Accuracy of the Discrete Fourier Transform and the Fast Fourier Transform
SIAM Journal on Scientific Computing
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
LAPACK Users' guide (third ed.)
LAPACK Users' guide (third ed.)
Automatically tuned linear algebra software
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
An updated set of basic linear algebra subprograms (BLAS)
ACM Transactions on Mathematical Software (TOMS)
Computational Methods for Inverse Problems
Computational Methods for Inverse Problems
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
Direct Methods for Sparse Linear Systems (Fundamentals of Algorithms 2)
JLAPACK - compiling LAPACK Fortran to Java
Scientific Programming
IEEE Transactions on Computers
Towards a Next-Generation Matrix Library for Java
COMPSAC '09 Proceedings of the 2009 33rd Annual IEEE International Computer Software and Applications Conference - Volume 01
Fast PCA for processing calcium-imaging data from the brain of drosophila melanogaster
Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics
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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.