GTC 2012 Program Guide - GPU Technology Conference

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C++ Accelerated Massive Parallelism (C++ AMP) �� What is C++ AMP, how can it help me, and where can I get it? C++ AMP is a key new C++ language feature plus an STL-like library. It's designed to help you increase the performance of �� MICROSOFT Ad? What platforms and hardware does C++ AMP support? �� What new language feature does C++ AMP introduce? Microsoft added the restrict(amp)� �� function can be executed on a C++ AMP accelerator. The restrict keyword instructs the compiler to statically check that the ��void myFunc() restrict(amp) {…} �� for purposes that are unrelated to C++ AMP. What new classes (APIs) does C++ AMP introduce? �� What does C++ AMP code look like? �� void AddArrays(int n, int m, int * pA, int * pB, int * pSum) { concurrency::array_view a(n, m, pA), b(n, m, pB), sum(n, m, pSum); concurrency::parallel_for_each(sum.extent, [=](concurrency::index i) restrict(amp) { sum[i] = a[i] + b[i]; }); } Follow our blog: �� Ask questions: ��
SESSION INFORMATION WEDNESDAY, MAY 16 WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM N S0010 Towards Routine Microsecond Molecular Dynamics Simulations on Commodity Hardware The original AMBER 11 provided performance on one GPU equivalent to an 8 node cluster and almost 60ns/day for 8 GPUs running the JAC production benchmark without additional approximations outstripping the performance of all conventional supercomputers. Here we describe further optimization of the code, coupled with hardware and software advances on the part of NVIDIA, that provides performance of >50ns/day on a single GPU with multiple GPUs providing simulation rates on systems the size of DHFR approaching a microsecond per day. This brings performance levels on desktops and commodity hybrid clusters to levels previously only considered possible using custom silicon. Speaker(s): Ross Walker (Assistant Professor, University of California San Diego) Topic(s): Molecular Dynamics, Life Sciences (Advanced) WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM A8 S0017 4D Medical Image Processing with CUDA Learn how to do 4D image processing with CUDA, especially for medical imaging applications. In this session we will give a couple of examples of how 4D image processing can take advantage of the computational power of the GPU. We will present how to use the GPU for functional magnetic resonance imaging (fMRI) analysis and true 4D image denoising. Most of our examples use the GPU both to speedup the analysis and to visualize the results. Speaker(s): Anders Eklund (PhD Student, Linköping University) Topic(s): Medical Imaging & Visualization, Audio, Image and Video Processing, Neuroscience, Visualization (Advanced) WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM B S0072 GPU-Enabled Spatiotemporal Model of Stochastic Cardiac Calcium Dynamics and Arrhythmias Calcium ions play a central role controlling the contraction of the heart to pump blood. This requires tight regulation of cellular calcium dynamics which depends upon over 1,000,000 calcium channels that open and close stochastically and have a very specific spatial arrangement. In the School of Systems Biology at George Mason University, CUDA technology coupled to novel algorithms for Monte Carlo simulation have made possible this computationally expensive spatiotemporal model of calcium dynamics in the heart muscle cell to study the regulation of calcium dynamics and what aberrations leads to cardiac arrhythmia. Speaker(s): Mohsin Jafri (Professor and Chair, George Mason University), Hoang-Tron Minh Tuan (PhD Student, George Mason University) Topic(s): Life Sciences, Bioinformatics (Beginner) WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM A7 S0171 Numerical Modeling Of 3D Anisotropic Seismic Wave Propagation On MultiGPU Platforms We present an efficient and accurate numerical algorithm for the simulation of seismic experiments. The basis of the approach is a heterogeneous spectral element method implemented on MultiGPU applied to anisotropic elastic wave equation. The approach was designed to simulate wave propagation in 3D arbitrary anisotropic elastic media. Due to the use of an unstructured grid, the spectral element algorithm enables handling complicate geometries of the layers. We discuss results and computational efforts of simulation on MultiGPU platform. Several aspects of the code implementation are considered: optimal domain decomposition, data transfers between GPU by means of P2P and UVA, etc. Speaker(s): Denis Sabitov (Schlumberger) Topic(s): Energy Exploration, Algorithms & Numerical Techniques, Supercomputing, Molecular Dynamics (Intermediate) WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM M S0253 Sensor Processing with Rugged Kepler GPUs (Presented by GE Intelligent Platforms) Swimming in sensors and drowning in data? Turn the tide on high-bandwidth sensors with rugged next-generation Kepler GPUs from NVIDIA. See how we deploy Kepler into the most extreme of environments, providing GPGPU capabilities onboard platforms where SWaP and GFLOPS/watt is key. Dig into four realtime CUDA sensor processing applications - Hyperspectral Imaging,Wide-Area Surveillance, 360° Situational Awareness, and GSM Cellular SIGINT. Discuss the CUDA algorithms, interconnects, and rugged platforms behind each. Learn how we utilize GPUDirect and realtime Linux for improved latency and determinism. Speaker(s): Dustin Franklin (GPGPU Applications Engineer, GE Intelligent Platforms) Topic(s): Audio, Image and Video Processing, General Interest, Machine Vision, Computer Vision (Intermediate) WEDNESDAY, MAY 16, 09:00 (25 MINUTES) MARRIOTT BALLROOM 3 S0289 Fine-Grained Parallel Preconditioners for Fast GPU-based Solvers Leverage the power of GPUs for efficient parallel solution of large sparse linear systems of equations by means of fine-grained and scalable parallel preconditioners. In this session we describe parallel preconditioners for GPUs based on multicolor re-ordering for Gauss-Seidel-type and ILU-type preconditioners as well as approximate inverse (FSAI) preconditioners. With the power(q)pattern method we detail a novel method for controlling the fill-in pattern of ILU(p) factorizations that introduces a high degree of parallelism in the preconditioning phase. We demonstrate significant improvements with respect to solver time for various problem scenarios and different Krylov-type solvers. Speaker(s): Dimitar Lukarski (Research Associate, Karlsruhe Institute of Technology (KIT)), Jan-Philipp Weiss (Junior Professor, Karlsruhe Institute of Technology) Topic(s): Algorithms & Numerical Techniques (Advanced) WEDNESDAY, MAY 16, 09:00 (50 MINUTES) ROOM A1 S0353 Programming Multi-GPU’s for Scalable Rendering Multi-GPU configurations are becoming common affordable options for OpenGL applications to scale performance, data size, display size and image quality. We show how to structure your application for multi-gpu rendering by using multiple threads and OpenGL contexts and handle the synchronization and data transfer. We conclude with a discussion of how to implement common parallel rendering approaches such as sort-first, sort-last and hybrid techniques. 47 CONFERENCE GUIDE WEDNESDAY
Page 1 and 2: PRESENTED BY PLATINUM SPONSORS MAY
Page 3 and 4: WELCOME TO GTC Dear GTC Attendees,
Page 5 and 6: IMPORTANT INFORMATION If there is a
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Page 9 and 10: SUNDAY, MAY 13 08:30 to 17:35 InPar
Page 11 and 12: Welcome to NVIDIA’s Emerging Comp
Page 13 and 14: 14:00 to 14:50 S2003 Emerging Compa
Page 15 and 16: CEO ON STAGE LISTING BIODIGITAL Bio
Page 17 and 18: MERSIVE Since it was founded in 200
Page 19 and 20: REALVIEW IMAGING LTD. RealView Imag
Page 21 and 22: CONFERENCE GUIDE 19
Page 23 and 24: AGENDA WEDNESDAY, MAY 16 Plenary Se
Page 25 and 26: SESSION INFORMATION - PRE-CONFERENC
Page 27 and 28: models with companion tools (e.g. f
Page 29 and 30: SESSION INFORMATION TUESDAY, MAY 15
Page 31 and 32: to NVIDIA’s GPUs. We summarize th
Page 33 and 34: Speaker(s): James Lin (Assistant Pr
Page 35 and 36: with extremely high memory bandwidt
Page 37 and 38: presenters showcasing research code
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Page 45 and 46: Speaker(s): Mark Harris (Chief Tech
Page 47: Speaker(s): Nathan Bell (Senior Res
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Page 55 and 56: collective behavior, helping reveal
Page 61: Speaker(s): Bjoern Landmann (Develo
Page 64 and 65: WEDNESDAY significantly beyond the
Page 66 and 67: WEDNESDAY Speaker(s): Cliff Woolley
Page 68 and 69: WEDNESDAY WEDNESDAY, MAY 16, 17:00
Page 71 and 72: SESSION INFORMATION THURSDAY, MAY 1
Page 73 and 74: THURSDAY, MAY 17, 09:30 (25 MINUTES
Page 75: applications. Furthermore guideline
Page 78 and 79: THURSDAY Speaker(s): Peter Zaspel (
Page 80 and 81: THURSDAY porting a numerical code t
Page 82 and 83: THURSDAY THURSDAY, MAY 17, 16:00 (5
Page 84 and 85: GPU Consolidation and Virtualizatio
Page 86 and 87: POSTER LISTINGS AN09 - Parallel Pro
Page 88 and 89: POSTER LISTINGS accuracy. Beside th
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POSTER LISTINGS mesh. To this end,
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POSTER LISTINGS speed enhancement w
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POSTER LISTINGS this work addresses
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What you need to know. Now. Dr. Dob
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SPEAKERS AND PANELISTS Arutyun Avet
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SPEAKERS AND PANELISTS with emphasi
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SPEAKERS AND PANELISTS computationa
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SPEAKERS AND PANELISTS Iain Couzin
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SPEAKERS AND PANELISTS Concept and
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SPEAKERS AND PANELISTS GE as a GPGP
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SPEAKERS AND PANELISTS h Session(s)
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SPEAKERS AND PANELISTS purpose comp
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SPEAKERS AND PANELISTS Osman Kent C
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SPEAKERS AND PANELISTS active contr
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SPEAKERS AND PANELISTS Rainald Lohn
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SPEAKERS AND PANELISTS Naoya Maruya
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SPEAKERS AND PANELISTS models, at A
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SPEAKERS AND PANELISTS Taro Okamoto
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SPEAKERS AND PANELISTS Loukas Petri
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SPEAKERS AND PANELISTS Erwin Roth R
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SPEAKERS AND PANELISTS Arroyo Video
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SPEAKERS AND PANELISTS John Stone S
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SPEAKERS AND PANELISTS Hoang-Tron M
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SPEAKERS AND PANELISTS Elmar Westph
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SPEAKERS AND PANELISTS Hongwei Zhou
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SPONSORS AND EXHIBITORS PLATINUM SP
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SPONSORS AND EXHIBITORS GOLD SPONSO
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SPONSORS AND EXHIBITORS PLATINUM ME
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SPONSORS AND EXHIBITORS Bright Comp
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SPONSORS AND EXHIBITORS MBA Science
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SPONSORS AND EXHIBITORS Polywell PQ
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SPONSORS AND EXHIBITORS Ubitus Inc.
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STAY EDUCATED! GTC is comprised of
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FIRST FLOOR TO ST. CLAIRE HOTEL BAL
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GTC 2012 Program Guide - GPU Technology Conference

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