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  1. Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units (GPGPU-2)
  2. Accelerating cosmological data analysis with graphics processors
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Accelerating cosmological data analysis with graphics processors
High performance computation and interactive display of molecular orbitals on GPUs and multi-core CPUs
GPU acceleration of a production molecular docking code
Accelerating phase unwrapping and affine transformations for optical quadrature microscopy using CUDA
Performance analysis of accelerated image registration using GPGPU
Accelerating linpack with CUDA on heterogenous clusters
hiCUDA: a high-level directive-based language for GPU programming
Architecture-aware optimization targeting multithreaded stream computing
QR decomposition on GPUs
3D finite difference computation on GPUs using CUDA
Optimization of tele-immersion codes
Understanding software approaches for GPGPU reliability

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Accelerating cosmological data analysis with graphics processors

Content Provider ACM Digital Library
Author Kindratenko, Volodymyr V. Brunner, Robert J. Roeh, Dylan W.
Abstract In this paper we describe a successful effort to accelerate the two-point angular correlation function---a basic statistics tool used in the field of cosmology to characterize the distribution of the matter and energy in the Universe---by using an NVIDIA GPU-based system. We demonstrate the use of GPUs to accelerate the calculation of histograms of angular separations for large datasets as we achieve over two orders of magnitude performance improvement over conventional microprocessors. We discuss the specific implementation details of GPU kernels for computing bin assignments and updating histogram bins. We also describe an MPI-based GPU-accelerated two-point correlation application that runs on a compute cluster with multiple GPUs. Finally, we discuss specific lessons we learned in using GPUs to implement this class of algorithms.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781605585178
DOI 10.1145/1513895.1513896
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2009-03-08
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Two-point angular correlation function Gpgpu
Content Type Text
Resource Type Article
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