가속한 프로젝트 배포하기

The kernel is fast and correct. Now package it, prove the win, and hand off a project others can actually use. 🚀

Split the code into clear files. One module for the kernel, one for I/O, keeps the project readable as it grows.

Decide what users call and what stays internal. A small, clear API means people use your code without reading every line.

Bundle the modules into a single shareable file. A .mojopkg lets others import your accelerated code with one line.

The app can stay mostly Python and call your Mojo kernel through interop. You accelerate the hot path without rewriting everything.

Time the shipped pipeline end to end. This final benchmark is what you compare to the original Python baseline.

Divide the old time by the new time to get the speedup. A clean ratio tells the whole story in a single honest number.

Run the full app on real input and check the output against the reference. Final correctness matters as much as the speed gain.

State the input size, hardware, and method with the result. An honest report lets others trust and reproduce your numbers.

Write a short note on how to install, run, and benchmark it. Good docs turn a fast experiment into something people can adopt.

You profiled, ported the hot path, vectorized, parallelized, tuned, and shipped. That full workflow is how real Mojo acceleration happens.

Pick the right way to report your capstone result.

You packaged the kernel, ran a final benchmark, verified correctness, and reported an honest speedup. Your accelerated project is ready to ship. 🎯