gpuvis: A Visualizer for GPU Traces

Developed by mikesart, gpuvis is a specialized tool designed to visualize GPU traces. The project is hosted on GitHub and serves as a powerful utility for analyzing graphics hardware performance.

(Note: Image link represents the screenshot mentioned in the repository)

---

🛠 Project Architecture & Files

The repository is organized into several key directories and configuration files to manage the build process and source code.

Directory Structure

File Inventory

The following files are present in the root directory:

• Build Scripts: CMakeLists.txt, Makefile, meson.build, meson_options.txt.
• Configuration: .clang-format, .editorconfig, .gitattributes, .gitignore.
• Documentation & Legal: README.md, LICENSE.
• Linux Integration: com.github.gpuvis.Gpuvis.desktop, com.github.gpuvis.Gpuvis.metainfo.xml, com.github.gpuvis.Gpuvis.svg.
• Other: patches, qtcreator.

---

⚖️ Licensing and Credits

The core gpuvis code is released under the MIT License.

MIT License Agreement

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.

Third-Party Dependencies

The project integrates various libraries and fonts, each with its own licensing terms:

---

📜 History and Context

The inception of this library was made possible through the support of Media Molecule. Its primary early application was for internal use during the development of the video game Tearaway.

Technical Nuance

When analyzing GPU traces, the tool helps calculate metrics such as throughput. For example, a simplified representation of GPU efficiency might be expressed as:

$\text{Efficiency} = \frac{\text{Actual Throughput}}{\text{Theoretical Peak Performance}} \times 100\%$

---

🚀 Development & Status

The project has evolved its build system over time, moving from basic Makefiles to more robust systems like cmake and meson.

Setup Checklist

• Clone repository
• Install dependencies (SDL, etc.)
• Run cmake or meson build
• Load a trace from the traces/ folder

Repository Statistics

• Stars: $\approx 1,000$
• Forks: $109$
• Watchers: $33$

Example Build Command

To initialize the project using CMake, one might use:

mkdir build && cd build
cmake ..
make -j$(nproc)

For further details, please refer to the GPUVis Documentation.