Showing 118 open source projects for "cpu benchmark linux"

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  • 1
    Android Contacts, Reborn

    Android Contacts, Reborn

    Android Contacts API Library written in Kotlin

    This library provides a complete set of APIs to do everything you need with Contacts in Android. You no longer have to deal with the Contacts Provider, database operations, and cursors. Whether you just need to get all or some Contacts for a small part of your app (written in Kotlin or Java), or you are looking to create your own full-fledged Contacts app with the same capabilities as the AOSP Android Contacts app and Google Contacts app, this library is for you.
    Downloads: 0 This Week
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  • 2
    cocoyaxi

    cocoyaxi

    A go-style coroutine library in C++11 and more

    ...Support system API hook (Windows/Linux/Mac), you can directly use third-party network library in coroutine.
    Downloads: 0 This Week
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  • 3
    AIMET

    AIMET

    AIMET is a library that provides advanced quantization and compression

    Qualcomm Innovation Center (QuIC) is at the forefront of enabling low-power inference at the edge through its pioneering model-efficiency research. QuIC has a mission to help migrate the ecosystem toward fixed-point inference. With this goal, QuIC presents the AI Model Efficiency Toolkit (AIMET) - a library that provides advanced quantization and compression techniques for trained neural network models. AIMET enables neural networks to run more efficiently on fixed-point AI hardware...
    Downloads: 2 This Week
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  • 4
    Jupyter Docker Stacks

    Jupyter Docker Stacks

    Ready-to-run Docker images containing Jupyter applications

    Jupyter Docker Stacks provides a curated set of ready-to-run Docker container images that bundle Jupyter applications with popular data science and computing tools, enabling users to quickly start working in a reproducible environment. These stacks support a range of use cases, from lightweight base notebook images to full featured environments that include scientific computing libraries, machine learning tools, and IDE-like notebook interfaces, all within Docker containers that run...
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    Honggfuzz

    Honggfuzz

    Security oriented software fuzzer

    honggfuzz is a general-purpose, high-performance fuzzer that mixes coverage feedback with practical crash triage to uncover memory-safety and logic bugs. It supports multiple fuzzing modes—stdin, file, and networking—so targets can be exercised the same way they run in production. Instrumentation via compiler hooks or hardware/perf counters guides mutations toward previously unseen edges, while persistent mode keeps the target process alive to amortize startup costs. The tool integrates...
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  • 6
    GoNB

    GoNB

    GoNB, a Go Notebook Kernel for Jupyter

    Go is a compiled language, but with very fast compilation, that allows one to use it in a REPL (Read-Eval-Print-Loop) fashion, by inserting a "Compile" step in the middle of the loop -- so it's a Read-Compile-Run-Print-Loop — while still feeling very interactive. GoNB leverages that compilation speed to implement a full-featured (at least it's getting there) Jupyter notebook kernel. As a side benefit it works with packages that use CGO — although it won't parse C code in the cells, so it...
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  • 7
    PennyLane

    PennyLane

    A cross-platform Python library for differentiable programming

    A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,...
    Downloads: 0 This Week
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  • 8
    AWS IoT Device Defender Library

    AWS IoT Device Defender Library

    Client library for using AWS IoT Defender service on embedded devices

    The Device Defender library enables you to send device metrics to the AWS IoT Device Defender Service. This library also supports custom metrics, a feature that helps you monitor operational health metrics that are unique to your fleet or use case. For example, you can define a new metric to monitor the memory usage or CPU usage on your devices. This library has no dependencies on any additional libraries other than the standard C library, and therefore, can be used with any MQTT client...
    Downloads: 1 This Week
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  • 9
    ProbabilisticCircuits.jl

    ProbabilisticCircuits.jl

    Probabilistic Circuits from the Juice library

    This module provides a Julia implementation of Probabilistic Circuits (PCs), tools to learn structure and parameters of PCs from data, and tools to do tractable exact inference with them. Probabilistic Circuits provides a unifying framework for several family of tractable probabilistic models. PCs are represented as computational graphs that define a joint probability distribution as recursive mixtures (sum units) and factorizations (product units) of simpler distributions (input units)....
    Downloads: 0 This Week
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  • 10
    Hasktorch

    Hasktorch

    Tensors and neural networks in Haskell

    Hasktorch is a powerful Haskell library for tensor computation and neural network modeling, built on top of libtorch (the backend of PyTorch). It brings differentiable programming, automatic differentiation, and efficient tensor operations into Haskell’s strongly typed functional paradigm. This project is in active development, so expect changes to the library API as it evolves. We would like to invite new users to join our Hasktorch discord space for questions and discussions....
    Downloads: 5 This Week
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  • 11

    ulttiny

    tiny User Level Threads library

    The ulttiny library is small, easy to use and very fast. It's optimized especially for scenarios where tasks and task groups are dynamically and concurrently created on the fly.
    Downloads: 0 This Week
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  • 12
    Generic Image Decoder

    Generic Image Decoder

    A standalone, portable generic Ada package for decoding images

    The Generic Image Decoder is a package for decoding a broad variety of image formats, from any data stream, to any kind of medium. Unconditionally portable code: OS-, CPU-, compiler- independent code. More information on... http://gen-img-dec.sf.net Alire crate: https://alire.ada.dev/crates/gid Mirror: https://github.com/zertovitch/gid
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    Downloads: 55 This Week
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  • 13
    HighwayHash

    HighwayHash

    Fast strong hash functions: SipHash/HighwayHash

    HighwayHash is a fast, keyed hash function intended for scenarios where you need strong, DoS-resistant hashing without the full overhead of a general-purpose cryptographic hash. It’s designed to defeat hash-flooding attacks by mixing input with wide SIMD operations and a branch-free inner loop, so adversaries can’t cheaply craft many colliding keys. The implementation targets multiple CPU families with vectorized code paths while keeping a portable fallback, yielding high throughput across...
    Downloads: 0 This Week
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  • 14
    LinAsm

    LinAsm

    Collection of fast and optimized assembly libraries for x86-64 Linux

    LinAsm is collection of very fast and SIMD optimized assembly written libraries for x86-64 Linux. It implements many common and widely used algorithms for array manipulations: searching, sorting, arithmetic and vector operations, unit conversions; fast mathematical and statistic functions; numbers and time converting algorithms; finite impulse response (FIR) digital filters; spectrum analysis algorithms, Fast Hartley transformation; CPU cache friendly functions and extremely fast abstract data types (ADT) such as hash tables b-trees, and much more. ...
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    Downloads: 19 This Week
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  • 15
    MMDeploy

    MMDeploy

    OpenMMLab Model Deployment Framework

    MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN...
    Downloads: 2 This Week
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  • 16
    Neural Tangents

    Neural Tangents

    Fast and Easy Infinite Neural Networks in Python

    Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,...
    Downloads: 1 This Week
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  • 17
    LMAX Disruptor

    LMAX Disruptor

    High performance inter-thread messaging library

    LMAX aims to be the fastest trading platform in the world. Clearly, in order to achieve this we needed to do something special to achieve very low-latency and high-throughput with our Java platform. Performance testing showed that using queues to pass data between stages of the system was introducing latency, so we focused on optimising this area. The Disruptor is the result of our research and testing. We found that cache misses at the CPU-level, and locks requiring kernel arbitration are...
    Downloads: 0 This Week
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  • 18
    DIG

    DIG

    A library for graph deep learning research

    The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to...
    Downloads: 0 This Week
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  • 19

    SimpleXlsxWriter

    C++ library for creating XLSX files for MS Excel 2007 and above.

    This library represents XLSX files writer for Microsoft Excel 2007 and above. The main feature of this library is that it uses C++ standard file streams. On the one hand it results in almost unnoticeable memory and CPU resources consumption while processing (that may be very useful at saving a large data arrays), but on the other hand it makes unfeasible to edit data that were written. Hence, if using this library the structure of the future report should be known enough. The library...
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    Downloads: 8 This Week
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  • 20

    Proteus Model Builder

    GUI for training of neural network models for GuitarML Proteus

    GUI for easier installation and training of neural network models for guitar amplifiers and pedals, based on the GuitarML Proteus models. These are usable for Proteus, Chowdhury-DSP BYOD and even NeuralPi, on all platforms incl. Linux and RaspberryPi. What is this? GuitarML's work on Proteus, NeuralPi and Proteusboard (hardware) is amazing. https://github.com/GuitarML Yet, it is not easy to wrap your head around if you are not familiar with programming, AI, machine learning, neuronal...
    Downloads: 8 This Week
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  • 21

    cppcrypto

    C++ cryptographic library (modern hash functions, ciphers, KDFs)

    cppcrypto provides optimized implementations of cryptographic primitives. Hash functions: BLAKE, BLAKE2, Echo, Esch, Groestl, JH, Kupyna, MD5, SHA-1, SHA-2, SHA-3, SHAKE, Skein, SM3, Streebog, Whirlpool. Block ciphers: Anubis, Aria, Camellia, CAST-256, Kalyna, Kuznyechik, Mars, Serpent, Simon, SM4, Speck, Threefish, Twofish, and Rijndael (AES) with all block/key sizes. Stream ciphers: HC-128, HC-256, Salsa20, XSalsa20, ChaCha, XChaCha. Encryption modes: CBC, CTR. AEAD modes:...
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    Downloads: 3 This Week
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  • 22
    How They DevOps

    How They DevOps

    A curated collection of publicly available resources

    How They DevOps is a collection of public writeups, posts, and references that show how well-known companies actually implement DevOps practices in the real world. Instead of describing DevOps in the abstract, it points to concrete CI/CD setups, infrastructure choices, incident processes, and tooling stacks used by tech organizations. This gives learners and teams a reality check: DevOps at scale is opinionated, messy, and adapted to business constraints. It’s especially useful for people...
    Downloads: 0 This Week
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  • 23
    Darknet YOLO

    Darknet YOLO

    Real-Time Object Detection for Windows and Linux

    This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project.
    Downloads: 17 This Week
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  • 24
    Cancelable Async Flows

    Cancelable Async Flows

    Cancelable Async Flows (CAF)

    CAF (Cancelable Async Flows) is a small utility that brings cooperative cancellation to JavaScript async workflows. It wraps async generators or promise-returning functions so they can respond to a cancel signal and halt work early, preventing wasted CPU and stray side effects. The library encourages a disciplined pattern: pass a token into your task, periodically check it, and unwind gracefully when cancellation is requested. This approach avoids brittle timeouts and “fire-and-forget” leaks...
    Downloads: 0 This Week
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  • 25
    Darknet

    Darknet

    Convolutional Neural Networks

    Darknet is an open source neural network framework written in C and CUDA, developed by Joseph Redmon. It is best known as the original implementation of the YOLO (You Only Look Once) real-time object detection system. Darknet is lightweight, fast, and easy to compile, making it suitable for research and production use. The repository provides pre-trained models, configuration files, and tools for training custom object detection models. With GPU acceleration via CUDA and OpenCV integration,...
    Downloads: 30 This Week
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