and managing clusters UPM
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 informationAdapting scientific computing problems to cloud computing frameworks Ph.D. Thesis. Pelle Jakovits
Adapting scientific computing problems to cloud computing frameworks Ph.D. Thesis Pelle Jakovits Outline Problem statement State of the art Approach Solutions and contributions Current work Conclusions
More informationNew technologies of enhanced oil recovery
New technologies of enhanced oil recovery Stanisław Rychlicki 1, Jerzy Stopa and Paweł Wojnarowski Nové technológie zvýšenia ťažby ropy It is known from the literature that up to 27 % of oil in oilfields
More informationHigh Performance Matrix Inversion with Several GPUs
High Performance Matrix Inversion on a Multi-core Platform with Several GPUs Pablo Ezzatti 1, Enrique S. Quintana-Ortí 2 and Alfredo Remón 2 1 Centro de Cálculo-Instituto de Computación, Univ. de la República
More informationHP ProLiant SL270s Gen8 Server. Evaluation Report
HP ProLiant SL270s Gen8 Server Evaluation Report Thomas Schoenemeyer, Hussein Harake and Daniel Peter Swiss National Supercomputing Centre (CSCS), Lugano Institute of Geophysics, ETH Zürich schoenemeyer@cscs.ch
More informationEVALUATION OF WELL TESTS USING RADIAL COMPOSITE MODEL AND DIETZ SHAPE FACTOR FOR IRREGULAR DRAINAGE AREA. Hana Baarová 1
The International Journal of TRANSPORT & LOGISTICS Medzinárodný časopis DOPRAVA A LOGISTIKA Mimoriadne číslo 8/2010 ISSN 1451 107X EVALUATION OF WELL TESTS USING RADIAL COMPOSITE MODEL AND DIETZ SHAPE
More informationJean-Pierre Panziera Teratec 2011
Technologies for the future HPC systems Jean-Pierre Panziera Teratec 2011 3 petaflop systems : TERA 100, CURIE & IFERC Tera100 Curie IFERC 1.25 PetaFlops 256 TB ory 30 PB disk storage 140 000+ Xeon cores
More informationherramienta para la ingeniería
www.bsc.es Supercomputación una herramienta para la ingeniería José Mª Cela CASE Dept. Director josem.cela@bsc.es CASE Departament We develop HPC software for science and industry 2 What kind of simulations
More informationMesh Generation and Load Balancing
Mesh Generation and Load Balancing Stan Tomov Innovative Computing Laboratory Computer Science Department The University of Tennessee April 04, 2012 CS 594 04/04/2012 Slide 1 / 19 Outline Motivation Reliable
More informationICES REPORT 12-01. January 2012. Reza Tavakoli, Gergina Pencheva, Mary F. Wheeler, Benjamin Ganis
ICES REPORT 12-01 January 2012 Petroleum Reservoir Parameter Estimation and Uncertainty Assessment with the Parallel Ensemble Based Framework Coupled with IPARS by Reza Tavakoli, Gergina Pencheva, Mary
More informationIntroduction to GPU Programming Languages
CSC 391/691: GPU Programming Fall 2011 Introduction to GPU Programming Languages Copyright 2011 Samuel S. Cho http://www.umiacs.umd.edu/ research/gpu/facilities.html Maryland CPU/GPU Cluster Infrastructure
More information