Parallel Colt: A High-Performance Java']Java Library for Scientific Computing and Image Processing

被引:25
作者
Wendykier, Piotr [1 ]
Nagy, James G. [1 ]
机构
[1] Emory Univ, Dept Math & Comp Sci, Atlanta, GA 30322 USA
来源
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE | 2010年 / 37卷 / 03期
基金
美国国家科学基金会;
关键词
Algorithms; Design; Performance; Deconvolution; FFT; inverse problems; iterative methods; multithreading; regularization; PET; motion correction; MOTION CORRECTION; BRAIN IMAGES; RECONSTRUCTION; ALGORITHM; SOFTWARE;
D O I
10.1145/1824801.1824809
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Major breakthroughs in chip and software design have been observed for the last nine years. In October 2001, IBM released the world's first multicore processor: POWER4. Six years later, in February 2007, NVIDIA made a public release of CUDA SDK, a set of development tools to write algorithms for execution on Graphic Processing Units (GPUs). Although software vendors have started working on parallelizing their products, the vast majority of existing code is still sequential and does not effectively utilize modern multicore CPUs and manycore GPUs. This article describes Parallel Colt, a multithreaded Java library for scientific computing and image processing. In addition to describing the design and functionality of Parallel Colt, a comparison to MATLAB is presented. Two ImageJ plugins for iterative image deblurring and motion correction of PET brain images are described as typical applications of this library. Performance comparisons with MATLAB including GPU computations via AccelerEyes' Jacket toolbox are also given.
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页数:22
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