Search Results for "parallel"
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Showing 29 open source projects for "parallel"
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
...It brings together Thrust, CUB, and libcudacxx, which collectively provide high-level abstractions, low-level performance primitives, and a CUDA-compatible standard library for GPU programming. The goal of CCCL is to simplify CUDA development by offering reusable building blocks that enable developers to write efficient and scalable parallel code without starting from scratch. Thrust provides a high-level interface for parallel algorithms, while CUB delivers highly optimized primitives for device-level operations, and libcudacxx ensures compatibility with modern C++ standards. By unifying these components, CCCL reduces duplication and improves developer productivity while maintaining performance across different GPU architectures. -
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FasterLIO
Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry
Faster-LIO is a lightweight, tightly coupled LiDAR-inertial odometry system for pose tracking and point-cloud mapping. It builds on FastLIO2 while replacing key spatial operations with parallel sparse incremental voxels. The design targets high update rates for both solid-state and spinning LiDAR sensors. It fuses LiDAR measurements with inertial data through an iterative Kalman-filter-based estimation pipeline. The software supports online ROS operation as well as offline processing of recorded bag files. Users can compile it with CMake or catkin, run it through Docker, visualize output in RViz, and save trajectories and point clouds. ... -
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ChrysaLisp
Parallel OS, with GUI, Terminal, OO Assembler, Class libraries
ChrysaLisp is a 64-bit, MIMD, multi-CPU, multi-threaded, multi-core, multi-user parallel operating system with features such as a GUI, terminal, OO Assembler, class libraries, C-Script compiler, Lisp interpreter, debugger, profiler, vector font engine, and more. It supports MacOS, Windows, and Linux for x64, Riscv64, and Arm64 and eventually will move to bare metal. It also allows the modeling of various network topologies and the use of ChrysaLib hub nodes to join heterogeneous host networks. ... -
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TensorStore
Library for reading and writing large multi-dimensional arrays
...It separates the logical view (shape, dtype, chunking) from the physical layout so the same code can target Zarr, N5, TIFF pyramids, or custom backends. Rich indexing, slicing, and broadcasting operations make it feel like a familiar array API, while asynchronous I/O pipelines stream chunks efficiently in parallel. Transactional semantics allow atomic updates and consistent snapshots, which is essential for large, shared datasets used by ML and scientific workflows. The library is engineered for scalability—background caching, chunk sharding, and retryable operations keep throughput high even over unreliable networks. With language bindings, it fits into Python-heavy analysis pipelines while retaining a fast C++ core. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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XGBoost
Scalable and Flexible Gradient Boosting
...It supports regression, classification, ranking and user defined objectives, and runs on all major operating systems and cloud platforms. XGBoost works by implementing machine learning algorithms under the Gradient Boosting framework. It also offers parallel tree boosting (GBDT, GBRT or GBM) that can quickly and accurately solve many data science problems. XGBoost can be used for Python, Java, Scala, R, C++ and more. It can run on a single machine, Hadoop, Spark, Dask, Flink and most other distributed environments, and is capable of solving problems beyond billions of examples. -
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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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frugally-deep
A lightweight header-only library for using Keras (TensorFlow) models
...Utterly ignores even the most powerful GPU in your system and uses only one CPU core per prediction. Quite fast on one CPU core, and you can run multiple predictions in parallel, thus utilizing as many CPUs as you like to improve the overall prediction throughput of your application/pipeline. -
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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. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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mold
A Modern Linker
Mold is a modern high-performance linker designed as a drop-in replacement for traditional Unix linkers, with a primary goal of dramatically reducing build times for large software projects. In compiled languages like C, C++, and Rust, the linking phase can become a significant bottleneck, especially in large codebases, and mold addresses this by leveraging highly optimized algorithms and extensive parallelism. It is capable of utilizing all available CPU cores efficiently, resulting in... -
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NeoPixelBus
An Arduino NeoPixel support library
...There are multiple competing libraries, FastLED being the biggest and Adafruit NeoPixel being the most common for beginners. On ESP32, both FastLED and NeoPixelBus can provide more than one channel/bus. FastLED primarily uses RMT to support 8 parallel channels. NeoPixelBus now supports the RMTs 8 channels and two more channels using i2s. -
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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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QtContribs - Harbour Qt Projects
New home to HbQt, HbIDE & HbDBU once Harbour SVN hosted contribs.
This is the repository to host all those Harbour's contrib libraries and applications which could not comply with strict Harbour project goals but had the potentiality to march into the future. The goal is to keep this repository parallel with Harbours contrib and use the same build system which Harbour uses. This way it will be possible easily to shift any library/application from here to Harbour or vice-verse. As I am totally ignorant of Harbour's build system, it will be appreciated if someone knowledgeable take over this responsibility, which might be one-time task. ... -
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eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original... -
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Thrust
The C++ parallel algorithms library
Thrust is the C++ parallel algorithms library which inspired the introduction of parallel algorithms to the C++ Standard Library. Thrust's high-level interface greatly enhances programmer productivity while enabling performance portability between GPUs and multicore CPUs. It builds on top of established parallel programming frameworks (such as CUDA, TBB, and OpenMP). -
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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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FastFlow: programming multi-core
Pattern-based multi/many-core parallel programming framework
FastFlow is a C/C++ programming framework supporting the development of pattern-based parallel programs on multi/many-core, GPUs and distributed platforms. FastFlow run-time is built upon non-blocking threads and lock-free queues. Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on commodity multi-core. ... -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
Tiramisu is a compiler for expressing fast and portable data parallel computations. It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. ... -
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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. -
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instantFSM
C++ inline state machine library
instantFSM is a header-only C++ state machine library. Its goal is to make state machine declaration and use easy enough that it can be integrated into your projects painlessly. Have a look atp the wiki where you will find a tutorial, samples, and a cheatsheet to get accustomed with instantFSM. The only instantFSM header file is downloadable from the files section or you can check it out from the git repository. -
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MapReduce++ is a project for implementation of parallel algorithms. It has currently two C++ implementations of the MapReduce abstraction: the MapMP library (multiprocessors) and the MaPI framework (multicomputers).
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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. Each microthread is conceptually similar to a task in Ada and it is much lighter weight than an operating system thread. SpikeOS was designed to handle millions of microthreads, for example in a neural network hosting millions of spiking model neurons.
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Ash C++ Template Library (AshTL)
Hashing and spatial concurrency library.
AshTL aims to provide a complete framework for dealing with spatial data in an efficient, parallel manner. As such, we primarily provide container classes and data types relating to 2D and 3D coordinate grids. AshTL is currently in alpha development (some features may not work correctly, and interfaces are likely to change). While in alpha and beta development, AshTL is licensed under AGPL v3+. Stable releases will include an exception so that AshTL itself will always be AGPL, but will not force code that uses it to be. -
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FeedForwardNeuralNetworkC++
Feedforward Neural Network writen in C++
Feedforward Neural Network writen in C++ serial and parallelized in TBB library. Also using Autotune library for best parallel performance. -
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Qpnc is a high level library developed using the Qt4 framework. It provides a set of data containers and operation abstracts used to declare a set of numerical computations, witch in turn are automatically executed in a parallel fashion.
