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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
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
| Erscheinungsjahr: | 2026 |
|---|---|
| Fachbereich: | Programmiersprachen |
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| ISBN-13: | 9789349887145 |
| ISBN-10: | 9349887142 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Autor: | Nelli, Fabio |
| Hersteller: | Orange Education Pvt Ltd |
| Verantwortliche Person für die EU: | Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de |
| Maße: | 280 x 216 x 25 mm |
| Von/Mit: | Fabio Nelli |
| Erscheinungsdatum: | 06.02.2026 |
| Gewicht: | 1,177 kg |
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