C++ Parallel

Open-source C++ projects categorized as Parallel

Top 23 C++ Parallel Projects

  • LightGBM

    A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

  • Project mention: SIRUS.jl: Interpretable Machine Learning via Rule Extraction | /r/Julia | 2023-06-29

    SIRUS.jl is a pure Julia implementation of the SIRUS algorithm by Bénard et al. (2021). The algorithm is a rule-based machine learning model meaning that it is fully interpretable. The algorithm does this by firstly fitting a random forests and then converting this forest to rules. Furthermore, the algorithm is stable and achieves a predictive performance that is comparable to LightGBM, a state-of-the-art gradient boosting model created by Microsoft. Interpretability, stability, and predictive performance are described in more detail below.

  • Taskflow

    A General-purpose Parallel and Heterogeneous Task Programming System

  • Project mention: Improvements of Clojure in his time | /r/Clojure | 2023-06-16

    For parallel programming nowadays, personally I reach for C++ Taskflow when I really care about performance, or a mix of core.async and running multiple load balanced instances when I’m doing more traditional web backend stuff in Clojure.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • napajs

    Napa.js: a multi-threaded JavaScript runtime

  • Project mention: A list of JavaScript engines, runtimes, interpreters | /r/learnjavascript | 2023-12-10

    Napa.js

  • root

    The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

  • Project mention: If you can't reproduce the model then it's not open-source | news.ycombinator.com | 2024-01-17

    I think the process of data acquisition isn't so clear-cut. Take CERN as an example: they release loads of data from various experiments under the CC0 license [1]. This isn't just a few small datasets for classroom use; we're talking big-league data, like the entire first run data from LHCb [2].

    On their portal, they don't just dump the data and leave you to it. They've got guides on analysis and the necessary tools (mostly open source stuff like ROOT [3] and even VMs). This means anyone can dive in. You could potentially discover something new or build on existing experiment analyses. This setup, with open data and tools, ticks the boxes for reproducibility. But does it mean people need to recreate the data themselves?

    Ideally, yeah, but realistically, while you could theoretically rebuild the LHC (since most technical details are public), it would take an army of skilled people, billions of dollars, and years to do it.

    This contrasts with open source models, where you can retrain models using data to get the weights. But getting hold of the data and the cost to reproduce the weights is usually prohibitive. I get that CERN's approach might seem to counter this, but remember, they're not releasing raw data (which is mostly noise), but a more refined version. Try downloading several petabytes of raw data if not; good luck with that. But for training something like a LLM, you might need the whole dataset, which in many cases have its own problems with copyrights…etc.

    [1] https://opendata.cern.ch/docs/terms-of-use

    [2] https://opendata.cern.ch/docs/lhcb-releases-entire-run1-data...

    [3] https://root.cern/

  • parallel-hashmap

    A family of header-only, very fast and memory-friendly hashmap and btree containers.

  • Project mention: The One Billion Row Challenge in CUDA: from 17 minutes to 17 seconds | news.ycombinator.com | 2024-04-13

    Standard library maps/unordered_maps are themselves notoriously slow anyway. A sparse_hash_map from abseil or parallel-hashmaps[1] would be better.

    [1] https://github.com/greg7mdp/parallel-hashmap

  • thread-pool

    BS::thread_pool: a fast, lightweight, and easy-to-use C++17 thread pool library

  • moose

    Multiphysics Object Oriented Simulation Environment

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • Vc

    SIMD Vector Classes for C++

  • RaftLib

    The RaftLib C++ library, streaming/dataflow concurrency via C++ iostream-like operators

  • HiGHS

    Linear optimization software

  • Project mention: Algorithms - Researchers Approach New Speed Limit for Seminal Problem | news.ycombinator.com | 2024-01-29
  • libfork

    A bleeding-edge, lock-free, wait-free, continuation-stealing tasking library built on C++20's coroutines

  • libgrape-lite

    🍇 A C++ library for parallel graph processing (GRAPE) 🍇

  • rapidgzip

    Gzip Decompression and Random Access for Modern Multi-Core Machines

  • Project mention: Show HN: Rapidgzip – Parallel Gzip Decompressing with 10 GB/S | news.ycombinator.com | 2023-09-04
  • YACLib

    Yet Another Concurrency Library

  • cvise

    Super-parallel Python port of the C-Reduce

  • rangeless

    c++ LINQ -like library of higher-order functions for data manipulation

  • ips4o

    In-place Parallel Super Scalar Samplesort (IPS⁴o)

  • elbencho

    A distributed storage benchmark for file systems, object stores & block devices with support for GPUs

  • rocPRIM

    ROCm Parallel Primitives

  • firebuild

    Automatic build accelerator cache for Linux

  • Project mention: I Improved My Rust Compile Times by 75% | news.ycombinator.com | 2024-03-19
  • charly-vm

    Fully parallel dynamically typed programming language

  • indexed_bzip2

    Fast parallel random access to bzip2 and gzip files in Python

  • ParallelReductionsBenchmark

    Thrust, CUB, TBB, AVX2, CUDA, OpenCL, OpenMP, SyCL - all it takes to sum a lot of numbers fast!

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

C++ Parallel related posts

Index

What are some of the best open-source Parallel projects in C++? This list will help you:

Project Stars
1 LightGBM 16,043
2 Taskflow 9,552
3 napajs 9,238
4 root 2,418
5 parallel-hashmap 2,316
6 thread-pool 1,924
7 moose 1,570
8 Vc 1,418
9 RaftLib 923
10 HiGHS 800
11 libfork 452
12 libgrape-lite 365
13 rapidgzip 314
14 YACLib 246
15 cvise 195
16 rangeless 192
17 ips4o 159
18 elbencho 147
19 rocPRIM 143
20 firebuild 117
21 charly-vm 93
22 indexed_bzip2 66
23 ParallelReductionsBenchmark 59

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