Search Results for "parallel computing datamaning"
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Showing 60 open source projects for "parallel computing datamaning"
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Sogou C++ Workflow
C++ parallel computing and asynchronous networking engine
As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements. -
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ncnn
High-performance neural network inference framework for mobile
ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including... -
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ROOT
Analyzing, storing and visualizing big data, scientifically
...It is reliable, performant and well supported, easy to use and obtain, and strives to maximize the quantity and impact of scientific results obtained per unit cost, both of human effort and computing resources. ROOT provides a very efficient storage system for data models, that demonstrated to scale at the Large Hadron Collider experiments: Exabytes of scientific data are written in columnar ROOT format. ROOT comes with histogramming capabilities in an arbitrary number of dimensions, curve fitting, statistical modeling, and minimization, to allow the easy setup of a data analysis system that can query and process the data interactively or in batch mode, as well as a general parallel processing framework, RDataFrame, that can considerably speed up an analysis. -
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ArrayFire
ArrayFire, a general purpose GPU library
ArrayFire is a general-purpose tensor library that simplifies the process of software development for the parallel architectures found in CPUs, GPUs, and other hardware acceleration devices. The library serves users in every technical computing market. Data structures in ArrayFire are smartly managed to avoid costly memory transfers and to take advantage of each performance feature provided by the underlying hardware. The community of ArrayFire developers invites you to build with us if you're interested and able to write top performing tensor functions. ... -
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TensorRT
C++ library for high performance inference on NVIDIA GPUs
...With TensorRT, you can optimize neural network models trained in all major frameworks, calibrate for lower precision with high accuracy, and deploy to hyperscale data centers, embedded, or automotive product platforms. TensorRT is built on CUDA®, NVIDIA’s parallel programming model, and enables you to optimize inference leveraging libraries, development tools, and technologies in CUDA-X™ for artificial intelligence, autonomous machines, high-performance computing, and graphics. With new NVIDIA Ampere Architecture GPUs, TensorRT also leverages sparse tensor cores providing an additional performance boost. -
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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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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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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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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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PMCGPU
Parallel simulators for Membrane Computing on the GPU
Membrane Computing is a new research area (within Natural Computing) that aims to provide computing devices abstracted from the functioning and structure of living cells. These devices are called P systems. The objective of this project (PMCGPU) is to bring together all the researchers working on the development of parallel simulators for P systems, specially those using the GPU (e.g. -
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Chapel
a Productive Parallel Programming Language
Chapel is an emerging parallel programming language whose design and development are being led by HPE in collaboration with academia, computing labs, and industry. Chapel's goal is to improve the productivity of parallel programmers, from laptops to supercomputers. **Please note that Chapel development has moved to GitHub** -
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Advanced Simulation Library
Free multiphysics simulation software package
...Its computational engine is based, among others, on the Lattice Boltzmann Methods (http://en.wikipedia.org/wiki/Lattice_Boltzmann_methods) and is written in OpenCL (http://en.wikipedia.org/wiki/OpenCL) which enable extraordinarily efficient deployment (http://asl.org.il/benchmarks) on a variety of massively parallel architectures, ranging from inexpensive FPGAs, DSPs and GPUs up to heterogeneous clusters and supercomputers. The engine is hidden entirely behind C++ classes, so that no OpenCL knowledge is required from application programmers. ASL can be utilized to model various coupled physical and chemical phenomena and employed in a multitude of fields: computational fluid dynamics, virtual sensing, industrial process data validation and reconciliation, image-guided surgery, computer-aided engineering, high-performance scientific computing, etc.. -
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CUPBB
A Compute Unified Parallel Building Blocks Library Using GPU Computing
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Bat2015
Bachelor of Science (Informatik)
...With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do. -
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aCompute
Aims to enable researcher to tap in to mobile computing capability
This is a software agent based computing program that will enable researchers and other users to tap in computing power of machine available by sharing work load on the fly with zero configuration on network & resources A self organizing agent program that will understand network and its resource. where as the only job left to researcher is to split up jobs in several chunks of programs either parallel or sequential jobs and go issue the job (A visual Modeler or Scripting support need to be yet designed) Software agents will automatically manage the rest or resource management, sharing , cloning of tasks etc. ... -
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Ichnaea
Performance Timing Tools
Ichnaea is a set of tools that aid in collecting and tracking parameters and timings for parallel applications. The Performance Modelling Timing Module, PMTM, is a library that wraps system timing calls to abstract these from code developers and aid portability. It also has functionality to store parameters and print those, along with the timing information to a comma separated variable file. The Performance Modelling Analysis Tool, PMAT, is coming soon. This is able to read in and... -
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parSRA
Portable Framework for the Parallel Execution of Short Read Aligners
...It uses the following techniques in order to improve scalability: 1) a fast splitting of the input reads using the FUSE kernel module available in most of current Linux distributions; 2) a balanced on-demand distribution of the reads based on the shared locks of UPC++, an extension of C++ for parallel computing that follows the Partitioned Global Address Space (PGAS) paradigm. parSRA is portable as its configuration file allows the users to parallelize the execution of existing SRA tools without the need to modify the source code of parSRA or the aligner. -
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Center for Parallel Computing
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neuranep
Neural Network Engineering Platform
A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. NeuraNEP emulates a distributed processing environment capable of handling millions of microthreads in parallel, for example running neural networks with millions of spiking cells. Microthreads are general processing elements that can also represent non-neural elements, such as cell populations, extracellular space, emulating... -
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Genetic Programming in OpenCL is a parallel implementation of genetic programming targeted at heterogeneous devices, such as CPU and GPU. It is written in OpenCL, an open standard for portable parallel programming across many computing platforms.
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Ezys
Ezys 3D medical image registration program
Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ... -
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Fast Gauss-Legendre Quadrature Rules
Computes Gauss-Legendre quadrature nodes and weights
This software computes Gauss-Legendre quadrature nodes and weights using the formulas developed in "Iteration-Free Computation of Gauss-Legendre Quadrature Nodes and Weights", I. Bogaert, published in the SIAM Journal of Scientific Computing (Permalink: http://dx.doi.org/10.1137/140954969). The key features are: - Speed: due to the simplified formulas and the O(1) complexity computation of individual Gauss-Legendre quadrature nodes and weights. The latter also makes this software perfectly compatible with parallel computing paradigms. - Accuracy: the error on the nodes and weights is smaller than a few ulps (see the paper for details). -
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PPSeq: Parallel NGS Analysis
Parallel Processing for Next-Generation Sequencing (NGS) Analysis
High-throughput next generation sequencing (NGS) technology has quickly emerged as a powerful tool in many aspects of biomedical research. However, along with its rapid development, the data magnitude and analysis complexity for NGS far exceed the capacity and capability of traditional small-scale computing facilities, such as multithreading algorithms on standalone workstations. To address this issue, here we present a solution using the ever-increasing supply of processing power by massive parallel processing (MPP) systems.
