Search Results for "cpu memory usage"
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Showing 760 open source projects for "cpu memory usage"
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tmux-mem-cpu-load
CPU, RAM, and load monitor for use with tmux
tmux-mem-cpu-load is a lightweight system monitoring utility designed for the tmux status line. It gives terminal users a compact way to view memory usage, CPU usage, and system load without opening a separate monitoring program. The tool is especially useful for developers, server administrators, and power users who spend long sessions inside tmux. -
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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. -
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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. -
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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). ... -
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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. -
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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. -
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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. -
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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... -
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mactop
Apple Silicon Monitor Top
mactop is a terminal-based monitoring tool designed specifically for Apple Silicon Macs. It displays real-time system metrics such as CPU usage, GPU usage, ANE activity, memory usage, power consumption, temperatures, fan speeds, disk I/O, and network activity. The tool uses native Apple APIs including SMC, IOReport, IOKit, IOHIDEventSystemClient, and Mach Kernel APIs to collect detailed hardware data without requiring sudo for core monitoring. mactop supports Apple Silicon models from M1 through M5, including Pro, Max, and Ultra variants, as well as newer core types like M5 S-Cores. ... -
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ProcDump for Mac
Release repository for ProcDump-for-Mac
...The project is built from the ProcDump for Linux code base and adapts the diagnostic workflow for macOS systems. It can capture dumps immediately or after a process meets conditions such as high CPU usage, low CPU usage, memory thresholds, thread count thresholds, or file descriptor thresholds. It also supports repeated captures, timed intervals, process-name waiting, polling frequency control, and extended logging. ProcDump for Mac is useful for developers who need lightweight process diagnostics without relying only on interactive debugging sessions. -
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jetson-stats
Simple package for monitoring and control your NVIDIA Jetson
...It supports Jetson platforms such as Orin, Xavier, Nano, TX, and newer Jetson families. The project includes jtop, a terminal-based dashboard that gives users a live view of CPU, GPU, memory, power, temperature, engine usage, and system status. It can also be imported into Python scripts, which makes it useful for custom monitoring, robotics dashboards, automation, and diagnostics. Developers working with embedded AI systems can use it to understand performance limits and troubleshoot hardware behavior during deployment. ... -
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beszel
Lightweight server monitoring hub with historical data, docker stats
A lightweight server resource monitoring hub with historical data, docker stats, and alerts. -
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TencentDB Agent Memory
TencentDB Agent Memory delivers fully local long-term memory for AI
...The design keeps high-level memory inspectable while preserving a drill-down path back to raw evidence. It is built for OpenClaw and Hermes-style agent workflows that need lower token usage, better continuity, and no external API dependency. -
14
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. -
15
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). ... -
16
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. ... -
17
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. -
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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). -
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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. ... -
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dtop
Terminal dashboard for Docker monitoring across multiple hosts
dtop is an open-source, terminal-based dashboard for monitoring Docker containers across local and remote hosts. Built with Rust, it provides a lightweight interface for viewing container activity and resource consumption directly from the command line. Users can monitor CPU usage, memory utilization, container status, and other operational metrics in real time. The application supports simultaneous connections to multiple Docker hosts through local sockets, SSH, TCP, and TLS. It integrates with Dozzle to provide convenient access to container logs and related monitoring interfaces. Configuration files allow users to define hosts, apply container filters, and customize monitoring preferences. ... -
21
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.... -
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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. -
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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. ... -
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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. ... -
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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. ...
