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TUESDAY, MAY 15, 16:00 (50 MINUTES ROOM K S0008 Algorithms and Tools for Bioinformatics on <strong>GPU</strong>s Learn how to use <strong>GPU</strong>s to accelerate compute- and data-intensive applications and algorithms Bioinformatics. High-throughput techniques for DNA sequencing and gene expression analysis with microarrays have led to a rapid growth in the amount of digital biological data, e.g. the NCBI Sequence Read Archive (SRA) houses raw sequence data generated by next-generation sequencing (NGS) technologies which succeeds 25 trillion base-pairs. Therefore, modern bioinformatics tools need to be scalable; i.e. they need to deal with an ever growing amount of data. <strong>GPU</strong>s and CUDA provide the opportunity to significantly reduce the runtime of many biological algorithms on inexpensive hardware. Speaker(s): Bertil Schmidt (Nanyang Technological University) Topic(s): Bioinformatics, Life Sciences (Intermediate) TUESDAY, MAY 15, 16:00 (50 MINUTES) ROOM J3 S0050 High Performance Logic Simulation with <strong>GPU</strong>s Verification has become the bottleneck of IC design process due to its fast increasing complexity. The fundamental means of verifying digital circuits is logic simulation, which can be performed at both register-transfer level (RTL) and gate level. In this work, we developed <strong>GPU</strong> based logic simulation solutions. We implemented a Chandy-Misra-Bryant parallel simulation protocol on <strong>GPU</strong>s for sufficient parallelism. A dynamic <strong>GPU</strong> memory allocator was introduced to efficiently manage <strong>GPU</strong> memory resources. RTL simulation is performed in a compiled-code scheme by translating Verilog code into equivalent CUDA code. Experimental results proved that the <strong>GPU</strong> simulators significantly outperform their CPU counterparts. Speaker(s): Yangdong Deng (Associate Professor, Tsinghua University) Topic(s): General Interest, Algorithms & Numerical Techniques (Advanced) TUESDAY, MAY 15, 16:00 (25 MINUTES) ROOM A1 S0062 Inverse 3D Vision: Detection and Tracking of NVIDIA Glasses Computer Vision is becoming increasingly popular and important nowadays. With the advent of powerful mobile devices and increasing power of desktop PCs, it is important to improve user experience by tackling the hardest problems of real-time interaction with the user. These include body parts tracking, face, and gesture recognition. This talk discusses techniques behind an interaction pattern between a user and a 3D visualization system, in which the system tracks the position of NVIDIA 3D Vision Glasses, and accounts this information during rendering. The mentioned techniques include Histograms of Oriented Gradients and Template Matching. The system implementation is discussed too. Speaker(s): Anton Obukhov Engineering Consultant, (Ubiquiti Networks) Topic(s): Computer Vision, Machine Vision, Development Tools & Libraries, (Advanced) TUESDAY, MAY 15, 16:00 (50 MINUTES) ROOM A3 S0089 Accelerator Directives, OpenACC and OpenMP4ACC Rather than require the programmer to rewrite code for accelerators several directive sets have been created and proposed to support non-cache coherent and cache coherent accelerators. This talk will present the OpenACC specification and its implementation for Cray developers, as well as touch on a similar proposal being evaluated by the OpenMP language committee. The presentation will start by discussing the Memory and Execution model needed to allow a programmer to write codes that will run effectively on both distinct memory systems and unified memory systems. Once a proper background has been set the directives will be examined via usage examples. Speaker(s): James Beyer (Software Engineer, Cray Inc), David Oehmke (Cray Inc.) Topic(s): Parallel <strong>Program</strong>ming Languages & Compilers, Supercomputing (Intermediate) TUESDAY, MAY 15, 16:00 (25 MINUTES) ROOM C S0108 An Innovative Massively Parallelized Molecular Dynamic Software In this paper, we present how we improved the speedup of the electronic structure calculator VASP by more than an order of magnitude. Recently, the research works done (at IFP Energies Nouvelles) have shown that by coupling traditional clusters or High Performance Computing (HPC) machines with accelerators based on graphical processor units (<strong>GPU</strong>s), by recording the most time consuming parts of the codes (with programming languages like CUDA, OpenCL) and offloading them on the graphic chips, it is possible to reduce the computing time to ensure a speedup of a factor of 5 to 15. Speaker(s): Thomas Guignon (Research Engineer, IFPEN), Ani Anciaux Sedrakian (IFP Energie Nouvelles) Topic(s): Molecular Dynamics, Supercomputing, Application Design & Porting Techniques (Intermediate) TUESDAY, MAY 15, 16:00 (50 MINUTES) MARRIOTT BALLROOM 3 S0221 1024 Bit Parallel Rational Arithmetic Operators for the <strong>GPU</strong> Learn how to create a set of rational arithmetic operators that manipulate 1024 bit operands on a Tesla C2050. These operators are used to create a numerically stable implementation for Bessel functions. Naive implementations of the Bessel functions produce unreliable results when they are used to solve Maxwell’s equations by way of Mie theory. Maxwell’s equations are used to model the scattering of light by small particles. Light scatter is used in Particle Characterization to measure the quality of materials like cocoa, cement and pharmaceuticals. Speaker(s): Robert Zigon (Sr. Staff Development Engineer, Beckman Coulter) Topic(s): Algorithms & Numerical Techniques, Computational Physics (Intermediate) TUESDAY, MAY 15, 16:00 (25 MINUTES) ROOM A8 S0245 Porting Legacy Plasma Codes to <strong>GPU</strong> Learn how to port legacy Fortran plasma codes to <strong>GPU</strong>. Many legacy plasma codes are written in Fortran and have many lines of codes. We will discuss techniques in porting such legacy codes easily and efficiently to CUDA C/C++. Performance analysis of major algorithmic patterns in plasma codes will be discussed. The discussion will use the <strong>GTC</strong> and GeFi plasma code as realistic examples. Speaker(s): Peng Wang (Devtech Engineer, NVIDIA) Topic(s): Computational Physics, Computational Physics (Intermediate) 41 CONFERENCE GUIDE TUESDAY
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