Search Results for "cpu benchmark linux" - Page 2
Sort By:
Showing 59 open source projects for "cpu benchmark linux"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
tvm
Open deep learning compiler stack for cpu, gpu, etc.
Apache TVM is an open source machine learning compiler framework for CPUs, GPUs, and machine learning accelerators. It aims to enable machine learning engineers to optimize and run computations efficiently on any hardware backend. The vision of the Apache TVM Project is to host a diverse community of experts and practitioners in machine learning, compilers, and systems architecture to build an accessible, extensible, and automated open-source framework that optimizes current and emerging... -
2
Fiber
Express inspired web framework written in Go
An Express-inspired web framework written in Go. Fiber is a Go web framework built on top of Fasthttp, the fastest HTTP engine for Go. It's designed to ease things up for fast development with zero memory allocation and performance in mind. Setting up routes for your application has never been so easy! The Express-like route definitions are easy to understand and work with. Serve your static HTML, CSS, and JavaScript files with ease by defining static routes. You can also serve the contents... -
3
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... -
4
MegEngine
Easy-to-use deep learning framework with 3 key features
...In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. Gain the lowest memory usage when inferencing a model by leveraging our unique pushdown memory planner. NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
5
TorchQuantum
A PyTorch-based framework for Quantum Classical Simulation
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing. -
6
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... -
7
pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
8
Execute JavaScript from Go
Execute JavaScript from Go
Execute JavaScript from Go. For scripts that are large or are repeatedly run in different contexts, it is beneficial to compile the script once and used the cached data from that compilation to avoid recompiling every time you want to run it. The v8go library would welcome contributions from anyone able to get an external windows build of the V8 library linking with v8go, using the version of V8 checked out in the deps/v8 git submodule, and documentation of the process involved. This process... -
9
MetalPetal
A GPU accelerated image and video processing framework built on Metal
MetalPetal is an image processing framework based on Metal designed to provide real-time processing for still images and video with easy-to-use programming interfaces. This chapter covers the key concepts of MetalPetal, and will help you to get a better understanding of its design, implementation, performance implications, and best practices. A MTIImage object is a representation of an image to be processed or produced. It does directly represent image bitmap data instead it has all the... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
-
10
SocketCluster
Highly scalable realtime pub/sub and RPC framework
Highly scalable pub/sub and RPC toolkit optimized for async/await. Pub/sub-channels are very cheap. You can have millions of unique channels without worrying about memory or CPU usage. Channels are automatically cleaned up when they are no longer used. The socket cluster CLI tool exposes kubectl (Kubernetes) shortcut commands to make deploying your app to any Kubernetes cluster really easy. All necessary Kubernetes .yaml files are provided. After deploying your app to a Kubernetes cluster,... -
11
ToolGood.Words
A high-performance sensitive word
A high-performance sensitive word (illegal word/dirty word) detection and filtering component, with a traditional and simplified exchange, supports full-width half-width exchange, Chinese characters to pinyin, fuzzy search, and other functions. C#Language, using StringSearchEx2.Replacefiltering, on a 48k sensitive thesaurus at over 300 million characters per second. (cpu i7 8750h). C#'s own regular is very slow, which StringSearchEx2.ContainsAnyis Regex.IsMatchmore than 88,000 times the... -
12
hashmap
A Golang lock-free thread-safe HashMap optimized for fastest access
A Golang lock-free thread-safe HashMap optimized for fastest read access. It is not a general-use HashMap and currently has slow write performance for write-heavy use. The minimal supported Golang version is 1.19 as it makes use of Generics and the new atomic package helpers. Reading from the hash map for numeric key types in a thread-safe way is faster than reading from a standard Golang map in an unsafe way and four times faster than Golang's sync.Map. Technical design decisions have been... -
13
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,... -
14
Yandex Tank
Load and performance benchmark tool
Yandex.Tank is an extensible open-source load testing tool for advanced Linux users which is especially good as a part of an automated load testing suite. Different load generators are supported. Evgeniy Mamchits' phantom is a very fast (100 000+ RPS) shooter written in C++ (default) JMeter is an extendable and widely known one. BFG is a Python-based generator that allows you to write your load scenarios in Python. Experimental Golang generator: pandora. Performance analytics backend... -
15
Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important... -
16
GPUImage 2
Framework for GPU-accelerated video and image processing
GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. ... -
17
Aqueduct
Dart HTTP server framework for building REST APIs
Aqueduct is a modern Dart HTTP server framework. The framework is composed of libraries for handling and routing HTTP requests, object-relational mapping (ORM), authentication and authorization (OAuth 2.0 provider) and documentation (OpenAPI). These libraries are used to build scalable REST APIs that run on the Dart VM. An object-oriented, multi-threaded HTTP server framework written in Dart. Aqueduct is an extensible HTTP framework for building REST APIs on top of the Dart VM. It includes a... -
18
Mocha.jl
Deep Learning framework for Julia
Mocha.jl is a deep learning framework for Julia, inspired by the C++ Caffe framework. It offers efficient implementations of gradient descent solvers and common neural network layers, supports optional unsupervised pre-training, and allows switching to a GPU backend for accelerated performance. The development of Mocha.jl happens in relative early days of Julia. Now that both Julia and the ecosystem has evolved significantly, and with some exciting new tech such as writing GPU kernels... -
19
Oyente
An Analysis Tool for Smart Contracts
A container with the required dependencies configured can be found here. The image is however outdated. We are working on pushing the latest image to dockerhub for your convenience. If you experience any issues with this image, please try to build a new docker image by pulling this codebase before open an issue. A collection of the utilities that were developed for the paper are in misc_utils. Use them at your own risk - they have mostly been disposable. This is an improved version of the... -
20
Crow
Crow is very fast and easy to use C++ micro web framework
Crow is C++ microframework for web. (inspired by Python Flask). If you just want to use crow, copy amalgamate/crow_all.h and include it. C++ compiler with good C++11 support (tested with g++>=4.8). Provide an amalgamated header file crow_all.h with every features. Handler arguments type check at compile time. Now supporting VS2013 with limited functionality (only run-time check for url is available.) Out-of-source build with CMake is recommended. -
21
Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform... -
22
Kitto
Kitto is a framework for interactive dashboards written in Elixir
Kitto is a framework for interactive dashboards written in Elixir. The source for the demo dashboards can be found at: kittoframework/demo. Jobs are supervised processes running concurrently. Widgets are coded in the popular React library. Uses a modern asset tool-chain, Webpack. Allows streaming SSE to numerous clients concurrently with low memory/CPU footprint. Easy to deploy using the provided Docker images, Heroku (guide) or Distillery (guide). Can serve assets in production. Keeps stats... -
23
Leaf
A game server framework in Go (golang)
Leaf, written in Go, is a open-source game server framework aiming to boost efficiency both in development and runtime. Simple APIs. Leaf tends to provide simple and plain interfaces which are always best for use. Self-healing. Leaf always tries to salvage the process from runtime errors instead of leaving it to crash. Multi-core support. Leaf utilize its modules and leaf/go to make use of CPU resouces at maximum while avoiding varieties of side effects may be caused. Each module runs inside... -
24
File system/directory monitoring utilities with loggin and task processing support (can execute files or make a WCF service call). Multiple configuration options. Source code libraries can be used to create a custom file system monitor.
-
25
selenium2lib
A selenium common library based on selenium 2.0, webdriver
selenium2lib is the common lib based on the popular web automation test framework(selenium 2.0) and this project include: 1. webdriver function testing help class, such as selenium 2.0 proxy class, selenium 1.0 proxy class, javascript executor proxy class, webdriver event listener extension, webdriver wait extension, webdriver factory,webdriver wrapped element(S2Div?, S2Table?), autoit java wrapped helper class, use snapsie to capture full image of IE browser, use camstudio to record DV...
