Release v4.0.0 (#2294)
This commit is contained in:
Kihiro Bando
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Your First Program with CuTe DSL\n",
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"\n",
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"## Introduction\n",
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"\n",
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"Welcome! In this tutorial, we'll write a simple \"Hello World\" program that runs on your GPU using CuTe DSL. This will help you understand the basics of GPU programming with our framework.\n",
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"\n",
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"### What You'll Learn\n",
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"\n",
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"- How to write code that runs on both CPU (host) and GPU (device),\n",
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"- How to launch a GPU kernel (a function that runs on the GPU),\n",
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"- Basic CUDA concepts like threads and thread blocks,\n",
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"\n",
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"### Step 1: Import Required Libraries\n",
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"\n",
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"First, let's import the libraries we need:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import cutlass \n",
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"import cutlass.cute as cute "
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"\n",
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"### Step 2: Write Our GPU Kernel\n",
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"A GPU kernel is a function that runs on the GPU. Here's a simple kernel that prints \"Hello World\".\n",
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"Key concepts:\n",
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"- `@cute.kernel`: This decorator tells CUTLASS that this function should run on the GPU\n",
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"- `cute.arch.thread_idx()`: Gets the ID of the current GPU thread (like a worker's ID number)\n",
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"- We only want one thread to print the message (thread 0) to avoid multiple prints"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"@cute.kernel\n",
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"def kernel():\n",
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" # Get the x component of the thread index (y and z components are unused)\n",
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" tidx, _, _ = cute.arch.thread_idx()\n",
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" # Only the first thread (thread 0) prints the message\n",
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" if tidx == 0:\n",
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" cute.printf(\"Hello world\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 3: Write Our Host Function\n",
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"\n",
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"Now we need a function that sets up the GPU and launches our kernel.\n",
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"Key concepts:\n",
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"- `@cute.jit`: This decorator is for functions that run on the CPU but can launch GPU code\n",
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"- We need to initialize CUDA before using the GPU\n",
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"- `.launch()` tells CUDA how many blocks, threads, shared memory, etc. to use"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"@cute.jit\n",
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"def hello_world():\n",
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"\n",
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" # Print hello world from host code\n",
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" cute.printf(\"hello world\")\n",
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" \n",
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" # Initialize CUDA context for launching a kernel with error checking\n",
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" # We make context initialization explicit to allow users to control the context creation \n",
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" # and avoid potential issues with multiple contexts\n",
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" cutlass.cuda.initialize_cuda_context()\n",
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"\n",
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" # Launch kernel\n",
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" kernel().launch(\n",
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" grid=(1, 1, 1), # Single thread block\n",
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" block=(32, 1, 1) # One warp (32 threads) per thread block\n",
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" )"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Step 4: Run Our Program\n",
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"\n",
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"There are 2 ways we can run our program:\n",
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"\n",
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"1. compile and run immediately\n",
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"2. separate compilation which allows us to compile the code once and run multiple times\n",
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" \n",
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"Please note the `Compiling...` for Method 2 prints before the \"Hello world\" of the first kernel. This shows the asynchronous behavior between CPU and GPU prints. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Running hello_world()...\n",
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"hello world\n",
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"Compiling...\n",
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"Hello world\n",
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"Running compiled version...\n",
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"hello world\n"
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]
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}
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],
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"source": [
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"# Method 1: Just-In-Time (JIT) compilation - compiles and runs the code immediately\n",
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"print(\"Running hello_world()...\")\n",
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"hello_world()\n",
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"\n",
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"# Method 2: Compile first (useful if you want to run the same code multiple times)\n",
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"print(\"Compiling...\")\n",
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"hello_world_compiled = cute.compile(hello_world)\n",
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"# Run the pre-compiled version\n",
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"print(\"Running compiled version...\")\n",
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"hello_world_compiled()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.5"
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},
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"widgets": {
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"application/vnd.jupyter.widget-state+json": {
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"state": {},
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"version_major": 2,
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"version_minor": 0
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}
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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