Parallel and High Performance Programming with Python (2nd Edition): Transform Your Code into a Powerhouse Using ... PyTorch, Spark, Dask (English Edition)

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. You’ll begin by mastering the core concepts of parallelism, threading, and multiprocessing, then move into asynchronous programming for responsive and efficient workloads. The book guides you through distributed Python across clusters, followed by deep dives into GPU acceleration using CUDA and PyTorch. You’ll explore real-world applications in data science and artificial intelligence, and learn how to scale pipelines seamlessly with Ray, Modin, and Spark. Advanced chapters introduce Joblib optimization, Kubernetes, and serverless scaling for cloud-native workloads, and cutting-edge topics such as FPGA acceleration and quantum computing, giving you a future-ready performance toolkit. Packed with hands-on examples, benchmarks, and deployment-ready best practices, this second edition helps you turn everyday Python into a high-performance, production-grade system.