Search Results for "cpu memory usage"
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Showing 36 open source projects for "cpu memory usage"
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MSA: Memory Sparse Attention
Trainable latent-memory framework for 100M-token contexts
MSA, or Memory Sparse Attention, is a research framework for scaling language-model memory to extremely long contexts. It replaces full attention over all tokens with sparse selection of compressed latent memory states. Document-wise rotary position encoding and top-k routing keep training and inference close to linear complexity. A tiered KV-cache design stores routing keys on GPU while larger content states can remain on CPU. -
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EaseProbe
A simple, standalone, and lightweight tool
...Support the bastion/jump server. Connect to a given port using TLS and (optionally) validate for revoked or expired certificates. Run an SSH command on a remote host and check the CPU, Memory, and Disk usage. MySQL. Connect to a MySQL server and run the SHOW STATUS SQL. Redis. Connect to a Redis server and run the PING command. Memcache. Connect to a Memcache server and run the version command or validate a given key/value pair. MongoDB. Connect to a MongoDB server and perform a ping. Kafka. Connect to a Kafka server and perform a list of all topics. -
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Nebulex
In-memory and distributed caching toolkit for Elixir
Nebulex provides support for transparently adding caching into an existing Elixir application. Similar to Ecto, the caching abstraction allows consistent use of various caching solutions with minimal impact on the code. Nebulex cache abstraction shields developers from directly dealing with the underlying caching implementations, such as Redis, Memcached, or even other Elixir cache implementations like Cachex. Additionally, it provides totally out-of-box features such as cache usage... -
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Netty-socketio
Socket.IO server implemented on Java
...YourKit is kindly supporting this open source project with its full-featured Java Profiler. YourKit, LLC is the creator of innovative and intelligent tools for profiling Java and .NET applications. CentOS, 1 CPU, 4GB RAM runned on VM, CPU 10%, Memory 15%, 6000 xhr-long polling sessions or 15000 websockets sessions, 4000 messages per second. -
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AWS IoT Device Defender Library
Client library for using AWS IoT Defender service on embedded devices
...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 library. This library is distributed under the MIT Open Source License. This library has gone through code quality checks including verification that no function has a GNU Complexity score over 8, and checks against deviations from mandatory rules in the MISRA coding standard. ... -
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bitnet.cpp
Official inference framework for 1-bit LLMs
bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous... -
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JetCache
JetCache is a Java cache framework
JetCache is a Java cache abstraction that provides uniform usage for different caching solutions. It provides more powerful annotations than those in Spring Cache. The annotations in JetCache support native TTL, two-level caching, and automatically refresh in distributed environments, also you can manipulate Cache instances by your code. Currently, there are four implementations: RedisCache, TairCache(not open source on github), CaffeineCache (in memory) and a simple LinkedHashMapCache (in memory). -
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Eclipse Collections
Eclipse Collections is a collections framework for Java
...Many container types include immutable collections, primitive collections, bimaps, multimaps and bags. You can make use of various container types, leveraging handy factory methods for instantiation. Eclipse Collections provides a memory-efficient implementation of Sets and Maps as well as primitive collections. Check out the Eclipse Collections Kata, a fun way to help you learn idiomatic Eclipse Collections usage. This particular kata is set up as a series of unit tests that fail. Your task is to make them pass, using Eclipse Collections. -
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Laravel Chunk Upload
The basic implementation for chunk upload with multiple providers
Laravel Chunk Upload simplifies chunked uploads with support for multiple JavaScript libraries atop Laravel's file upload system, designed with a minimal memory footprint. Features include cross-domain request support, automatic cleaning, and intuitive usage. -
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waifu2x ncnn Vulkan
waifu2x converter ncnn version, run fast GPU with vulkan
ncnn implementation of waifu2x converter. Runs fast on Intel/AMD/Nvidia/Apple-Silicon with Vulkan API. waifu2x-ncnn-vulkan uses ncnn project as the universal neural network inference framework. -
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MNN
MNN is a blazing fast, lightweight deep learning framework
...Android platform, core so size is about 400KB, OpenCL so is about 400KB, Vulkan so is about 400KB. Supports hybrid computing on multiple devices. Currently supports CPU and GPU. -
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Sming
Open source framework simplifying the creation of C++ applications
Sming is an asynchronous embedded C/C++ framework with superb performance and multiple network features. Sming is open source, modular and supports multiple architectures including ESP8266 and ESP32. Superb performance and memory usage (Sming compiles to native firmware!) Fast and user-friendly development. Integrated host emulator to assist with developing, testing, and debugging libraries and applications on a PC before uploading them to an actual microcontroller. Built-in powerful wireless modules. Compatible with standard Libraries use popular hardware in a few lines of code. ... -
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SDWebImageSwiftUI
SwiftUI Image loading and Animation framework powered by SDWebImage
SDWebImageSwiftUI is a SwiftUI image-loading framework, which is based on SDWebImage. It brings all your favorite features from SDWebImage, like async image loading, memory/disk caching, animated image playback and performances. The framework provide the different View structs, which API match the SwiftUI framework guideline. If you're familiar with Image, you'll find it easy to use WebImage and AnimatedImage. Since SDWebImageSwiftUI is built on top of SDWebImage, it provide both the... -
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Symfony VarExporter
Allows exporting any serializable PHP data structure to plain PHP code
Symfony VarExporter is a component that provides fast and safe serialization of PHP objects, especially those involving closures, services, or references. Unlike traditional serialize() or var_export(), VarExporter produces PHP code that can be re-evaluated safely and efficiently, which is useful in caching, dependency injection, and configuration scenarios. -
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Phalcon
High performance, full-stack PHP framework delivered as a C extension
Its innovative architecture makes Phalcon the fastest PHP framework ever built! Developers do not need to know C to use Phalcon. Its functionality is exposed as PHP classes and interfaces under the Phalcon namespace, ready to be used. Zephir/C extensions are loaded together with PHP one time on the web server's daemon start process. Classes and functions provided by the extension are ready to use for any application. The code is compiled and isn't interpreted because it's already compiled to... -
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fgprof
fgprof is a sampling Go profiler that allows you to analyze On-CPU
fgprof is a sampling Go profiler that allows you to analyze On-CPU as well as Off-CPU (e.g. I/O) time together. Go's builtin sampling CPU profiler can only show On-CPU time, but it's better than fgprof at that. Go also includes tracing profilers that can analyze I/O, but they can't be combined with the CPU profiler. fgprof is designed for analyzing applications with mixed I/O and CPU workloads. This kind of profiling is also known as wall-clock profiling. If this is the first time you hear... -
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EnTT
A fast and reliable entity component system (ECS) and much more
...A constexpr utility for human readable resource names. An incredibly fast entity-component system based on sparse sets, with its own pay for what you use policy to adjust performance and memory usage according to the users' requirements. Offers a minimal configuration system built using the monostate pattern. -
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Play Framework
A high velocity web framework
...By being RESTful by default, including assets compilers, JSON & WebSocket support, Play is a perfect fit for modern web & mobile applications. Play is based on a lightweight, stateless, web-friendly architecture. Built on Akka, Play provides predictable and minimal resource consumption (CPU, memory, threads) for highly-scalable applications. Make your changes and simply hit refresh! All you need is a browser and a text editor. Underneath the covers Play uses a fully asynchronous model built on top of Akka. -
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MegEngine
Easy-to-use deep learning framework with 3 key features
...After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. 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. ... -
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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, you can scale indefinitely by using the kubectl scale deployment command to add more SCC-worker and SCC-broker instances as needed. ... -
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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... -
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Valence
A Rust framework for building Minecraft servers
Rust framework for building Minecraft: Java Edition servers. Built on top of Bevy ECS, Valence is an effort to create a Minecraft-compatible server completely from scratch in Rust. You can think of Valence as a game engine for Minecraft servers. It doesn't do much by default, but by writing game logic yourself and leveraging Bevy's powerful plugin system, you can make almost anything. Opinionated features like dynamic scripting, dedicated executables, and vanilla game mechanics are all... -
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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,... -
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MACE
Deep learning inference framework optimized for mobile platforms
Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes... -
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SHAD0W
A post exploitation framework designed to operate covertly
...By using Donut along with the process injection capabilities of SHAD0W, it provides the operator the ability to execute .NET assemblies, DLLs, EXEs, JS, VBS or XSLs fully inside the memory. Dynamically resolved syscalls are heavily used to avoid userland API hooking, anti-DLL injection to make it harder for EDR to load code into the beacons, and official Microsoft mitigation methods to protect spawn processes. Runs fully inside of Docker allowing cross-platform usage. SHAD0W is a modular C2 framework designed to successfully operate on mature environments. ...
