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GPU ComputingMotivation
© NVIDIA Corporation 2007
Computing Challenge
graphic
Task Computing Data Computing
© NVIDIA Corporation 2007
Extreme Growth in Raw Data
Source: John Bates, NOAA Nat. Climate Center
NOAA Weather Data
Peta
byte
s
Source: Alexa, YouTube 2006
YouTube Bandwidth Growth
Mill
ions
Source: Hedburg, CPI, Walmart
Walmart Transaction Tracking
Mill
ions
Source: Jim Farnsworth, BP May 2005
BP Oil and Gas Active Data
Tera
byte
s
NOAA NASA Weather Data in Petabytes
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2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017
© NVIDIA Corporation 2007
Computational Horsepower
GPU is a massively parallel computation engineHigh memory bandwidth (5-10x CPU)High floating-point performance (5-10x CPU)
© NVIDIA Corporation 2007
Benchmarking: CPU vs. GPU Computing
G80 vs. Core2 Duo 2.66 GHzMeasured against commercial CPU benchmarks when possible
“Free” Massively Parallel Processors
It’s not science fiction, it’s just funded by them
Asst Master Chief Harvard
SuccessStories
© NVIDIA Corporation 2007
Success Stories: Data to DesignAcceleware EM Field simulation technology for the GPU
3D Finite-Difference and Finite-Element (FDTD)
Modeling of:
Cell phone irradiation
MRI Design / Modeling
Printed Circuit Boards
Radar Cross Section (Military)
Pacemaker with Transmit Antenna10X
1X
4 GPUs2 GPUs1 GPUCPU3.2 GHz
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Performance (Mcells/s)
20X
5X
© NVIDIA Corporation 2007
EvolvedMachines130X Speed upSimulate brain circuitrySensory computing: vision, olfactory
EvolvedMachines
© NVIDIA Corporation 2007
10X with MATLAB CPU+GPU
Pseudo-spectral simulation of 2D Isotropic turbulence
Matlab: Language of Science
http://www.amath.washington.edu/courses/571-winter-2006/matlab/FS_2Dturb.m
http://developer.nvidia.com/object/matlab_cuda.html
© NVIDIA Corporation 2007
MATLAB Example:Advection of an elliptic vortex
256x256 mesh, 512 RK4 steps, Linux, MATLAB filehttp://www.amath.washington.edu/courses/571-winter-2006/matlab/FS_vortex.m
Matlab168 seconds
Matlab with CUDA(single precision FFTs)20 seconds
© NVIDIA Corporation 2007
MATLAB Example:Pseudo-spectral simulation of 2D Isotropic turbulence
MATLAB 992 seconds
MATLAB with CUDA(single precision FFTs)93 seconds
512x512 mesh, 400 RK4 steps, Windows XP, MATLAB filehttp://www.amath.washington.edu/courses/571-winter-2006/matlab/FS_2Dturb.m
© NVIDIA Corporation 2007
NAMD/VMD Molecular Dynamics
http://www.ks.uiuc.edu/Research/vmd/projects/ece498/lecture/
240X speedup Computational biology
© NVIDIA Corporation 2007
Molecular Dynamics Example
Case study: molecular dynamics research at U. Illinois Urbana-Champaign
(Scientist-sponsored) course project for CS 498AL: Programming Massively Parallel Multiprocessors (Kirk/Hwu)Next slides stolen from a nice description of problem, algorithms, and iterative optimization process available at:
http://www.ks.uiuc.edu/Research/vmd/projects/ece498/lecture/
© NVIDIA Corporation 2007
© NVIDIA Corporation 2007
Molecular Modeling: Ion Placement
Biomolecular simulations attempt to replicate in vivoconditions in silico.Model structures are initially constructed in vacuumSolvent (water) and ions are added as necessary for the required biological conditionsComputational requirements scale with the size of the simulated structure
© NVIDIA Corporation 2007
Evolution of Ion Placement CodeFirst implementation was sequentialVirus structure with 10^6 atoms would require 10 CPU daysTuned for Intel C/C++ vectorization+SSE, ~20x speedupParallelized /w pthreads: high data parallelism = linear speedupParallelized GPU accelerated implementation: 3 GeForce 8800GTX cards outrun ~300 Itanium2 CPUs!Virus structure now runs in 25 seconds on 3 GPUs!Further speedups should still be possible…
© NVIDIA Corporation 2007
Multi-GPU CUDA Coulombic Potential Map Performance
Host: Intel Core 2 Quad, 8GB RAM, ~$3,0003 GPUs: NVIDIA GeForce 8800GTX, ~$550 each32-bit RHEL4 Linux (want 64-bit CUDA!!)235 GFLOPS per GPU for current version of coulombic potential map kernel705 GFLOPS total for multithreaded multi-GPU version Three GeForce 8800GTX GPUs
in a single machine, cost ~$4,650
ProfessorPartnership
© NVIDIA Corporation 2007
NVIDIA Professor Partnership
Support faculty research & teaching effortsSmall equipment gifts (1-2 GPUs) Significant discounts on GPU purchases
Especially Quadro, Tesla equipmentUseful for cost matching
Research contracts Small cash grants (typically ~$25K gifts)Medium-scale equipment donations (10-30 GPUs)
Informal proposals, reviewed quarterlyFocus areas: GPU computing, especially with an educational mission or component
http://www.nvidia.com/page/professor_partnership.html
Easy
Competitive
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