Python Parallel and Concurrent Programming Part 2

Write more effective programs that execute multiple instructions simultaneously. Learn advanced techniques for parallel and concurrent programming in Python.

Introduction

• Learn parallel programming basics
• What you should know
• Exercise files

1. Synchronization

• Condition variable
• Condition variable: Python demo
• Producer-consumer
• Producer-consumer threads: Python demo
• Producer-consumer processes: Python demo
• Semaphore
• Semaphore: Python demo

2. Barriers

• Race condition
• Race condition: Python demo
• Barrier
• Barrier: Python demo

3. Asynchronous Tasks

• Computational graph
• Thread pool
• Thread pool: Python demo
• Process pool: Python demo
• Future
• Future: Python demo
• Divide and conquer
• Divide and conquer: Python demo

4. Evaluating Parallel Performance

• Speedup, latency, and throughput
• Amdahl's law
• Measure speedup
• Measure speedup: Python demo

5. Designing Parallel Programs

• Partitioning
• Communication
• Agglomeration
• Mapping

6. Challenge Problems

• Welcome to the challenges
• Challenge: Matrix multiply in Python
• Solution: Matrix multiply in Python
• Challenge: Merge sort in Python
• Solution: Merge sort in Python
• Challenge: Download images in Python
• Solution: Download images in Python

Conclusion

• Additional resources
• Next steps