Search Results for "cpu memory usage"
Sort By:
Showing 1127 open source projects for "cpu memory usage"
View related business solutions-
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
Application Monitoring That Won't Slow Your App DownFull APM with errors, performance, logs, and uptime monitoring. 99.999% uptime SLA on the platform itself.
-
1
TrafficMonitor
Floating window used to display current network speed, CPU & memory
TrafficMonitor is a network monitoring software with floating window feature for Windows. It displays the current internet speed and CPU and RAM usage. There are also other capabilities like an embedded display in the taskbar, changeable display skins, and historical traffic statistics. There are two versions of TrafficMonitor, the standard version and the Lite version. The standard version includes all the functions, while the Lite version does not include hardware monitoring functions such as temperature monitoring, GPU usage, and hard disk usage. ... -
2
FastSD CPU
Fast stable diffusion on CPU and AI PC
...The repository contains multiple interfaces including a desktop GUI for simple generation, an advanced web-based UI with support for extensions like LoRA and ControlNet, and a command-line interface for scripted usage or server deployments. With support for performance-oriented libraries such as OpenVINO and hardware acceleration on platforms like Intel AI PCs, FastSD CPU aims to shrink generation times dramatically compared with naive CPU implementations. -
3
CPU Features
A cross platform C99 library to get cpu features at runtime
...Implemented in portable C99, it is thread-safe, has no memory allocations, and raises no exceptions, making it suitable even for use in low-level system libraries. The design emphasizes portability, extensibility, and compatibility with sandboxed or restricted environments where direct CPU access may be limited. -
4
dockprom
Docker hosts and containers monitoring with Prometheus, Grafana, etc.
...You can change the credentials in the compose file or by supplying the ADMIN_USER and ADMIN_PASSWORD environment variables on compose up. Grafana is preconfigured with dashboards and Prometheus as the default data source. The Docker Host Dashboard shows key metrics for monitoring the resource usage of your server. Server uptime, CPU idle percent, number of CPU cores, available memory, swap and storage. System load average graph, running and blocked by IO processes graph, interrupts graph. CPU usage graph by mode (guest, idle, iowait, irq, nice, softirq, steal, system, user). Memory usage graph by distribution (used, free, buffers, cached). ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
OSHI
Native Operating System and Hardware Information
...It does not require the installation of any additional native libraries and aims to provide a cross-platform implementation to retrieve system information, such as OS version, processes, memory and CPU usage, disks and partitions, devices, sensors, etc. -
6
mactop
Apple Silicon Monitor Top written in pure Golang
mactop is a terminal-based monitoring tool "top" designed to display real-time metrics for Apple Silicon chips. It provides a simple and efficient way to monitor CPU and GPU usage, E-Cores and P-Cores, power consumption, and other system metrics directly from your terminal. -
7
Stats
macOS system monitor in your menu bar
Stats currently supported on macOS 10.13 (High Sierra) and higher. Stats is an application that allows you to monitor your macOS system. CPU utilization, GPU utilization, memory usage, disk utilization, sensors information (Temperature/Voltage/Power), battery level, network usage, fans speed, fan control, and Bluetooth devices. Supports many languages, such as English, Polski, Українська, Русский, and many more. You can help by adding a new language or improve existing translation. -
8
Zenith
Sort of like top or htop but with zoom-able charts, CPU, GPU
In terminal graphical metrics for your *nix system written in Rust. The make file provides for building fully static versions on Linux against the musl C library. It requires musl-gcc to be installed on the system. Install "musl-tools" package on debian/ubuntu derivatives, "musl-gcc" on fedora and equivalent on other distributions from their standard repos. If one needs to build with NVIDIA support in a virtual environment, then it requires some more setup since typically the VM software is... -
9
beszel
Lightweight server monitoring hub with historical data, docker stats
A lightweight server resource monitoring hub with historical data, docker stats, and alerts. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
10
CPU-Z
Utility for detailed CPU and system hardware information.
CPU-Z for Windows® x86/x64 is a freeware that gathers information on some of the main devices of your system : Processor name and number, codename, process, package, cache levels. Mainboard and chipset. Memory type, size, timings, and module specifications (SPD). Real time measurement of each core's internal frequency, memory frequency. -
11
auto-cpufreq
Automatic CPU speed & power optimizer for Linux
Automatic CPU speed & power optimizer for Linux. Actively monitors laptop battery state, CPU usage, CPU temperature, and system load, ultimately allowing you to improve battery life without making any compromises. -
12
CTranslate2
Fast inference engine for Transformer models
...The project implements a custom runtime that applies many performance optimization techniques such as weights quantization, layers fusion, batch reordering, etc., to accelerate and reduce the memory usage of Transformer models on CPU and GPU. The execution is significantly faster and requires less resources than general-purpose deep learning frameworks on supported models and tasks thanks to many advanced optimizations: layer fusion, padding removal, batch reordering, in-place operations, caching mechanism, etc. The model serialization and computation support weights with reduced precision: 16-bit floating points (FP16), 16-bit integers (INT16), and 8-bit integers (INT8). ... -
13
parca
Continuous profiling for analysis of CPU and memory usage
Continuous profiling for analysis of CPU, memory usage over time, and down-to-the-line number. Saving infrastructure costs, improving performance, and increasing reliability. A single profiler, using eBPF, automatically discovers targets from Kubernetes or systemd across the entire infrastructure with very low overhead. Supports C, C++, Rust, Go, and more. Both producing pprof formatted profiles with the eBPF-based profiler and ingesting any pprof formatted profiles allowing for wide language adoption and interoperability with existing tooling. ... -
14
Pingora
A library for building fast, reliable and evolvable network services
Pingora is a Rust-based high-performance HTTP proxy and networking framework developed by Cloudflare to eventually replace NGINX. Designed for extreme reliability and memory-safe concurrency, it handles over 40 million requests per second in production and reduces CPU/memory usage significantly compared to traditional web servers. -
15
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. ... -
16
Scalene
High-performance CPU, GPU, and memory profiler for Python
Scalene is a high-performance CPU, GPU and memory profiler for Python that does a number of things that other Python profilers do not and cannot do. It runs orders of magnitude faster than other profilers while delivering far more detailed information. Once Scalene has profiled your program, it will launch a web browser with an interactive user interface (all processing is done locally). -
17
NeoHtop
Blazing-fast system monitoring for your desktop
NeoHtop is a modern, high-performance system monitoring application that reimagines the classic htop experience using contemporary technologies such as Rust, Tauri, and Svelte. It provides real-time visibility into running processes, CPU load, and memory usage through a visually polished desktop interface designed for speed and clarity. Unlike traditional terminal monitors, neohtop emphasizes usability with advanced search capabilities, process pinning, and dynamic sorting, allowing users to quickly identify resource-intensive workloads. The application supports dark and light themes and auto-refreshes system statistics to maintain an always-current operational view. ... -
18
TaskExplorer
Powerful system task manager
...It includes advanced panels: a Thread Panel with stack traces (helpful for diagnosing deadlocks or hangs), a Memory Panel that lets you view or even edit process memory (with search capabilities), a Socket Panel showing open network connections, data rates, pseudo-UDP connections (via ETW), and a Modules Panel listing all loaded DLLs and memory-mapped files. -
19
whisper.cpp
Port of OpenAI's Whisper model in C/C++
whisper.cpp is a lightweight, C/C++ reimplementation of OpenAI’s Whisper automatic speech recognition (ASR) model—designed for efficient, standalone transcription without external dependencies. The entire high-level implementation of the model is contained in whisper.h and whisper.cpp. The rest of the code is part of the ggml machine learning library. The command downloads the base.en model converted to custom ggml format and runs the inference on all .wav samples in the folder samples.... -
20
PowerInfer
High-speed Large Language Model Serving for Local Deployment
PowerInfer is a high-performance inference engine designed to run large language models efficiently on personal computers equipped with consumer-grade GPUs. The project focuses on improving the performance of local AI inference by optimizing how neural network computations are distributed between CPU and GPU resources. Its architecture exploits the observation that only a subset of neurons in large models are frequently activated, allowing the system to preload frequently used neurons into GPU memory while processing less common activations on the CPU. This hybrid execution strategy significantly reduces memory bottlenecks and improves overall inference speed. ... -
21
MCP Monitor
A system monitoring tool that exposes system metrics
The MCP System Monitor is a tool that exposes system metrics via the Model Context Protocol (MCP), allowing Large Language Models (LLMs) to retrieve real-time system information through an MCP-compatible interface. -
22
AGI (Android GPU Inspector)
Android GPU Inspector
Android GPU Inspector (AGI) is a desktop tool for profiling, tracing, and debugging graphics workloads running on Android devices. It helps developers analyze Vulkan and OpenGL ES applications at the system, frame, and draw-call levels to uncover GPU and CPU bottlenecks. AGI captures detailed performance counters, timelines, and pipeline state to reveal stalls, overdraw, shader hotspots, and inefficient resource usage. Its frame debugger lets you step through commands, inspect render targets and textures, review shaders, and experiment with pipeline changes to validate optimizations. ... -
23
fluentbit
Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX
Fluent Bit is a super-fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments. A robust, lightweight, and portable architecture for high throughput with low CPU and memory usage from any data source to any destination. Proven across distributed cloud and container environments. Highly available with I/O handlers to store data for disaster recovery. Granular management of data parsing and routing. Filtering and enrichment to optimize security and minimize cost. The lightweight, asynchronous design optimizes resource usage: CPU, memory, disk I/O, network. ... -
24
dashdot
A simple, modern server dashboard
dashdot is a modern server dashboard primarily used by smaller private servers, offering real-time monitoring of system metrics through a sleek and customizable web interface. -
25
PicoClaw
Ultra-Efficient AI Assistant in Go
PicoClaw is an ultra-lightweight, open-source personal AI assistant written in Go, architected from the ground up to operate with extremely low memory usage (under 10 MB) and fast boot times, making it suitable for inexpensive hardware platforms and embedded devices. Inspired by earlier AI assistant projects like “nanobot,” it was refactored to emphasize resource efficiency while still supporting meaningful AI-driven interactions such as conversational workflows, planning tasks, and automation. ...
