MLIR tutorials for Deep Learning optimization series

This repository contains a structured series covering MLIR, compiler optimizations, GPU execution, transformers, and deep learning superoptimization.

Note: The "ML" part of the MLIR name stands for "multi-level" (not machine learning!).

Table of Contents

• Part 1 - What and why MLIR?
• Part 2 - Memory in MLIR
• Part 3 - Affine Dialect and OpenMP
• Part 4 - Linear Algebra and Linalg
• Part 5 - Neural Networks and Tensors
• Part 6 - e-graphs and Term Rewriting
• Part 7 - NVIDIA GPU Execution
• Part 8 - Transformer Architecture
• Part 9 - Superoptimizing Deep Learning

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Installing MLIR

MLIR requires a few dependencies to be installed. Follow the steps below.

Step 1: Install Dependencies

Install the required build tools:

sudo apt-get update
sudo apt-get install -y cmake ninja-build ccache

Step 2: Clone the LLVM Repository

Clone the LLVM project repository, which contains MLIR:

git clone https://github.com/llvm/llvm-project.git

Step 3: Build MLIR from Source

Note: Building MLIR can take a significant amount of time depending on your system (This tutorial is done on Linux based OS).

Create a build directory and configure the project:

mkdir -p llvm-project/build
cd llvm-project/build

cmake -G Ninja ../llvm \
  -DLLVM_ENABLE_PROJECTS=mlir \
  -DLLVM_BUILD_EXAMPLES=ON \
  -DLLVM_TARGETS_TO_BUILD="Native;ARM;X86" \
  -DCMAKE_BUILD_TYPE=Release \
  -DLLVM_ENABLE_ASSERTIONS=ON \
  -DCMAKE_C_COMPILER=clang \
  -DCMAKE_CXX_COMPILER=clang++ \
  -DLLVM_CCACHE_BUILD=ON

Build and run MLIR tests:

cmake --build . --target check-mlir

Install MLIR:

cmake --build . --target install

Step 4: Verify the Installation

Check the installed MLIR version:

mlir-opt --version

If the installation was successful, the command will print the installed MLIR version information.