NVIDIA GPU Computing Theater

 
 
Tuesday, November 17, 2009
11:00 Accelerating Market Value-at-Risk Estimation on GPUs
Matthew Dixon, University of California Davis
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12:00 Turostream: A CFD Solver for Many-Core Processors

Tobias Brandvik, Whittle Laboratory, University of Cambridge
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1:00 GPU Acceleration: a Fad or the Yellow Brick Road onto Exascale?
Professor Satoshi Matsuoka, Global Scientific Information and Computing Center (GSIC) of Tokyo Institute of Technology (Tokyo Tech)
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2:00 A Powerful IDE for GPU Computing on Windows: Code Named Nexus

Stephen Jones, NVIDIA
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3:00 Languages, APIs and Tools for GPU Computing on the CUDA Architecture
Will Ramey, NVIDIA
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4:00 Overview of NVIDIA CUDA Support in AMBER- Lessons Learned, Capabilities Gained
Ross Walker, University of California San Diego, San Diego Supercomputing Center
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5:00-5:30 The Next Generation CUDA Architecture, Code Named Fermi
The Soul of a Supercomputer in the Body of a GPU
Jonathan Cohen, NVIDIA
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Wednesday, November 18, 2009
10:30 A Linear Algebra Library for Multicore/Accelerators: the PLASMA/MAGMA Collection
Jack Dongarra, University of Tennessee
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11:00 An NSF Funded Partnership To Enable Large Scale Computational Science with Heterogeneous Computing

Jeffrey Vetter, Oakridge National Labs/Georgia Tech
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12:00 Harnessing GPU Speed to Accelerate LAMMPS Particle Simulation
Paul Crozier, Sandia National Laboratory
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1:00 Accelerating Molecular Modeling Applications with GPU Computing
John Stone, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana Champaign
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1:30 A Powerful IDE for GPU Computing on Windows: Code Named Nexus
Stephen Jones, NVIDIA
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2:00 The Future of HPC, GPU Computing
Bill Dally, NVIDIA
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3:00 Application of GPUs to Solve the Systems of Linear Equations That Arise in Lattice Quantum Chromodynamics (lattice QCD)
Michael Clark, Harvard University
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4:00 Data Analysis and Visualization on Emerging Architectures
Patrick McCormick, Los Alamos National Laboratory

Coming Soon

5:00 Languages, APIs and Tools for GPU Computing on the CUDA Architecture
Will Ramey, NVIDIA
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Thursday, November 19, 2009
11:00 Low Power Data-Intensive Computing Using the ION Platform
Alex Szalay, Johns Hopkins University
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12:00 A Powerful IDE for GPU Computing on Windows: Code Named Nexus
Stephen Jones, NVIDIA
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1:00 The Next Generation CUDA Architecture, Code Named Fermi
The Soul of a Supercomputer in the Body of a GPU
Michael Garland, NVIDIA
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2:00 To GPU Synchronize or Not GPU Synchronize
Wu-chun Feng, Virginia Tech
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3:00 Languages, APIs and Tools for GPU Computing on the CUDA Architecture
Will Ramey, NVIDIA
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