An embeddable, lightweight profiler for C++ applications with CPU/GPU timing, live web view, and dynamic instrumentation.
Microprofile is an embeddable, lightweight performance profiler for C++ applications. It provides detailed CPU and GPU timing data, live web-based visualization, and dynamic runtime instrumentation to help developers optimize code and identify performance bottlenecks. The tool is designed to be integrated directly into projects with minimal setup and overhead.
C++ developers, particularly in game development or graphics-intensive applications, who need real-time, low-overhead profiling for both CPU and GPU code across multiple APIs.
Developers choose Microprofile for its simplicity, embeddability, and comprehensive feature set—including GPU timing, dynamic instrumentation, and a live web UI—all in a few source files with minimal dependencies, making it ideal for integration into existing projects.
microprofile is an embeddable profiler
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The profiler consists of just a few source files with minimal dependencies, making it easy to embed into existing C++ projects without bloating the build system, as emphasized in the README's philosophy.
Includes a built-in web server (host:1338) for real-time visualization and control via a browser, allowing developers to monitor and capture performance data interactively without external tools.
On x86-64 platforms, enables injection of profiling markers at runtime without recompilation, useful for debugging optimized builds, though it's experimental and has limitations.
Supports timing for multiple graphics APIs including OpenGL, D3D11, D3D12, and Vulkan, catering to cross-platform game development, with examples provided in the README.
The README admits that relative placement of GPU timings vs CPU timings tends to slide, making precise correlation difficult for optimization and analysis.
Dynamic instrumentation is labeled as experimental, with risks like thread safety issues during code patching and limitations on instrumentable code sequences, requiring careful use.
Allocates 2MB per thread for profiling buffers by default, which can become significant in applications with many threads, impacting overall memory usage.