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Unleash the Full Power of Python to Run Faster Code, Scale Smarter, and Compute Without Limits.
Book Description Python is the backbone for data science, AI, and cloud computing, and the demand for speed and scalability has never been higher. That's why mastering parallel and high-performance programming is essential to transform Python into a tool that meets modern performance demands.
Building on the success of the first edition, Parallel and High Performance Programming with Python (2nd Edition) expands and modernizes the original work, adding new frameworks, deployment patterns, and acceleration techniques for next-generation computing.
What you will learn - Design and optimize high-performance Python applications using parallelism, concurrency, and async patterns. - Profile, diagnose, and eliminate CPU, I/O, and memory bottlenecks for real-world workloads.
Table of Contents 1. Introduction to Parallel Programming 2. Parallel Programming with Threads 3. Parallel Programming with Processes 4. Asynchronous Programming 5. Distributed Python 6. GPU Programming with Python 7. Parallel Computing Applications 8. Parallel Computing for Data Science 9. Parallel Computing for Artificial Intelligence 10. Future of Parallel Programming 11. Modern Frameworks for Parallelism and Distribution: Ray and Modin 12. PySpark 13. Joblib 14. Parallelization on Cloud and Serverless Systems 15. Parallel Programming with FPGAs 16. Introduction to Quantum Computing and Quantum Architectures Index
