Open-Awesome
CategoriesAlternativesStacksSelf-HostedExplore
Open-Awesome

© 2026 Open-Awesome. Curated for the developer elite.

TermsPrivacyAboutGitHubRSS
  1. Home
  2. C/C++
  3. Remotery

Remotery

Apache-2.0Cv1.2.1

A realtime CPU/GPU profiler hosted in a single C file with a remote web viewer for performance analysis.

GitHubGitHub
3.3k stars284 forks0 contributors

What is Remotery?

Remotery is a real-time CPU and GPU profiler designed for performance analysis in applications like games and high-performance software. It provides lightweight instrumentation across multiple threads and graphics APIs, with a remote web-based viewer for live and historical performance inspection. The profiler is implemented as a single C file for easy integration and supports a wide range of platforms and GPU APIs.

Target Audience

Game developers, graphics programmers, and engineers working on performance-critical applications across Windows, Linux, macOS, iOS, Android, and consoles. It's particularly useful for those needing real-time profiling of both CPU and GPU activity.

Value Proposition

Developers choose Remotery for its simplicity (single C file), cross-platform support, and powerful real-time web viewer. It offers unique features like GPU UI rendering for high-performance updates, automatic thread sampling, and support for multiple graphics APIs without requiring complex setup or administrative privileges.

Overview

Single C file, Realtime CPU/GPU Profiler with Remote Web Viewer

Use Cases

Best For

  • Profiling real-time CPU and GPU performance in game engines
  • Analyzing multi-threaded application performance across processor cores
  • Debugging graphics API performance (Direct3D, OpenGL, Vulkan, Metal, CUDA)
  • Integrating lightweight profiling into C/C++ projects with minimal overhead
  • Remote performance monitoring via a web browser on any device
  • Comparing historical profiling traces to track performance regressions

Not Ideal For

  • Projects requiring deep IDE integration for seamless debugging within tools like Visual Studio or Xcode
  • Environments with strict security policies that prohibit web-based viewers or network access
  • Applications where profiling overhead must be absolutely minimal, as Remotery adds instrumentation despite being lightweight
  • Teams needing advanced statistical analysis, automated regression testing, or flame graphs out of the box

Pros & Cons

Pros

Single-File Integration

Remotery is hosted in a single C file (lib/Remotery.c), making it trivial to add to any C/C++ project by just including the file and header, as emphasized in the Compiling section.

Cross-Platform Profiling

It supports a wide range of platforms including Windows, Linux, macOS, iOS, Android, and consoles, plus GPU APIs like D3D, OpenGL, Vulkan, Metal, and CUDA, enabling consistent profiling across diverse environments.

High-Performance Web Viewer

The viewer uses GPU rendering for the UI, bypassing the DOM to achieve 60hz updates, which allows real-time monitoring without lag, as stated in the Features list.

Automatic Thread Sampling

Identifies processor core usage for threads without requiring Administrator privileges, simplifying multi-threaded analysis on systems like Windows and Linux.

Cons

Complex GPU API Setup

Binding to GPU APIs like Vulkan requires specific extensions (e.g., hostQueryReset, timelineSemaphore) and careful function pointer passing, adding setup overhead and potential for errors.

Limited Metal Granularity

For Metal, profiling is restricted to command buffer timing only, with no finer-grained samples, which may not provide detailed insights for GPU-intensive tasks.

Manual Build Configuration

On some platforms like MINGW-64, manual linking of libraries (libws2_32.a and libwinmm.a) is required, and macro definitions (e.g., RMT_USE_*) must be set correctly, increasing integration complexity.

Frequently Asked Questions

Quick Stats

Stars3,307
Forks284
Contributors0
Open Issues35
Last commit1 year ago
CreatedSince 2014

Tags

#c-library#vulkan#cuda#direct3d#opengl#metal#profiler#cpu#d3d11#c#d3d12#game-development#cross-platform#performance-profiling#cpu-profiler#real-time-analysis#gpu

Built With

W
WebGL
J
JavaScript
C
C++

Included in

C/C++70.6k
Auto-fetched 4 hours ago

Related Projects

googletestgoogletest

GoogleTest - Google Testing and Mocking Framework

Stars38,852
Forks10,833
Last commit12 hours ago
Google MockGoogle Mock

GoogleTest - Google Testing and Mocking Framework

Stars38,852
Forks10,833
Last commit12 hours ago
Catch2Catch2

A modern, C++-native, test framework for unit-tests, TDD and BDD - using C++14, C++17 and later (C++11 support is in v2.x branch, and C++03 on the Catch1.x branch)

Stars21,302
Forks3,355
Last commit14 hours ago
benchmarkbenchmark

A microbenchmark support library

Stars10,297
Forks1,783
Last commit5 hours ago
Community-curated · Updated weekly · 100% open source

Found a gem we're missing?

Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.

Submit a projectStar on GitHub