Leseprobe
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Parallel and High Performance Programming with Python
Fabio Nelli
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Naturwissenschaften, Medizin, Informatik, Technik / Informatik, EDV
Beschreibung
This book will teach you everything about the powerful techniques and applications of parallel computing, from the basics of parallel programming to the cutting-edge innovations shaping the future of computing.
The book starts with an introduction to parallel programming and the different types of parallelism, including parallel programming with threads and processes. The book then delves into asynchronous programming, distributed Python, and GPU programming with Python, providing you with the tools you need to optimize your programs for distributed and high-performance computing.
The book also covers a wide range of applications for parallel computing, including data science, artificial intelligence, and other complex scientific simulations. You will learn about the challenges and opportunities presented by parallel computing for these applications and how to overcome them.
By the end of the book, you will have insights into the future of parallel computing, the latest research and developments in the field, and explore the exciting possibilities that lie ahead.
Table of Contents
1. Introduction to Parallel Programming
2. Building Multithreaded Programs
3. Working with Multiprocessing and mpi4py Library
4. Asynchronous Programming with AsyncIO
5. Realizing Parallelism with Distributed Systems
6. Maximizing Performance with GPU Programming using CUDA
7. Embracing the Parallel Computing Revolution
8. Scaling Your Data Science Applications with Dask
9. Exploring the Potential of AI with Parallel Computing
10. Hands-on Applications of Parallel Computing
Kundenbewertungen
Optimization, Python, Dask, Pandas, Machine learning, Multiprocessing, Parallel Data Science with Dask, SCOOP, Parallel programming, Data analysis, GPU programming with Numba(CUDA) e PyOpenGL, Dramatiq, Distributed computing, GPU programming, Deep Learning with PyTorch, High-performance computing, Performance, Scientific computing, Multithreading, Python threads, TensorFlow, Parallel algorithms, Asyncio, Best practice, Distribute Computing with Celery, NumPy