Tesla 101. 2 CUDA GPU Accelerates Computing The Right Processor for the Right Task.

Slides:



Advertisements
Similar presentations
$100 $400 $300$200$400 $200$100$100$400 $200$200$500 $500$300 $200$500 $100$300$100$300 $500$300$400$400$500.
Advertisements

Presentation Outline A word or two about our program Our HPC system acquisition process Program benchmark suite Evolution of benchmark-based performance.
Founded in 2010: UCL, Southampton, Oxford and Bristol Key Objectives of the Consortium: Prove the concept of shared, regional e-infrastructure services.
Floating-Point Data Compression at 75 Gb/s on a GPU Molly A. O’Neil and Martin Burtscher Department of Computer Science.
GPU Programming using BU Shared Computing Cluster
HPC USER FORUM ISV PANEL April 2010 Dearborn, MI.
HIGH-PERFORMANCE COMPUTING Dr. Mayez Al-Mouhamed Professor, Computer Engineering Department King Fahd University of Petroleum & Minerals.
June 9, DCSE Delft Centre for Computational Science and Engineering Delft Centre for Computational Science and Engineering.
GPU Computing with Hartford Condor Week 2012 Bob Nordlund.
GPGPU Introduction Alan Gray EPCC The University of Edinburgh.
HPCC Mid-Morning Break High Performance Computing on a GPU cluster Dirk Colbry, Ph.D. Research Specialist Institute for Cyber Enabled Discovery.
May 8th, 2012 Higher Ed & Research. Molecular Dynamics Applications Overview AMBER NAMD GROMACS LAMMPS Sections Included * * In fullscreen mode, click.
National Center for Supercomputing Applications University of Illinois at Urbana-Champaign Porting, Benchmarking, and Optimizing Computational Material.
Why GPU Computing. GPU CPU Add GPUs: Accelerate Science Applications © NVIDIA 2013.
FSOSS Dr. Chris Szalwinski Professor School of Information and Communication Technology Seneca College, Toronto, Canada GPU Research Capabilities.
OpenFOAM on a GPU-based Heterogeneous Cluster
HIGH PERFORMANCE COMPUTING ENVIRONMENT The High Performance Computing environment consists of high-end systems used for executing complex number crunching.
Weekly Report Start learning GPU Ph.D. Student: Leo Lee date: Sep. 18, 2009.
High Performance Computing (HPC) at Center for Information Communication and Technology in UTM.
1 AppliedMicro X-Gene ® ARM Processors Optimized Scale-Out Solutions for Supercomputing.
GPGPU overview. Graphics Processing Unit (GPU) GPU is the chip in computer video cards, PS3, Xbox, etc – Designed to realize the 3D graphics pipeline.
HPCC Mid-Morning Break Dirk Colbry, Ph.D. Research Specialist Institute for Cyber Enabled Discovery Introduction to the new GPU (GFX) cluster.
Institutional Research Computing at WSU: Implementing a community-based approach Exploratory Workshop on the Role of High-Performance Computing in the.
International conference “Modern problems of computational mathematics and mathematical modeling”, dedicated to the 90th anniversary of academician G.I.Marchuk.
Motivation “Every three minutes a woman is diagnosed with Breast cancer” (American Cancer Society, “Detailed Guide: Breast Cancer,” 2006) Explore the use.
Training Program on GPU Programming with CUDA 31 st July, 7 th Aug, 14 th Aug 2011 CUDA Teaching UoM.
Statistical Performance Analysis for Scientific Applications Presentation at the XSEDE14 Conference Atlanta, GA Fei Xing Haihang You Charng-Da Lu July.
MATLAB and the GPU Who is AccelerEyes? What’s a GPU?
Low-Latency Accelerated Computing on GPUs
By Arun Bhandari Course: HPC Date: 01/28/12. GPU (Graphics Processing Unit) High performance many core processors Only used to accelerate certain parts.
GPU Computing April GPU Outpacing CPU in Raw Processing GPU NVIDIA GTX cores 1.04 TFLOPS CPU GPU CUDA Architecture Introduced DP HW Introduced.
1 © 2012 The MathWorks, Inc. Parallel computing with MATLAB.
Taking the Complexity out of Cluster Computing Vendor Update HPC User Forum Arend Dittmer Director Product Management HPC April,
Programming for Hybrid Architectures
GPU Architectural Considerations for Cellular Automata Programming A comparison of performance between a x86 CPU and nVidia Graphics Card Stephen Orchowski,
GPU Architecture and Programming
HPCMP Benchmarking Update Cray Henry April 2008 Department of Defense High Performance Computing Modernization Program.
Personal Chris Ward CS147 Fall  Recent offerings from NVIDA show that small companies or even individuals can now afford and own Super Computers.
By Dirk Hekhuis Advisors Dr. Greg Wolffe Dr. Christian Trefftz.
1)Leverage raw computational power of GPU  Magnitude performance gains possible.
SAN DIEGO SUPERCOMPUTER CENTER Advanced User Support Project Overview Adrian E. Roitberg University of Florida July 2nd 2009 By Ross C. Walker.
What is MCSR? Who is MCSR? What Does MCSR Do? Who Does MCSR Serve? What Kinds of Accounts? Why Does Mississippi Need Supercomputers? What Kinds of Research?
Implementation and Optimization of SIFT on a OpenCL GPU Final Project 5/5/2010 Guy-Richard Kayombya.
Shangkar Mayanglambam, Allen D. Malony, Matthew J. Sottile Computer and Information Science Department Performance.
Integration center of the cyberinfrastructure of NRC “KI” Dubna, 16 july 2012 V.E. Velikhov V.A. Ilyin E.A. Ryabinkin.
SAN DIEGO SUPERCOMPUTER CENTER Advanced User Support Project Overview Thomas E. Cheatham III University of Utah Jan 14th 2010 By Ross C. Walker.
© David Kirk/NVIDIA and Wen-mei W. Hwu, ECE408/CS483, University of Illinois, Urbana-Champaign 1 Graphic Processing Processors (GPUs) Parallel.
GPU Accelerated Vessel Segmentation Using Laplacian Eigenmaps Lin Cheng, Hyunsu Cho and Peter A. Yoon Trinity College.
GPGPU introduction. Why is GPU in the picture Seeking exa-scale computing platform Minimize power per operation. – Power is directly correlated to the.
Porting Irregular Reductions on Heterogeneous CPU-GPU Configurations Xin Huo Vignesh T. Ravi Gagan Agrawal Department of Computer Science and Engineering,
Graphic Processing Units Presentation by John Manning.
Sobolev(+Node 6, 7) Showcase +K20m GPU Accelerator.
August Accelerated Computing CPU Optimized for Serial Tasks GPU Accelerator Optimized for Parallel Tasks 10x Performance 5x Energy Efficiency.
HPC Design of Ion Based Molecular Clusters A. Bende, C. Varodi, T. M. Di Palma INCDTIM – Istituto Motori-CNR, Napoli, Italy Romania-JINR cooperation framework.
29 th of March 2016 HPC Applications and Parallel Computing Paradigms.
What’s ? Laurent Vanel High Performance Infrastructure Specialist.
GPGPU use cases from the MoBrain community
Tesla P100 Performance Guide
HPC Roadshow Overview of HPC systems and software available within the LinkSCEEM project.
GPU Computing Jan Just Keijser Nikhef Jamboree, Utrecht
POTENTIAL EGEE APPLICATIONS IN THE CZECH REPUBLIC INITIAL IDEAS
Peng Wang, Ph.D. HPC Developer Technology, NVIDIA
…updates… 9/19/2018.
A new business imperative – Oil & Gas
IDC HPC User Forum 09/08/2009 Manuel Hoffmann, Vice President, Channel Development /15/2018.
The C&C Center Three Major Missions: In This Presentation:
Computer simulation studies of forced rupture kinetics of
Parallel computing in Computational chemistry
Rui Oliveira University of Minho & INESC TEC.
Accelerating New Science
Presentation transcript:

Tesla 101

2 CUDA GPU Accelerates Computing The Right Processor for the Right Task

3 How CPUs and GPUs Work void serial_function(… ) {... } void parallel_function(float... ) {... } void main( ) {... parallel_function >(..); serial_function(..);... } CUDA Application Code Heavy parallel workload on the GPU Other serial routines on the CPU

GPU Performance Far Outstrips CPUs Double Precision: NVIDIA GPU Double Precision: x86 CPU

5 Much More Power Efficient Tesla GPUs CPU Only

6 Transformational for Customers 4 Months 2 Years $1M Budget ~120 Compute Nodes~45 CPU + GPU Nodes Time to Discovery

7 #1 Numerical Computation MATLAB #1 Molecular Dynamics AMBER #1 Engineering Simulation ANSYS #1 3D DCC 3ds Max

Science Category GPU Port Complete GPU Port Started & Results Published Early GPU Port Molecular Dynamics NAMD AMBER DL_POLY CHARMM GROMACS Chemistry LAMMPS MOLPRO GAMESS CPMD DESMOND GAUSSIAN Fluid Dynamics OpenFOAM S3D FEFLO ANSYS CFD Structural Mechanics ANSYS Mechanical Simulia Abaqus/Std (beta) CTH LS-DYNA Implicit MSC Marc PAM-CRASH IMPLICIT MSC Nastran Earth Science WRF HOMME, HYCOM COSMO-2, PFLOTRAN ASUCA CCSM/CESM Material Science PARATEC LAMMPS PWscf CPMD VASP GAUSSIAN Oil & Gas Schlumberger PetrelVoxelGeo Paradigm Analytics Matlab Mathworks Others GADGET2 GTC MILC DENOVO Leading HPC Applications Ramping

9 CUDA Taking HPC by Storm 100,000 Active GPU Developers 400 Universities Teaching CUDA Clusters Worldwide 35+ CUDA Research Centers 200,000,000 CUDA GPUs Deployed 100% OEMs offer CUDA GPUs