Refactor code structure for improved readability and maintainability

Author: NJX-njx

CMakeLists.txt

@@ -0,0 +1,14 @@
+cmake_minimum_required(VERSION 3.24)
+project(microgpt_cuda LANGUAGES CXX CUDA)
+
+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CUDA_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+set(CMAKE_CUDA_STANDARD_REQUIRED ON)
+
+if(NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
+  set(CMAKE_CUDA_ARCHITECTURES 86)
+endif()
+
+add_executable(microgpt_cuda microgpt_cuda.cu)
+target_compile_options(microgpt_cuda PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--use_fast_math>)

README.md

@@ -2,7 +2,7 @@
 
 ![microgpt logo](assets/microgpt.png)
 
-Optimized version of [Karpathy's microgpt](https://karpathy.ai/microgpt.html) — the most atomic way to train and inference a GPT in pure, dependency-free Python.
+Optimized version of [Karpathy's microgpt](https://karpathy.ai/microgpt.html), the most atomic way to train and inference a GPT in pure, dependency-free Python.
 
 **293 lines, 0 dependencies.** All optimizations preserve the original simplicity.
 
@@ -12,34 +12,50 @@ Optimized version of [Karpathy's microgpt](https://karpathy.ai/microgpt.html) 
 |---|---|---|
 | Direct `__truediv__` implementation | +8 | ~20-30% fewer computation graph nodes per step |
 | Fused `cross_entropy` (log-softmax + NLL) | +5 | Fewer nodes + better numerical stability |
-| Iterative `backward()` topological sort | ±0 | Eliminates recursion depth limit |
-| `sum(losses[1:], losses[0])` | ±0 | Removes phantom `Value(0)` node |
-| Adam β running product | +2 | Numerically stable bias correction at large step counts |
+| Iterative `backward()` topological sort | 0 | Eliminates recursion depth limit |
+| `sum(losses[1:], losses[0])` | 0 | Removes phantom `Value(0)` node |
+| Adam running product | +2 | Numerically stable bias correction at large step counts |
 | `with open()` file handle | +1 | Proper resource cleanup |
-| **Weight tying** (wte = lm_head) | -1 | Standard GPT-2 practice, 432 fewer params |
-| **Cosine LR schedule** | ±0 | Smoother decay than linear, matches Karpathy's latest |
+| **Weight tying** (wte = lm_head) | -1 | Standard GPT-2 practice, fewer params |
+| **Cosine LR schedule** | 0 | Smoother decay than linear |
 | **Train/val split** (90/10) | +3 | Basic ML hygiene, detect overfitting |
 | **Periodic validation** (every 100 steps) | +10 | Pure-float NLL eval on held-out docs |
 | **Gradient clipping** (global norm) | +4 | Prevents exploding gradients, stabilizes training |
-| **AdamW weight decay** | +1 | Decoupled regularization (Loshchilov & Hutter 2019) |
+| **AdamW weight decay** | +1 | Decoupled regularization |
 | **Top-k sampling** (k=5) | +4 | Higher quality inference, avoids garbage tokens |
 | **Per-step timing** | +3 | Performance observability in ms/step |
 
-**Total: +50 lines** (243 → 293), no new dependencies.
+**Total: +50 lines** (243 -> 293), no new dependencies.
 
 ## Files
 
-- **`microgpt.py`** — The complete optimized algorithm (runnable)
-- **`microgpt_optimized.html`** — Syntax-highlighted 3-column view with change annotations
+- **`microgpt.py`** - Complete optimized Python algorithm (runnable)
+- **`microgpt_cuda.cu`** - CUDA/C++ port with full train/val/inference loop
+- **`microgpt_optimized.html`** - Syntax-highlighted 3-column view with change annotations
+- **`CMakeLists.txt`** - CMake entrypoint for CUDA build
 
 ## Quick Start
 
 ```bash
 python microgpt.py
 ```
 
-It will auto-download `input.txt` (names dataset) on first run, train for 500 steps with periodic validation, then generate samples via top-k sampling.
+It auto-downloads `input.txt` on first run, trains for 500 steps with periodic validation, then generates samples via top-k sampling.
+
+## CUDA Build
+
+```bash
+cmake -S . -B build -G "Visual Studio 17 2022" -A x64
+cmake --build build --config Release
+.\build\Release\microgpt_cuda.exe
+```
+
+For quick smoke tests:
+
+```bash
+.\build\Release\microgpt_cuda.exe --steps 5 --samples 3
+```
 
 ## Credits
 
-Original by [@karpathy](https://github.com/karpathy) — [microgpt](https://karpathy.ai/microgpt.html) | [Gist](https://gist.github.com/karpathy/8627fe009c40f57531cb18360106ce95)
+Original by [@karpathy](https://github.com/karpathy) - [microgpt](https://karpathy.ai/microgpt.html) | [Gist](https://gist.github.com/karpathy/8627fe009c40f57531cb18360106ce95)