The Visualization Toolkit (VTK) is a C++ library for 3D computer graphics, image processing and visualization. It supports a wide variety of visualization algorithms including: scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques such as: implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. VTK has an extensive information visualization framework, has a suite of 3D interaction widgets, supports parallel processing, and integrates with various databases on GUI toolkits such as Qt and Tk.

TTK

QtDCM implements several Qt widgets for manipulating Dicom data. With QtDCM, it is possible to explore a Dicom CD-ROM, to search and download from a PACS (Pictures Archive and Communications System) and to convert series of images to the nifti format. Thanks to its simple design, QtDcm is very easy to integrate in other application (see the example directory in the code).

The RPI is a lightweight framework to encapsulate image registration algorithms.

medInria is a multi-platform medical image processing and visualization software. medInria offers from standard to cutting-edge processing functionalities for your medical images such as 2D/3D/4D image visualization, image registration, diffusion MR processing and tractography.

MIPP is a portable wrapper for SIMD instructions written in C++11.

This is a minimalist MPI hello world.

The Open MPI Project is an MPI-3 implementation that is developed and maintained by a consortium of academic, research, and industry partners. Open MPI is therefore able to combine the expertise, technologies, and resources from all across the High Performance Computing community in order to build the best MPI library available. Open MPI offers advantages for system and software vendors, application developers and computer science researchers.

The Open MPI Project is an MPI-3 implementation that is developed and maintained by a consortium of academic, research, and industry partners. Open MPI is therefore able to combine the expertise, technologies, and resources from all across the High Performance Computing community in order to build the best MPI library available. Open MPI offers advantages for system and software vendors, application developers and computer science researchers.

Fortran CoArrays is a library implementing a PGAS model for programming parallel application in Fortran

PaMPA is a C library for dynamic parallel remeshing and redistribution of unstructured meshes.

SimGrid is a scientific instrument to study the behavior of large-scale distributed systems such as grids, "clouds", HPC, and P2P systems. It can be used to evaluate heuristics, prototype applications or even assess legacy MPI applications.

SimGrid is a scientific instrument to study the behavior of large-scale distributed systems such as grids, "clouds", HPC, and P2P systems. It can be used to evaluate heuristics, prototype applications or even assess legacy MPI applications.

Brian is a simulator for spiking neural networks, written in Python. It is designed to be easy to learn and use, highly flexible and easily extensible.

METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill-reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes.

SLURM is a fault-tolerant and highly scalable cluster management and job scheduling system for large and small clusters. It allocates access to resources (computer nodes) to users for some duration of time, provides a framework for starting, executing, and monitoring work (typically a parallel job) on a set of allocated nodes, and arbitrates contention for resources by managing a queue of pending work.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

PARCOACH is an Open-source software dedicated to the collective errors detection in parallel applications.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.

StarPU is a run-time system that offers support for heterogeneous multicore machines. While many efforts are devoted to design efficient computation kernels for those architectures (e.g. to implement BLAS kernels on GPUs), StarPU not only takes care of offloading such kernels (and implementing data coherency across the machine), but it also makes sure the kernels are executed as efficiently as possible.