Search Results for "parallel computing" - Page 2
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Showing 188 open source projects for "parallel computing"
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Google Highway
Performance-portable, length-agnostic SIMD with runtime dispatch
Google Highway is a high-performance C++ library designed to provide portable SIMD (Single Instruction, Multiple Data) vectorization across multiple CPU architectures while maintaining predictable and efficient behavior. It abstracts low-level vector intrinsics into a consistent API that maps closely to hardware instructions, allowing developers to write high-performance code without relying heavily on compiler auto-vectorization. Highway enables the same source code to run across different... -
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. Find the best... -
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FortranBSD
FortranBSD is DragonflyBSD-based OS with built-in GNU Fortran
I'm excited to introduce the first release of FortranBSD, a new operating system designed specifically for Fortran developers who demand high-performance and seamless multithreading support. FortranBSD is based on DragonflyBSD which is an outstanding OS for HPC application and: 🔹 Superior parallel computing capabilities beat Linux/MS Windows over the performance. 🔹 Optimized for Fortran programming 🔹 Built on a robust, efficient foundation 🔹 Ideal for scientific computing, simulations, and high-performance Computation (HPC) applications FortranBSD is a game-changer for anyone working with Fortran who wants an OS that fully supports and enhances multithreaded execution. ... -
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PelicanHPC is an iso-hybrid (CD or USB) image that let's you set up a high performance computing cluster in a few minutes. A Pelican cluster allows you to do parallel computing using MPI. You can run Pelican on a single multiple core machine to use all cores to solve a problem, or you can network multiple computers together to make a cluster. The frontend node (either a real computer or a virtual machine) boots from the image.
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PICSL Greedy Registration Tool
Fast deformable 3D image registration tool
Greedy is a tool for fast medical image registration. It was developed at the Penn Image Computing and Science Lab at the University of Pennsylvania. The motivation for developing greedy was to have a really fast CPU-based deformable image registration tool that could be used in applications where many images have to be registered in parallel - like multi-atlas image segmentation. -
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OpenFOAM
The Open Source CFD Toolbox
OpenFOAM - The Open Source CFD Toolbox. OpenFOAM is a generic, programmable software tool for Computational Fluid Dynamics (CFD). For more information, see: - Main Website: https://openfoam.org - C++ Source Documentation: https://cpp.openfoam.org - Issue (Bug) Tracking: https://bugs.openfoam.org - User Guide: https://cfd.direct/openfoam/user-guide -
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Octave Forge
A collection of packages providing extra functionality for GNU Octave
Octave Forge is a central location for collaborative development of packages for GNU Octave. The Octave Forge packages expand Octave's core functionality by providing field specific features via Octave's package system. See https://octave.sourceforge.io/packages.php for a list of all available packages. GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and... -
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GrOWin
Gromacs on Windows
...Optimized Performance: Experience enhanced performance with Growin's dedicated CPU and GPU versions of the software. Whether you're utilizing the raw processing power of your CPU or leveraging the parallel computing capabilities of your GPU. 3. User-Friendly Interface: A simple command line interface on Windows for seamless navigation and efficient utilization of GROMACS functionalities. Discover the next level of MD simulations with Growin opening new possibilities -
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Optimizer_sovkov
Constructing and optimizing general mathematical and physical models
...Currently, the main focus of these is computational quantum mechanics, analysis and simulation of molecular spectra, and general-purpose approximants. The package provides the most reliable modern strategies for linear and non-linear model optimization, regularization, and hypothesis tests. Parallel computing is supported. -
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syre
Synchronous Reluctance (machines) - evolution
SyR-e is a Matlab/Octave package developed to design, evaluate and optimize synchronous reluctance and permanent magnet machines. To perform Finite Element Analysis (FEA) SyR-e is linked to FEMM software, and the simulation process (model creation, pre-processing, post-processing) is automatic and completely controlled from SyR-e code. For the design section, SyR-e embeds automatic procedures based on design equations, minimal FEA simulations or multi-objective optimization algorithm... -
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KeyKiller-Cuda
Solving the Satoshi Puzzle
KeyKiller is a GPU-accelerated version of the KeyKiller project, designed to achieve extreme performance in solving Satoshi Nakamoto's puzzles using modern NVIDIA GPUs. KeyKiller CUDA pushes the limits of cryptographic key search performance by leveraging CUDA, thread-beam parallelism, and batch EC operations. The command-line version is open-source and free to use. For the paid advanced graphics version, please visit: https://gitlab.com/8891689/KeyKiller-Cuda/ -
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octave-ocl
OpenCL support for GNU Octave
The Package is installable in GNU Octave and offers OpenCL support for parallelization of numerical computations. It is most effective for computations which are based on large vectors or n-dimensional arrays of numbers, and mostly (but not limited to) identical element-wise operations. The user can select which available OpenCL hardware and drivers are to be used. The Package offers new numeric data types with many built-in operations (e.g., overloaded operators). It is flexibly... -
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DEVS-Suite Simulator
Component, CA, and CCA models; superdense time, DB repo, testing, etc.
Integrated component-based and cellular automata (CA) Parallel DEVS simulator: https://acims.asu.edu/devs-suite/ OFFERS: 1) synchronized execution & animation, 2) run-time linear/superdense I/O & state trajectories, 3) Action Level Real-Time modeling & simulation, 4) model checking, 5) ABM, 6) CA & composable CA playback, 7) KIB interaction modeling, 8) hierarchical model libraries, 9) Black-Box testing & debugging, 10) PostgreSQL repository, 11) FMU (OpenModelica), 12) OSATE (AADL) with domain-specific models: NoC; SW/HW co-design, Service-Oriented Computing, cancer biology, Dynamic Structure, SOA DEVS, MIPS32 processors, and computer networks for education. ... -
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dft_installer.sh
Automated Installer for VASP, SIESTA, their libraries and utilities
Automated Installer for VASP, SIESTA, and their libraries and utilities for serial and parallel modes in a Linux environment. (dft_installer.sh) Gustavo Domínguez Rodríguez, Gabriel Iván Canto Santana, Jorge Alejandro Tapia Gonzalez, Cesar Alberto Cab Cauich High-performance scientific software is commonly compiled on the computing system, for optimizing it according to its specific characteristics. However, this compilation is often a tedious and limiting process, which frequently becomes an obstacle for its use. ... -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. -
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
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Singularity
Open source container platform designed to be simple, fast, and secure
Singularity is an open-source container platform designed to be simple, fast, and secure. Many container platforms are available, but Singularity is designed for ease of use on shared systems and in high-performance computing (HPC) environments. -
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SMASH
Massively parallel software for quantum chemistry calculations
Scalable Molecular Analysis Solver for High-performance computing systems (SMASH) is massively parallel software for quantum chemistry calculations and released under the Apache 2.0 open source license. It is currently capable of energy, analytical gradient, and geometry optimization calculations of Hartree-Fock theory and Density Functional Theory (DFT), and energy calculations of Second-order Moller-Plesset (MP2) perturbation theory. -
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NESSIE is a modern first-principle calculation software that can adequately address the need for ever-higher levels of numerical accuracy and high-performance in large-scale electronic structure simulations, as well as pioneer the fundamental study of quantum many-body effects in a large number of emerging nanomaterials. NESSIE is an electronic structure code that uses a real-space FEM discretization and domain-decomposition (DD) to perform all-electron ground-state DFT and real-time...
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VOX-FE
Voxel-based Finite Element Analysis for Biomechanical Applications
VOX-FE is voxel-based FE software, developed jointly between the University of Hull's Medical & Biological Engineering Research Group and Edinburgh Parallel Computing Centre, with a sophisticated graphical user interface that allows the complex loading regimes that are inevitably present in biomechanical analyses to be readily applied to the model geometry, and the resultant 3D stress and strain patterns to be visualized easily. In addition to the introduction above, several example videos are available on YouTube: https://www.youtube.com/watch?... -
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Version2. to cite this collection: DOI: http://dx.doi.org/10.12785/ijcds/100161 title={A Combined Method of Naïve-Bayes and Pooling Strategy for Building Test Collection for Arabic/English Information Retrieval}, author={Mazari, Ahmed Cherif and Djeffal, Abdelhamid}, journal={International Journal of Computing and Digital Systems}, volume={10}, year={2021}, publisher={University of Bahrain} }
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Cuda Simulated Annealing GPU Route Plan
An Optimized GPU-Accelerated Route Planning of Multi-UAV Systems Using
An Optimized GPU-Accelerated Route Planning of Multi-UAV Systems Using Simulated Annealing Article CUDA CODE Usage of multiple unmanned aerial vehicles (UAV) in a certain mission makes flight route planning more complicated and slower. In order to obtain better performance, in the literature, most of the researchers propose using evolutionary algorithms and artificial intelligence approaches based on heuristics as optimization techniques. In addition to this, parallel programming... -
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splitjob
Reads from stdin, splits and sends to parallel invocations of commands
Useful to split up jobs over multiple CPU cores or even multiple computers. Examples: tar -cf - /bigdirectory | splitjob -j 4 gzip > big.tar.gz splitjob "ssh h1 bzip2" "ssh h2 bzip2" < f > f.bz2 -
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YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
...Darknet on the CPU is fast (approximately 1.5 seconds on an Intel Core i7-6700HQ CPU @ 2.60GHz × 8) but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. The CMakeLists.txt file automatically detects if you have CUDA installed or not. CUDA is a parallel computing platform and application programming interface (API) model created by Nvidia. -
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Accelerate
Embedded language for high-performance array computations
Data.Array.Accelerate defines an embedded language of array computations for high-performance computing in Haskell. Computations on multi-dimensional, regular arrays are expressed in the form of parameterized collective operations (such as maps, reductions, and permutations). These computations are online-compiled and executed on a range of architectures. Accelerate is a free, general-purpose, open-source library that simplifies the process of developing software that targets massively parallel architectures including multicore CPUs and GPUs. ...
