PEDSIM is a microscopic pedestrian crowd simulation system. The PEDSIM library allows you to use pedestrian dynamics in your own software. Based on pure C++/STL without additional packages, it runs on virtually every operating system. The PEDSIM Demo Application (Qt) gives you a quick overview of the capabilities, and is a starting point for your own experiments. PEDSIM is suitable for use in crowd simulations (e.g. indoor evacuation simulation, large scale outdoor simulations), where one is interested in output like pedestrian density or evacuation time. The quality of the individual agent's trajectory is high, PEDSIM can be used for creating massive pedestrian crowds in movies. Since libpedsim is easy to use and extend, it is a good starting point for science projects.
TooN is a very efficient numerics library for C++. The main focus of the library is efficient and safe handling of large numbers of small vector matrices and providing as much compile time checking as is possible. The library also works with large vectors and matrices and integrates easily with existing code. In addition to elementary vector and matrix operations, the library also providers linear solvers, matrix decompositions, optimization, and wrappers around LAPACK.
StarCluster is a utility for creating traditional computing clusters used in research labs or for general distributed computing applications on Amazon's Elastic Compute Cloud (EC2). It uses a simple configuration file provided by the user to request cloud resources from Amazon and to automatically configure them with a queuing system, an NFS shared /home directory, passwordless SSH, OpenMPI, and ~140GB scratch disk space. It consists of a Python library and a simple command line interface to the library. For end-users, the command line interface provides simple intuitive options for getting started with distributed computing on EC2 (i.e. starting/stopping clusters, managing AMIs, etc). For developers, the library wraps the EC2 API to provide a simplified interface for launching/terminating nodes, executing commands on the nodes, copying files to/from the nodes, etc.
Regress Pro is scientific and industrial software that can be used to study experimental data coming from spectroscopic ellipsometers or reflectometers. The program has been developed mainly looking to the application of thin film measurement in semiconductor industry. The software is suitable both to determine the thickness of the layers and to determine the optical properties of dielectric materials.
FFTW++ is a C++ header class for the FFTW Fast Fourier Transform library that automates memory allocation, alignment, planning, and wisdom. In 2D and 3D, implicit dealiasing of convolutions substantially reduces memory usage and computation time. Wrappers for C, Python, and Fortran are included.
GriF is a collaborative grid framework to support computational chemistry applications. It is meant to be used as a tool to facilitate massive grid calculations and also to improve scientific collaboration. Accordingly, GriF facilitates profiling the users of grid communities in order to systematically evaluate the work carried out in a grid and to foster its sustainability.
Qt-based library with functionality to create highly efficient and fully graphical applications, oriented to computer vision, image processing, and scientific computation. The library features an homogeneous and well documented object-oriented API, with wrapping methods for high performance functionality from libraries such as OpenCV, GSL, CGAL, IPP, BLAS, LAPACK, or Octave library.
Salad (short for Letter Salad) is an efficient and flexible implementation of the well-known anomaly detection method Anagram by Wang et al. (RAID 2006). Salad is based on n-gram models, that is, data is represented as all of its substrings of length n. During training these n-grams are stored in a Bloom filter. This enables the detector to represent a large number of n-grams in little memory and still being able to efficiently access the data. Salad extends Anagram by allowing various n-gram types, a 2-class version of the detector for classification, and various model analysis modes.