23 best open source openmp projects.

We have collection of more than 1 Million open source products ranging from Enterprise product to small libraries in all platforms. We aggregate information from all open source repositories. Search and find the best for your needs. Check out projects section.

Displaying 1 to 20 from 23 results

armadillo-code - Armadillo: fast C++ library for linear algebra & scientific computing - http://arma

Armadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net

linear-algebra matrix matrix-functions linear-algebra-library statistics matlab blas lapack hpc scientific-computing mkl machine-learning armadillo openmp gaussian-mixture-models cpp11 vector sparse-matrix expression-template matrix-factorization

UACluster2

UACluster2 is set of manuals and tools to create and manage high performance computing cluster based on Microsoft Hyper-V virtual machines. It needs Microsoft HPC Server 2008 (Microsoft HPC Server 2008 R2) as a basis of cluster creation.

computing-cluster hpc mpi openmp parallel-computing parallel-programming

Hopfield Simulator

DotNet

This is The Hopfield neural network simulator. It show how a Hopfield neural network works as recurent NN. At the moment I need to develop GUI for this project. And I want to invite funs of AI algorithms like me. Project is developin in C++ and C#. I use Visual Studio 2008.

ai ann openmp

Arraymancer - A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU, OpenCL and embedded devices

Arraymancer is a tensor (N-dimensional array) project in Nim. The main focus is providing a fast and ergonomic CPU, Cuda and OpenCL ndarray library on which to build a scientific computing and in particular a deep learning ecosystem. The library is inspired by Numpy and PyTorch. The library provides ergonomics very similar to Numpy, Julia and Matlab but is fully parallel and significantly faster than those libraries. It is also faster than C-based Torch.

tensor nim multidimensional-arrays cuda deep-learning machine-learning cudnn high-performance-computing gpu-computing matrix-library neural-networks parallel-computing openmp linear-algebra ndarray opencl gpgpu iot automatic-differentiation autograd

raytracing-render - Developing raytracing render from scratch.

Developing ray tracing render from scratch. Requires libpng to be installed. Tested on Mac OS 10.8 with gcc 4.2, gcc 4.7, gcc 4.9 and gcc 5 (as far as OpenMP is required - currently, Clang can't be used).

raytracing-render kd-tree libpng antialiasing openmp

amgcl - C++ library for solving large sparse linear systems with algebraic multigrid method

AMGCL is a header-only C++ library for solving large sparse linear systems with algebraic multigrid (AMG) method. AMG is one of the most effective iterative methods for solution of equation systems arising, for example, from discretizing PDEs on unstructured grids. The method can be used as a black-box solver for various computational problems, since it does not require any information about the underlying geometry. AMG is often used not as a standalone solver but as a preconditioner within an iterative solver (e.g. Conjugate Gradients, BiCGStab, or GMRES). AMGCL builds the AMG hierarchy on a CPU and then transfers it to one of the provided backends. This allows for transparent acceleration of the solution phase with help of OpenCL, CUDA, or OpenMP technologies. Users may provide their own backends which enables tight integration between AMGCL and the user code.

amg c-plus-plus sparse-linear-systems opencl cuda gpgpu openmp scientific-computing cpp multigrid

openmp-examples - openmp examples

This repository contains OpenMP-examples which I create while learning OpenMP. This is a playground repository. I follow Tim Mattson's Introduction to OpenMP video playlist on youtube.

openmp parallel parallel-computing cpp multithreading learning-openmp alternating-least-squares

omega_h - Simplex mesh adaptivity for HPC

Omega_h is a C++11 library that implements tetrahedron and triangle mesh adaptativity, with a focus on scalable HPC performance using (optionally) MPI, OpenMP, or CUDA. It is intended to provided adaptive functionality to existing simulation codes. Mesh adaptivity allows one to minimize both discretization error and number of degrees of freedom live during the simulation, as well as enabling moving object and evolving geometry simulations. Omega_h will do this for you in a way that is fast, memory-efficient, and portable across many different architectures. For a bare minimum setup with no parallelism, you just need CMake, a C++11 compiler, and preferably ZLib installed.

mpi cuda meshing mesh-generation finite-elements c-plus-plus c-plus-plus-11 parallel-computing cmake hpc openmp cpp cpp11 gpu triangulation parallel parallelism mesh geometry

bkcrack - Crack legacy zip encryption with Biham and Kocher's known plaintext attack.

Crack legacy zip encryption with Biham and Kocher's known plaintext attack. Get the latest version from the git repository.

crack plaintext zip openmp multithread attack plaintext-attack

splatt - The Surprisingly ParalleL spArse Tensor Toolkit.

SPLATT is a library and C API for sparse tensor factorization. SPLATT supports shared-memory parallelism with OpenMP and distributed-memory parallelism with MPI. will suffice. The installation prefix can be chosen by adding a '--prefix=DIR' flag to configure.

tensor parallel machine-learning cpd mpi openmp

rkmh - Classify sequencing reads using MinHash.

HTML

rkmh performs identification of individual reads, identity-based read filtering, and alignment-free variant calling using MinHash (as implemented in Mash). It is compatible with Mash and sourmash via JSON exchange. We're using rkmh to identify which strains are present in infections with multiple strains of the same virus. rkmh could also be used to remove reads from contaminants or call mutations in novel strains relative to a nearby reference. You could even select out only reads from a pathogen sample contaminated with human DNA.

nanopore minhash mutations openmp bioinformatics kmer

abyss - :microscope: Assemble large genomes using short reads

ABySS is a de novo sequence assembler intended for short paired-end reads and large genomes. Please cite our papers.

bloom-filter c-plus-plus science bioinformatics assembler scaffold genome openmp mpi

ytk-mp4j - Ytk-mp4j is a fast, user-friendly, cross-platform, multi-process, multi-thread collective message passing java library which includes gather, scatter, allgather, reduce-scatter, broadcast, reduce, allreduce communications for distributed machine learning

Java

Ytk-mp4j is a fast, user-friendly, cross-platform, multi-process, multi-thread collective message passing java library which includes gather, scatter, allgather, reduce-scatter, broadcast, reduce, allreduce communications.

mpi allreduce reduce broadcast machine-learning messaging-library openmp

rawspeed - fast raw decoding library

So RawSpeed is not intended to be a complete RAW file display library, but only act as the first stage decoding, delivering the RAW data to your application. You can get access to the lastest version using from here. You will need to include the “RawSpeed” and “data” folder in your own project.

camera cpp cpp11 pthreads openmp xml zlib dng jpeg decoding dslr cmake bayer x-trans library cr2 nef raw cpp14

pagoda2 - R package for analyzing and interactively exploring large single-cell RNA-seq datasets

Javascript

To install pagoda2 please follow the instructions below.

bioinformatics single-cell transcriptomics heterogeneity analysis r ngs data-visualization docker-container largevis openmp clang

gapbs - GAP Benchmark Suite

This is the reference implementation for the GAP Benchmark Suite. It is designed to be a portable high-performance baseline that only requires a compiler with support for C++11. It uses OpenMP for parallelism, but it can be compiled without OpenMP to run serially. The details of the benchmark can be found in the specification. The GAP Benchmark Suite is intended to help graph processing research by standardizing evaluations. Fewer differences between graph processing evaluations will make it easier to compare different research efforts and quantify improvements. The benchmark not only specifies graph kernels, input graphs, and evaluation methodologies, but it also provides an optimized baseline implementation (this repo). These baseline implementations are representative of state-of-the-art performance, and thus new contributions should outperform them to demonstrate an improvement.

graph-algorithms benchmark bfs openmp

crowdsource-video-experiments-on-android - Crowdsourcing video experiments (such as collaborative benchmarking and optimization of DNN algorithms) using Collective Knowledge Framework across diverse Android devices provided by volunteers

Java

This CK-powered open-source Android application lets the community participate in experiment crowdsourcing which require webcam (such as crowd-benchmarking and crowd-tuning Caffe, Tensorflow and other DNN frameworks or any realistic application for image processing and recognition) using their mobile devices (mobile phones, tablets, IoT, etc) and exchange knowledge via public CK servers. You can download this app from the Google Play Store.