Search Results for "cpu-z linux" - Page 2
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Showing 100 open source projects for "cpu-z linux"
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parallel-ssh
Asynchronous parallel SSH client library.
parallel-ssh is an asynchronous parallel SSH library designed for large-scale automation. It differentiates itself from alternatives, other libraries and higher-level frameworks like Ansible or Chef in several ways. -
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CrossDB
Ultra High-performance Lightweight Embedded and Server OLTP RDBMS
CrossDB is a ultra high-performance, lightweight embedded and server OLTP RDBMS. It is designed for high-performance scenarios where the main memory can hold the entire database. -
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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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RLax
Library of JAX-based building blocks for reinforcement learning agents
RLax (pronounced “relax”) is a JAX-based library developed by Google DeepMind that provides reusable mathematical building blocks for constructing reinforcement learning (RL) agents. Rather than implementing full algorithms, RLax focuses on the core functional operations that underpin RL methods—such as computing value functions, returns, policy gradients, and loss terms—allowing researchers to flexibly assemble their own agents. It supports both on-policy and off-policy learning, as well as... -
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Napkin Math
Techniques and numbers for estimating system's performance
Napkin Math is a technical reference project for estimating software system performance from first principles. It collects practical numbers, benchmark-style measurements, and mental models that help engineers make fast back-of-the-envelope calculations. The project is useful for questions like how much memory throughput matters, how long storage operations may take, what network latency to expect, or how expensive logging could become at high request volume. It treats these values as... -
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Face Alignment
2D and 3D Face alignment library build using pytorch
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning-based face alignment method. For numerical evaluations, it is highly recommended to use the lua version which uses identical models with the ones evaluated in the paper. More models will be added soon. By default, the package will use the SFD face detector. However, the users can alternatively... -
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Faiss
Library for efficient similarity search and clustering dense vectors
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning. Faiss is written in C++ with complete wrappers for Python/numpy. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research. Faiss contains several methods for similarity search. It... -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of... -
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ArrayFire
ArrayFire, a general purpose GPU library
...Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. Built-in visualization functions through Forge. -
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Amazon EC2 Instance Selector
A CLI tool and go library which recommends instance types
A CLI tool and go library which recommends instance types based on resource criteria like vcpus and memory. There are over 270 different instance types available on EC2 which can make the process of selecting appropriate instance types difficult. Instance Selector helps you select compatible instance types for your application to run on. The command-line interface can be passed resource criteria like vcpus, memory, network performance, and much more and then return the available, matching... -
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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. -
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Binaryen
Compiler infrastructure and toolchain library for WebAssembly
Binaryen is a compiler and toolchain infrastructure library for WebAssembly, written in C++. It aims to make compiling to WebAssembly easy, fast, and effective. Binaryen has a simple C API in a single header, and can also be used from JavaScript. It accepts input in WebAssembly-like form but also accepts a general control flow graph for compilers that prefer that. Binaryen's internal IR uses compact data structures and is designed for completely parallel codegen and optimization, using all... -
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POCO
Cross-platform C++ libraries for building network applications
The POCO C++ Libraries are powerful cross-platform C++ libraries for building network- and internet-based applications that run on desktop, server, mobile, IoT, and embedded systems. Whether building automation systems, industrial automation, IoT platforms, air traffic management systems, enterprise IT application and infrastructure management, security and network analytics, automotive infotainment and telematics, financial or healthcare, C++ developers have been trusting the POCO C++... -
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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. -
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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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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... -
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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,... -
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DCV Color Primitives
DCV Color Primitives Library
DCV Color Primitives is a library to perform image color model conversion. Aware of the underlying hardware and supplemental cpu extension sets (up to avx2). Support data coming from a single buffer or coming from multiple image planes. Support non-tightly packed data. Support images greater than 4GB (64 bit). Convert an image from bgra to nv12 (single plane) format containing yuv in BT601. You might want to propagate errors to the caller function or mix with some other error types. So far,... -
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DGL
Python package built to ease deep learning on graph
Build your models with PyTorch, TensorFlow or Apache MXNet. Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers.... -
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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... -
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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).... -
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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.... -
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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. -
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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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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...
