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08-09-10, 01:30 PM
With the GPU Technology Conference (http://www.nvidia.com/object/gpu_technology_conference.html) (GTC) only 6 weeks away, we¬*wanted to start¬*highlighting some of the can‚??t-miss sessions. With over 240 technical sessions (https://nvidia.confreg.com/gputechconference/schedule/by-day/) to choose from, there's a lot of ground to cover.¬* This week we're looking at high performance computing (HPC) content.

At last year‚??s GTC, attendees learned about how GPUs are playing a crucial role in HPC. Supercomputing experts including, Wen-mei Hwu of the University of Illinois at Urbana-Champaign, Satoshi Matsuoka of Tokyo Technical Institute of Japan, James Phillips of Georgia Institute of Technology, John Taylor¬* of CSIRO and Jeffrey Vetter of Oakridge National Laboratoryp - just to name a few - gathered to discuss their experiences building and deploying GPU-based supercomputing clusters. They also presented case studies of designing and porting codes for ‚??big iron‚?? GPU supercomputers. Watch a video of part of the Supersessionfrom GTC 2009, Here (http://www.nvidia.com/content/GTC/videos/Super%20Computer%20Break%20Out%20Pt2_HD_480p.wmv).

This year we're bringing even more great insights from HPC experts. Check out these three sessions you can look forward to at GTC 2010:

Power Management Techniques for Heterogeneous Exascale Computing (Session #2052) - Xiaohui Cui, Oak Ridge National Laboratories:
Power consumption has become the leading design constraint for large scale computing systems. In order to achieve exascale computing, system energy efficiency must be improved significantly. Our approach will focus on investigating software methodologies to achieve energy efficient computing on heterogeneous systems accelerated with GPUs.

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Nearly Instantaneous Reconstruction for MRIs (#2094) - General Electric:
GE‚??s Autocalibrating Reconstruction for Cartesian Imaging (ARC) is a computationally intensive, widely used algorithm in MRI Reconstruction using Parallel Imaging. We demonstrate that an optimized CUDA implementation of ARC on a GPU can enable nearly instantaneous reconstruction and speedups of up to 10x over an optimized dual socket QuadCore CPU implementation. We will discuss challenges both with computational intensity and data read/write efficiency. We will also compare the Fermi C2050 with the C1060.

Moving the Frontier of Oil and Gas Exploration and Production with GPUs (Session #2141) - Olav Lindtjorn, Schlumberger:
Learn how the Oil and Gas Industry is embracing GPUs in order to tackle new and complex oil and gas plays around the world. The first part of this talk gives an overview of the business and geopolitical drivers of the industry, followed with the critical contribution of computation in the quest for secure supply of energy.

Stay tuned to the blog for more content highlights, and register before September 1 (http://www.nvidia.com/object/gpu_tech_conf_registration.html) to take advantage of early bird discounts.

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