Parallel Computing
Showing 36 of 186 projects
Portable implementation of Grand Central Dispatch (GCD) for concurrent code execution on multicore hardware across Swift platforms.
A general-purpose GPU compute framework built on Vulkan for cross-vendor graphics cards, enabling high-performance data processing and machine learning.
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
NVIDIA's implementation of the C++ Standard Library for CUDA C++ development.
A cross-platform, dependency-free C++ and Python DAG framework for building parallel computational graphs.
A Node.js module that implements the Web Worker API using native threads for CPU-bound tasks.
A distributed query execution engine that extends Apache DataFusion to run SQL queries in parallel across multiple nodes.
A hybrid thread/fiber task scheduler for C++11 that enables efficient execution of blocking tasks.
A visual workflow-based AI deployment framework for multi-platform and multi-backend inference, supporting large models and edge devices.
A Go toolkit for building concurrent programs using composable, channel-based pipelines with automatic error propagation.
A header-only C++ library for CUDA providing accelerated primitives for solving irregularly parallel problems on GPUs.
A JIT compiler for writing high-performance GPU programs in .NET languages like C#, offering CUDA-level performance with C# convenience.
A high-performance, feature-rich Entity Component System (ECS) library for Rust game development with minimal boilerplate.
A collection of high-performance GICP-based point cloud registration algorithms with multi-threaded and GPU-accelerated implementations.
A C++ GPU computing library providing an STL-like interface for OpenCL-based parallel programming.
A distributed map-reduce framework for parallel computations over large datasets on unreliable computer clusters.
A computational parallel flow library for Elixir built on top of GenStage for parallel processing of collections.
A portable C++ library providing SIMD vector types for explicit data-parallel programming with zero-overhead abstractions.
A C++-based high-performance parallel environment execution engine for vectorized reinforcement learning simulations.
A lightweight concurrency framework for C++11 inspired by Microsoft PPL, providing tasks, parallel algorithms, and schedulers.
A collection of reusable scientific computing software components for solving large-scale, complex multi-physics engineering problems.
A functional programming toolkit for R that enhances data manipulation with consistent, type-stable functions for working with vectors and lists.
A functional programming toolkit for R that enhances data manipulation with consistent, type-stable functions.
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 Python library for parallel active learning of mathematical functions, intelligently sampling parameter spaces to minimize evaluations.
High-performance, end-to-end reinforcement learning implementations fully written in JAX for massive parallelization on GPUs.
A microbenchmark that spawns one million concurrent actors/coroutines to compare concurrency performance across programming languages.
A C++ library for parallel text file reading with CSV support and Python bindings.
A reactive programming library for C++14 that enables declarative data dependencies and automatic change propagation.
A tool for running Appium tests in parallel across Android and iOS real devices and simulators.
A C++ template library providing high-performance SIMD-accelerated sorting algorithms for integers, floats, and custom objects.
Python bindings for MPI
A JAX-based library providing accelerated reinforcement learning environments with full compatibility to the classic gym API.
An evolutionary optimization library for Go implementing genetic algorithms, particle swarm optimization, differential evolution, and other algorithms.
Thin, unified C++ wrappers for NVIDIA's CUDA APIs (Runtime, Driver, NVRTC, NVTX) that improve safety and ease of use.
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