Programming Massively Parallel Processors - Complete Solutions

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Overview

This repository contains comprehensive solutions to all exercises in Programming Massively Parallel Processors by David Kirk and Wen-mei Hwu (4th Edition). Each chapter includes:

• Detailed exercise solutions with step-by-step explanations
• Working code implementations in both CUDA C and Python
• Performance benchmarks comparing different approaches
• Visual diagrams for complex algorithms

Chapter Organization

Each chapter follows this structure:

├── code/
│   ├── *.cu          # CUDA implementations
│   ├── *.py          # Python alternatives  
│   ├── Makefile      # Build configuration
│   └── ...
└── README.md         # Theory + Exercises + Solutions

Available Chapters

Quick Start

Prerequisites

• NVIDIA GPU with CUDA support
• CUDA Toolkit installed
• Python 3.11+ (optional, for Python examples)

Setup

# Clone the repository
git clone <repository-url>
cd pmpp

# For Python examples (optional)
conda create -n pmpp python=3.11
conda activate pmpp
pip install -r requirements.txt

Running Examples

CUDA/C Examples:

cd chapter-XX/code
make
./program_name

Python Examples:

cd chapter-XX/code
python script_name.py

Contributing

Found an error? Please open an issue using this template:

Describe the bug

Describe where the problem is and what precisely is wrong.

Proposed solution

Here paste your proposed solution. Please include the reasoning behind why you believe your solution is correct.

Contribution Guidelines

• Maintain the existing explanation style with clear reasoning
• Include working code for any new implementations
• Add performance data where relevant
• Follow the existing code formatting standards

License

This project is licensed under the MIT License - see the LICENSE file for details.