95 repositorios
Tools focused on quantifying execution time, memory allocation, and hardware utilization rather than step-by-step code inspection.
Explore 95 awesome GitHub repositories matching development tools & productivity · Performance and Resource Profilers. Refine with filters or upvote what's useful.
This project is a cross-platform mobile framework that enables the development of native iOS and Android applications from a single codebase. It utilizes a declarative component-based model where developers define user interfaces using a syntax extension that maps directly to underlying platform-native view primitives. By decoupling application logic from the host platform's main thread, the framework maintains a consistent native view hierarchy while ensuring that JavaScript execution remains independent of UI rendering. The framework distinguishes itself through a robust bridge architecture
Displays real-time performance metrics, including frame rates and resource utilization, directly within the application during development.
PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic differentiation system that allows for flexible, non-static graph execution. The framework is designed for deep integration with Python, enabling natural usage alongside standard scientific computing ecosystems. It distinguishes itself through a comprehensive distributed training sui
Tracks operator execution time and memory usage to pinpoint performance bottlenecks across various hardware backends.
Syncthing es un motor de sincronización de archivos descentralizado que mantiene estados de datos consistentes en múltiples dispositivos a través de redes mesh peer-to-peer. Funciona como un demonio en segundo plano que replica automáticamente las creaciones, modificaciones y eliminaciones de archivos entre nodos de confianza sin necesidad de servidores centrales. Al utilizar indexación de bloques direccionable por contenido y sincronización delta a nivel de bloque, el sistema identifica y transfiere solo los segmentos modificados de los archivos, asegurando una propagación de datos eficiente en entornos heterogéneos. El proyecto se distingue por una arquitectura centrada en la seguridad que se basa en la autenticación TLS mutua para verificar la identidad del dispositivo, asegurando que todas las conexiones estén vinculadas criptográficamente a huellas digitales de certificados de confianza. Admite modos de sincronización flexibles, incluyendo replicación bidireccional, duplicación unidireccional para copias de seguridad y cumplimiento basado en referencias. Para mayor privacidad, el sistema proporciona cifrado a nivel de carpeta para dispositivos no confiables y permite un control granular del tráfico de red, incluida la capacidad de restringir operaciones a redes locales o utilizar infraestructura de retransmisión para el cruce de NAT. Más allá de sus capacidades principales de replicación, la plataforma ofrece herramientas de gestión integrales, incluido un panel basado en web para monitorear el estado de la conexión y el rendimiento, así como una interfaz de línea de comandos para una configuración avanzada. Incluye estrategias de versionado robustas para proteger contra la pérdida de datos y admite escenarios de despliegue complejos a través de la integración de servicios nativos y métricas de observabilidad. El software está diseñado para la compatibilidad multiplataforma y puede instalarse a través de gestores de paquetes estándar o entornos contenedorizados.
Generates performance profiles by recording CPU usage data via debug endpoints for bottleneck analysis.
Vite is a frontend build toolchain that provides a unified development and production pipeline for modern web applications. It functions as a modular, environment-agnostic build engine that leverages native ES modules to serve source code directly to the browser, eliminating the need for expensive bundling during the development phase. By maintaining an environment-aware module graph, it supports concurrent development across client, server, and custom runtime environments. The project distinguishes itself through a high-performance development server that utilizes a hot module replacement pr
Profiles transformation hooks to identify performance bottlenecks during file loading and server startup.
Arthas is a Java diagnostic tool and runtime debugger designed for real-time troubleshooting of applications. It functions as a remote diagnostics agent that allows users to inspect the runtime state of a Java process, including its heap objects and classloader hierarchies, without requiring a process restart. The project distinguishes itself through advanced bytecode manipulation capabilities, enabling live class hotswapping and the modification of bytecode in running processes. It supports in-memory source compilation and runtime bytecode decompilation to verify and update logic instantly w
Analyzes CPU usage and thread states to identify resource-heavy processes and performance bottlenecks.
JavaFamily is a curated set of learning paths and reference guides for backend engineering, distributed systems, and virtual machine internals. It provides a structured curriculum covering the Java language, operating system concepts, and network protocols. The project features detailed study guides for the Java virtual machine architecture, including memory management and garbage collection. It also includes a comprehensive reference for distributed systems, covering microservices, remote procedure call frameworks, and scalable system design. The collection covers a broad range of technical
Offers methods for locating threads and processes that consume excessive CPU resources.
Immer is an immutable state management library used to create new versions of data structures. It allows the production of new state by mutating a temporary draft instead of using manual object spreading. The project implements structural sharing to reuse unchanged parts of a data tree between versions, which reduces memory consumption. It also functions as a JSON patch generator to calculate and output the differences between two state versions. To ensure data integrity, the library includes a state mutation protector that freezes data structures to detect and prevent accidental modificatio
Provides tools to map execution bottlenecks back to original functions by processing CPU profile files.
This project is a machine learning array framework and tensor computation library designed for high-performance numerical computing. It provides a comprehensive suite of tools for constructing and training neural networks, featuring an automatic differentiation engine that facilitates gradient-based optimization and complex mathematical modeling. The library distinguishes itself through a unified memory architecture that allows data to be shared across CPU and GPU devices without explicit copies, significantly reducing data movement overhead. Its execution model relies on a lazy evaluation en
Calculates the total byte count of arrays to monitor resource consumption and identify potential memory bottlenecks during heavy computational tasks.
Iris is a high-performance web framework and API toolkit for the Go programming language. It provides the infrastructure necessary to build HTTP/2 web applications, REST APIs, and MVC-based websites. The project distinguishes itself through a flexible architectural model that supports multiple isolated application instances within a single process and allows for binary-embedded asset loading to eliminate external filesystem dependencies. It features dynamic router hot-reloading and a pluggable view engine for rendering dynamic HTML content. The framework covers a broad range of capabilities,
Includes a dedicated interface for profiling CPU usage, memory, and goroutines to identify bottlenecks.
BCC is an eBPF development toolkit and tracing framework used for monitoring and analyzing the Linux kernel. It functions as a performance analysis tool and debugging utility to capture system events, measure kernel latency, and provide network observability. The project distinguishes itself by providing a build system that integrates with LLVM to compile C-like code into BPF bytecode at runtime. It utilizes BPF Type Format data for relocations to maintain cross-kernel compatibility and extracts kernel headers to ensure the generated programs match the specific kernel version. The toolkit co
Samples stack traces at timed intervals to identify active code paths and performance bottlenecks.
FlameGraph is a performance profiling and visualization toolkit designed to identify bottlenecks in software execution. It functions as a processing engine that transforms raw stack trace samples into interactive, hierarchical diagrams. By representing aggregated execution frequency as nested rectangles, the tool allows developers to visualize hot code paths and analyze system behavior across both kernel and user-space environments. The project distinguishes itself through its ability to perform differential profile analysis, which highlights performance regressions or improvements by compari
Samples active code paths and stack traces at specific frequencies to identify which functions consume the most processor time.
This project is a secure container runtime that provides strong isolation for application workloads by implementing a userspace kernel. By intercepting system calls and executing them within a memory-safe, restricted environment, it minimizes the attack surface exposed to the host kernel. It functions as a drop-in engine for standard container orchestration platforms, ensuring compatibility with industry-standard runtime specifications while maintaining a hardened execution boundary. The runtime distinguishes itself through its ability to virtualize core system resources, including an indepen
Restricts exposed CPU features to a predefined list to ensure compatibility when migrating container snapshots.
This project is a comprehensive educational resource and programming course covering C++ language semantics and features from C++03 through C++26. It provides structured tutorials and technical guides focused on modern C++ development. The material offers specialized instruction on template metaprogramming, including the use of type traits and compile-time computations. It features detailed guides on concurrency and parallelism for multi-core execution, as well as a reference for software design applying SOLID principles and RAII. Additionally, it covers build performance optimization to redu
Guides users through CPU profiling to identify performance bottlenecks and analyze cache behavior.
py-spy is a sampling profiler and process debugger for Python. It allows for the analysis of running processes to identify performance bottlenecks and diagnose hanging programs without requiring code changes or restarts. The tool operates by reading the memory of a running process from the outside, which enables non-invasive sampling and state collection without pausing execution. It can resolve binary symbols to capture performance data from native extensions written in compiled languages and generate visual flame graphs for both native extensions and subprocesses. The project provides capa
Identifies slow functions and execution bottlenecks in running Python programs without modifying source code.
Memray is a memory profiler for Python that tracks heap allocations in both Python code and native C or C++ extensions. It captures memory events by hooking into the language runtime and traversing call stacks, providing a comprehensive view of how an application consumes memory. The tool is designed to minimize performance impact on the target application by using thread-local buffering and streaming data to an external process or file. The project distinguishes itself through its ability to monitor complex, multi-threaded systems and child processes in real-time. It provides diagnostic util
Analyzes and optimizes heap allocation patterns in Python applications to identify memory leaks.
Proton GE Custom is a compatibility layer designed to execute Windows games on Linux by translating binary instructions and API calls. It focuses on improving game stability and performance through a Wine-based translation system. The project utilizes custom patches and per-game configuration overrides to resolve specific application crashes and glitches. It implements specialized media foundation patching to ensure stable playback of proprietary cinematic formats and adds support for High Dynamic Range output. The software covers a range of gaming optimizations, including raw input latency
Uses per-game launch parameters and environment variables to resolve application-specific crashes.
gh-ost is a triggerless online schema migration tool for MySQL. It functions as a replication client and table management utility that synchronizes data from a source table to a shadow table using binary logs, allowing for table structure modifications without locking original tables or causing downtime. The tool distinguishes itself by using binary-log-based replication instead of triggers to stream row-based events to a shadow table. It implements load-aware throttling and dynamic performance tuning to adjust migration speed based on server load and replication lag. Users can monitor and ad
Captures CPU and block profiles during execution to identify performance bottlenecks and analyze runtime behavior.
Scalene is a high-performance diagnostic utility designed to measure resource consumption during the execution of Python applications. It functions as a line-level monitor, providing granular insights that pinpoint the specific source code responsible for performance overhead. The tool distinguishes itself through statistical profiling that captures stack traces and resource usage without requiring manual instrumentation of the source code. It tracks CPU, GPU, and memory consumption by intercepting library-level calls and hardware driver commands, allowing for the analysis of both managed and
Tracks CPU, GPU, and memory usage at the line level to identify bottlenecks in Python code.
node-inspector is a web-based debugger for Node.js applications that integrates the Blink developer tools interface. It functions as a runtime profiler and inspection suite, providing a remote debugging interface to connect a local browser to a Node.js process. The project enables live code iteration, allowing source code to be modified while the process is running and persisting those changes back to the physical file system. It also includes a JavaScript runtime profiler to monitor CPU and heap usage for identifying bottlenecks and memory leaks. The tool covers execution flow control throu
Analyzes CPU and heap usage patterns to identify performance bottlenecks and memory leaks within the running process.
Opentui is a terminal user interface framework for building interactive command line applications. It provides a component-based system featuring a flexbox layout engine, a virtual node component tree, and a low-level 2D cell array renderer. The project is distinguished by a sophisticated keyboard binding engine that maps complex multi-stroke sequences and chords to named commands using prioritized, reactive layers. It also implements a plugin architecture that allows external modules to inject custom UI components into designated layout slots and extend input logic at runtime. Its capabilit
Displays real-time statistics including FPS and memory usage via an in-app performance overlay.