Openmp
Showing 23 of 23 projects
A fast, header-only C++ machine learning library with bindings for Python, R, Julia, and Go.
A C++ parallel algorithms library that enables high-performance computing on GPUs and multicore CPUs with a productivity-focused interface.
An open-source cross-platform performance library of basic building blocks for deep learning applications, optimized for CPUs and GPUs.
A C++ programming model for writing performance-portable applications targeting all major HPC platforms.
A simple, portable Fast Fourier Transform (FFT) library for C with support for fixed and floating point data types.
An open-source C library with MATLAB interfaces implementing popular computer vision algorithms for image understanding and local feature extraction.
A framework for building parallel, multi-disciplinary simulation software, focusing on modularity, extensibility, and high-performance computing.
A C++17 library providing efficient STL-like data structures (vector, unordered_map, etc.) for GPU programming with CUDA, OpenMP, and HIP backends.
A C++ template library providing high-performance SIMD-accelerated sorting algorithms for integers, floats, and custom objects.
A header-only C++ library for solving large sparse linear systems using algebraic multigrid (AMG) method with support for GPU acceleration.
A multi-threaded, SSE-optimized Normal Distributions Transform algorithm for point cloud registration, offering up to 10x speedup over the original PCL implementation.
A C++14 header-only library for high-performance video and image processing using meta-programming and SIMD optimizations.
A C++ vector expression template library for OpenCL, CUDA, and OpenMP that simplifies GPGPU development.
A modern C++17 header-only quantum computing library for simulating arbitrary quantum processes.
A C++ header-only library of statistical distribution functions with compile-time computing capabilities.
A fast C++ library for fuzzy string matching using Levenshtein Distance, offering MIT licensing and algorithmic improvements.
A parallel Monte Carlo and machine learning library for scientific inference, available in Python, MATLAB, Fortran, C++, and C.
A Julia interface for XGBoost, providing efficient distributed gradient boosting for regression, classification, and ranking.
A massively parallel library for training self-organizing maps on multicore CPUs, GPUs, and clusters with support for dense and sparse data.
A pure Fortran 2003+ OOP library for reading and writing VTK XML files for scientific visualization.
A high-performance unified C++ framework implementing domain decomposition methods for solving large-scale elliptic PDEs on parallel computers.
An open-source Fortran 2003 solver for Navier-Stokes equations using finite volume methods with parallel computing capabilities.
A GPU-accelerated (CUDA) C++ template library for building and training artificial neural networks, including self-organizing maps and back-propagation networks.
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