gautam1858

gautam1858 / tiny-gpu-compiler

Public

An MLIR-based compiler that takes GPU kernels and compiles them to real hardware instructions. Interactive web visualizer included.

gautam1858.github.iotiny-gpu-compiler
61
8
100% credibility
Found Feb 25, 2026 at 26 stars 2x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

An interactive educational tool that compiles simple GPU kernels written in a C-like language into binary instructions and simulates their execution on a tiny GPU hardware model, all viewable step-by-step in a web browser.

How It Works

1
🔍 Discover the tool

You find this fun learning project online that shows how computer code turns into GPU instructions, like peeking inside a magic box.

2
🌐 Try the online playground

Click the live demo link in your web browser to instantly play without installing anything—no setup needed.

3
✏️ Write or pick a simple program

Choose a ready example like adding numbers in parallel, or type your own short code in the friendly editor.

4
⚡ Watch it transform step by step

Hit compile and see your code magically break down into colorful stages, from words to numbers the GPU understands.

5
▶️ Run it on the mini GPU

Press play to watch threads race through the instructions, updating memory right before your eyes.

6
🔧 Dig deeper locally if you want

Download and run on your computer for bigger experiments or your own data.

🎉 Master GPU magic

You now see exactly how everyday parallel code becomes lightning-fast hardware actions—aha moment achieved!

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Star Growth

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AI-Generated Review

What is tiny-gpu-compiler?

This MLIR-based compiler takes simple GPU kernels written in a C-like DSL and compiles them to real 16-bit hardware instructions for the tiny-gpu Verilog core. Developers get a full pipeline from source code through MLIR IR, register allocation, and binary emission, with outputs like annotated assembly, hex, or raw binaries via CLI or Docker. An interactive web visualizer in TypeScript lets you step through stages and simulate execution cycle-by-cycle in the browser.

Why is it gaining traction?

It fills the gap between high-level GPU code and silicon by visualizing the entire MLIR-based compiler flow for system-level design and hardware acceleration, something missing from tiny-gpu or tinygrad projects. The live demo hooks users instantly—no install needed to see kernels lower to instructions and run on a cycle-accurate simulator. Outputs integrate directly with tiny-gpu testbenches, making it practical for quick prototyping.

Who should use this?

Compiler nerds exploring MLIR-based compilers, hardware hackers targeting custom GPU accelerators, or educators demoing GPU compilation pipelines. Ideal for tiny-gpu users wanting to author kernels without hand-assembling ISA, or students dissecting how vec_add becomes machine code.

Verdict

Early project at 11 stars and 1.0% credibility—docs shine but lacks broad tests or ecosystem plugins. Spin up the demo if you're into compilers/hardware; skip for production unless you need a tiny MLIR GPU backend.

(187 words)

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