Write NEON intrinsics using GitHub Copilot to improve Adler32 performance
Introduction
About NEON and Adler32
Create a C Version of Adler32
Create a test program
Create a Makefile
Build and run the test program
Create a NEON version of Adler32
Compare the NEON version to the standard C version of Adler32
Debug the NEON version to match the standard C version
Summarize the project with a README.md file
Other ideas for GitHub Copilot
Next Steps

  Log an issue

  Fork and edit

  Discuss on Discord

What else can I do with GitHub Copilot on this project?

GitHub Copilot can help you explore additional performance and optimization ideas:

  • Test different compiler flags using Agent mode to automate iteration and identify the best combinations.
  • Add Clang support to your Makefile and compare performance against GCC — performance can differ significantly depending on your code structure.
  • Generate a wider range of data sizes and random patterns to stress-test functionality and measure performance under varied conditions.
  • Explore alternative algorithm structures that rely on compiler autovectorization instead of NEON intrinsics — you might discover better performance simply by restructuring the C code.

AI tools won’t always generate high-performance code out of the box, but they can rapidly accelerate your experimentation and learning — especially in new areas of programming like NEON-based performance optimization.

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