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Qalculate! is a multi-purpose desktop calculator. It is small and simple to use but with much power and versatility underneath. Features include customizable functions, units, arbitrary precision, plotting, and a user-friendly interface.

Topaz is a graph plotting system for scientists and engineers. 1. Topaz has a powerful graph expression and functions such as least square method. Topaz provides almost all functions that you need to make a 2D scattering graph. 2. Topaz has a polished character based user interface. 3. Topaz has powerful macro language of "Topaz script", which is like Perl. You can expand topaz itself or you can perform batch jobs using topaz scripts. Topaz official Web Page.

This library provides routines that return: (1) Beta random deviates (2) Chi-square random deviates (3) Exponential random deviates (4) F random deviates (5) Gamma random deviates (6) Multivariate normal random deviates (mean and covariance matrix specified) (7) Noncentral chi-square random deviates (8) Noncentral F random deviates (9) Univariate normal random deviates (10) Random permutations of an integer array (11) Real uniform random deviates between specif (12) Binomial random deviates (13) Negative Binomial random deviates (14) Multinomial random deviates (15) Poisson random deviates (16) Integer uniform deviates between specified limits (17) Seeds for the random number generator calculated from a character string

RngStreams is a C implementation of a high-quality uniform random number generator that supports multiple "independent" streams of uniform random numbers. It was written by Pierre L'Ecuyer and Richard Simard, who have a website at: http://www.iro.umontreal.ca/~simardr/indexe.html This GNU-style package is compiled and maintained by Josef Leydold and released under the GNU Public License (GPL).

This port contains data and baseline images for VTK regression testing and other VTK examples. The Data directory are data files of various types. This includes polygonal data, images, volumes, structured grids, rectilinear grids, and multi-variate data. The Baseline are the testing images. These are used in testing to compare a valid image against a generated image. If a difference between the two images is found, then the test is considered to have failed.

The ScaLAPACK (or Scalable LAPACK) library includes a subset of LAPACK routines redesigned for distributed memory MIMD parallel computers. It is currently written in a Single-Program-Multiple-Data style using explicit message passing for interprocessor communication. It assumes matrices are laid out in a two-dimensional block cyclic decomposition.

The SDPA (SemiDefinite Programming Algorithm) is a software package for solving semidefinite program (SDP). It is based on a Mehrotra-type predictor-corrector infeasible primal-dual interior-point method. The SDPA handles the standard form SDP and its dual. It is implemented in C++ language utilizing the LAPACK for matrix computation. The SDPA incorporates dynamic memory allocation and deallocation. So, the maximum size of an SDP to be solved depends on the size of memory which users' computers install. The SDPA enjoys the following features: 1. Callable library of the SDPA is available. 2. Efficient method for computing the search directions when an SDP to be solved is large scale and sparse. 3. Block diagonal matrix structure and sparse matrix structure in data matrices are available. 4. Some information on infeasibility of a semidefinite program to be solved is provided.

The SDPARA (SemiDefinite Programming Algorithm PARAllel version) is a parallel version of the SDPA. C++ source codes of the SDPARA are available in this homepage. They form a stand-alone software package for solving SDPs in parallel with the help of MPI (Message Passing Interface) and ScaLAPACK (Scalable LAPACK). However callable libraries of the SDPARA, which could be used combinedly with other C++ programs, are not available. We assume that you know how to use the latest version of the SDPA and MPICH.

sfft is a library to compute discrete Fourier transforms of signals with a sparse frequency domain, using an algorithm that is more efficient than other known FFT algorithms. It was developed by Haitham Hassanieh, Piotr Indyk, Dina Katabi, and Eric Price at the Computer Science and Artifical Intelligence Lab at MIT. Performance optimizations were developed by J. Schumacher at the Computer Science Department of ETH Zurich in 2013.

SLATEC is a comprehensive software library containing over 1400 general purpose mathematical and statistical routines written in Fortran 77.