Search Results for "network performance" - Page 17
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Showing 688 open source projects for "network performance"
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The Neural Process Family
This repository contains notebook implementations
Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. They can learn distributions over functions from... -
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sharppcap
ully managed, cross platform
Fully managed, cross-platform (Windows, Mac, Linux) .NET library for capturing packets from live and file-based devices -
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OpenPPM
Project Portfolio Management
Open PPM is an open source product, used for Project Management and Project Portfolio Management, in accordance with the PMBOK® (Project Management Body of Knowledge) guide, from PMI® (Project Management Institute). -
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Zabbix
Enterprise-class, distributed monitoring solution for networks & apps
Zabbix is an enterprise-class open source distributed monitoring solution designed to monitor and track performance and availability of network servers, devices and other IT resources. It supports distributed and WEB monitoring, auto-discovery, and more. An enterprise-class distributed monitoring solution for networks & apps -
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BytePS
A high performance and generic framework for distributed DNN training
...We use Tesla V100 32GB GPUs and set batch size equal to 64 per GPU. Each machine has 8 V100 GPUs (32GB memory) with NVLink-enabled. Machines are inter-connected with 100 Gbps RDMA network. This is the same hardware setup you can get on AWS. -
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PyTracking
Visual tracking library based on PyTorch
A general python framework for visual object tracking and video object segmentation, based on PyTorch. Official implementation of the RTS (ECCV 2022), ToMP (CVPR 2022), KeepTrack (ICCV 2021), LWL (ECCV 2020), KYS (ECCV 2020), PrDiMP (CVPR 2020), DiMP (ICCV 2019), and ATOM (CVPR 2019) trackers, including complete training code and trained models. -
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OkDownload
A reliable, flexible, fast and powerful download engine
...The core library is Pure and light. More flexible callback mechanism and listener. More flexible to expand each part of OkDownload. Fewer threads to do the same thing without drop performance. File-IO thread pool is independent of Network-IO thread pool. Make sense auto filename from URL if can't find from response header. Cancel and Start is very effective especially for a bunch of tasks with tons of optimize. -
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Appmetrics
Node Application Metrics provides a foundational infrastructure
AppMetrics is a monitoring library for Node.js and Java applications, providing insights into application performance and resource usage. -
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VivaGraph
Graph drawing library for JavaScript
VivaGraphJS is a powerful, high-performance graph drawing library for JavaScript that enables developers to visualize complex networks directly in the browser or in Node.js environments. It is designed for speed and scalability, handling large graph datasets with smooth rendering and interactive capabilities such as dragging nodes and zooming. The library supports multiple rendering backends including SVG, WebGL, and Canvas, allowing developers to choose the best balance of performance and visual fidelity for their use case. ... -
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Greenlet
Move an async function into its own thread
...Since Greenlets can't rely on surrounding scope anyway, it's best to always create them at the "top" of your module. Greenlet is most effective when the work being done has relatively small inputs/outputs. One such example would be fetching a network resource when only a subset of the resulting information is needed. Greenlet will even accept and optimize transferables as arguments to and from a greenlet worker function. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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java-Kcp
Reliable udp network library (kcp algorithm) based on java netty
java-Kcp is a Java implementation of the KCP reliable UDP protocol built on top of Netty. It is designed for applications that need fast, reliable communication over UDP, especially games, video systems, and network acceleration services. The project includes forward error correction support and aims to remain compatible with other KCP implementations, including C, Go, and a related C# version. Its documentation provides server and client examples, usage parameters, best practices, troubleshooting notes, and performance testing information. ... -
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pytorch-examples
Simple examples to introduce PyTorch
...It also serves as a quick reference for common patterns and techniques used in deep learning workflows. The project aligns with PyTorch’s philosophy of combining usability with performance and flexibility. Overall, pytorch-examples is an essential learning resource for anyone working with PyTorch. -
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printThis
jQuery printing plugin; print specific elements on a page
...Accepts custom CSS/jQuery selectors. The amount of time to wait before calling print() in the printThis iframe. Defaults to 1000 milliseconds. Appropriate values depend heavily on the content and network performance. Graphics heavy, slow, or uncached content may need extra time to load. Use a custom page title on the iframe. This may be reflected on the printed page, depending on the settings. Blank by default. Copies style attributes from the body and html tags into the printThis iframe. Added to provide support for CSS Variables. ... -
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React Boilerplate
A highly scalable, offline-first foundation with the best DX
React Boilerplate is a highly scalable, offline-first foundation for React.js applications. It offers the best developer experience with a focus on performance and best practices. React Boilerplate offers predictable state management so you can take control of your app’s state and keep state mutations manageable. It also features next generation JavaScript, so you can stop worrying about browser support or use features like arrow functions, JSX syntax and more. There’s also support for next generation CSS, and being offline first, it allows availability without network connection from the moment your users load the app. ... -
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NeuroNER
Named-entity recognition using neural networks
..."deep learning") Is cross-platform, open source, freely available, and straightforward to use. Enables the users to create or modify annotations for a new or existing corpus. Train the neural network that performs the NER. During the training, NeuroNER allows monitoring of the network. Evaluate the quality of the predictions made by NeuroNER. The performance metrics can be calculated and plotted by comparing the predicted labels with the gold labels. -
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Mars
A cross-platform network component developed by WeChat
...It consists of four main parts: Comm, which contains a basic library, including basic tools like sockets, threads, alarm, message queues, and coroutines; Xlog, which provides high-performance, high-availability, security, and fault-tolerant log functions; SDT which is the network diagnosis module; and STN or signaling transmission network module, the major component of Mars responsible for the small data signaling channel between the terminal and the server. Mars has been proven effective by billions of WeChat users. ... -
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fft
A fast distributed file transfer
...Because it’s oriented around relays, it can better utilize geographically diverse infrastructure and avoid bottlenecks at any one egress point. The issue tracker highlights active concerns such as congestion control with many workers and IPv6 support, signaling performance-minded design goals. Overall, fft aims to give teams a fast, resilient way to move big artifacts using parallelism at the network edge. -
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Ceras
Universal binary serializer for a wide variety of scenarios
...It goes above and beyond in terms of features, speed, and comfort. Supports reference loops, large/complicated inheritance chains, splitting objects into parts. Ceras generally ranks at the top end of the performance spectrum, together with NetSerializer and MessagePack-CSharp. To get an idea of how Ceras performs here are the preliminary benchmark results. The resulting binary size is about the same as MessagePack-CSharp. Don't forget to tune the settings in SerializerConfig for your specific situation. Using Ceras to read/write network packets might require different settings than, lets say, saving a settings-object to a file, or persisting items/spells/monsters in a game. -
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Easy-TensorFlow
Simple and comprehensive tutorials in TensorFlow
...Furthermore, since most of the developers are using TensorFlow for code development, having hands-on on TensorFlow is a necessity these days. Tensorboard is a powerful visualization suite that is developed to track both the network topology and performance, making debugging even simpler. -
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RaptorJIT
A dynamic language for system programming (LuaJIT fork)
RaptorJIT is a Lua implementation suitable for high-performance low-level system programming. If you want to use a simple dynamic language to write a network stack; a hypervisor; a unikernel; a database; etc, then you have come to the right place. -
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DeepTraffic
DeepTraffic is a deep reinforcement learning competition
...The system presents a simulated multi-lane highway where an AI-controlled vehicle must navigate traffic while maximizing speed and avoiding collisions. Participants design neural network policies that determine the vehicle’s actions, such as accelerating, decelerating, changing lanes, or maintaining speed. The project was created as part of an educational competition associated with MIT’s deep learning courses, encouraging students and researchers to experiment with reinforcement learning techniques. The environment provides a coding interface where users can design neural network architectures and tune hyperparameters while observing their agent’s performance in a visual simulation. -
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Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
...Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not offer the data processing flexibility needed in research. Tensorpack squeezes the most performance out of pure Python with various auto parallelization strategies. There are too many symbolic function wrappers already. Tensorpack includes only a few common layers. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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Enemy Territory: Legacy
Based on the raedwulf-et project
etlegacy-deprecated is the archived version of ET: Legacy, a community-driven project that maintains and modernizes Wolfenstein: Enemy Territory, the classic team-based WWII multiplayer shooter. This legacy repository contains older iterations of the codebase, which aimed to preserve the original gameplay while improving security, portability, and performance on modern systems. Though deprecated in favor of the active repository, it offers insight into early modernization efforts and is...
