Fabio Nelli eBooks

Parallel and High Performance Programming with Python (2nd Edition)Transform Your Python Code into a High-Performance Powerhouse Using Multithreading, CUDA, PyTorch, Spark, and Dask. E-book. Formato EPUB Fabio Nelli   -  Orange Education Pvt Ltd, 2026  - 

Unleash the Full Power of Python to Run Faster Code, Scale Smarter, and Compute Without Limits.Key Features? Get a free one-month digital subscription to www.avaskillshelf.com? Master end-to-end Python parallelism from multithreading and multiprocessing to distributed computing on GPUs, clusters, and the cloud.? Accelerate real-world workloads using cutting-edge frameworks like Ray, Dask, PyTorch, Spark, Modin, Joblib, and CUDA.? Deploy high-performance pipelines at scale with Kubernetes, serverless computing, FPGAs, and emerging quantum acceleration techniques.Book DescriptionPython 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.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.? Accelerate compute-intensive tasks using CUDA kernels, PyTorch tensors, NumPy vectorization, and GPU-enabled deep learning workflows.? Build and scale distributed systems seamlessly with Dask, Ray, Apache Spark, and Modin for massive data processing.? Deploy and orchestrate compute pipelines on Kubernetes, AWS Lambda, and Azure Functions for cost-efficient scalability.? Integrate advanced acceleration technologies like Joblib, FPGA workflows, and quantum simulation frameworks to stay ahead of the curve.Who is This Book For?This book is tailored for data scientists, machine learning engineers, Python developers, and backend programmers who need to boost performance and scalability in their applications. It also serves data and cloud engineers, DevOps/MLOps professionals, HPC specialists, and distributed systems developers building high-throughput pipelines. Technical architects, research engineers, and quantitative analysts will find advanced design patterns to optimize workloads across CPUs, GPUs, clusters, FPGAs, and serverless or quantum environments.Table of Contents1. Introduction to Parallel Programming2. Parallel Programming with Threads3. Parallel Programming with Processes4. Asynchronous Programming5. Distributed Python6. GPU Programming with Python7. Parallel Computing Applications8. Parallel Computing for Data Science9. Parallel Computing for Artificial Intelligence10. Future of Parallel Programming11. Modern Frameworks for Parallelism and Distribution: Ray and Modin12. PySpark13. Joblib14. Parallelization on Cloud and Serverless Systems15. Parallel Programming with FPGAs16. Introduction to Quantum Computing and Quantum Architectures       Index

Parallel and High Performance Programming with Python: Unlock Parallel and Concurrent Programming in Python using Multithreading, CUDA, Pytorch, and Dask. E-book. Formato EPUB Fabio Nelli   -  Orange Education Pvt Ltd, 2023  - 

Unleash the capabilities of Python and its libraries for solving high performance computational problems. Key Features ? Explores parallel programming concepts and techniques for high-performance computing. ? Covers parallel algorithms, multiprocessing, distributed computing, and GPU programming. ? Provides practical use of popular Python libraries/tools like NumPy, Pandas, Dask, and TensorFlow.Book DescriptionThis 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.What you will learn? Build faster, smarter, and more efficient applications for data analysis, machine learning, and scientific computing? Implement parallel algorithms in Python? Best practices for designing, implementing, and scaling parallel programs in PythonWho is this book for?This book is aimed at software developers who wish to take their careers to the next level by improving their skills and learning about concurrent and parallel programming. It is also intended for Python developers who aspire to write fast and efficient programs, and for students who wish to learn the fundamentals of parallel computing and its practical uses.Table of Contents1. Introduction to Parallel Programming 2. Building Multithreaded Programs 3. Working with Multiprocessing and mpi4py Library4. Asynchronous Programming with AsyncIO5. Realizing Parallelism with Distributed Systems 6. Maximizing Performance with GPU Programming using CUDA7. Embracing the Parallel Computing Revolution8. Scaling Your Data Science Applications with Dask9. Exploring the Potential of AI with Parallel Computing10. Hands-on Applications of Parallel Computing

Parallel and High Performance Programming with PythonUnlock parallel and concurrent programming in Python using multithreading, CUDA, Pytorch and Dask. (English Edition). E-book. Formato EPUB Fabio Nelli   -  Orange Education Pvt Ltd, 2023  - 

Unleash the capabilities of Python and its libraries for solving high performance computational problems.KEY FEATURES ? Explores parallel programming concepts and techniques for high-performance computing. ? Covers parallel algorithms, multiprocessing, distributed computing, and GPU programming. ? Provides practical use of popular Python libraries/tools like NumPy, Pandas, Dask, and TensorFlow.DESCRIPTIONThis 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.WHAT WILL YOU LEARN ? Build faster, smarter, and more efficient applications for data analysis, machine learning, and scientific computing? Implement parallel algorithms in Python? Best practices for designing, implementing, and scaling parallel programs in PythonWHO IS THIS BOOK FOR?This book is aimed at software developers who wish to take their careers to the next level by improving their skills and learning about concurrent and parallel programming. It is also intended for Python developers who aspire to write fast and efficient programs, and for students who wish to learn the fundamentals of parallel computing and its practical uses.TABLE OF CONTENTS 1. Introduction to Parallel Programming 2. Building Multithreaded Programs 3. Working with Multiprocessing and mpi4py Library4. Asynchronous Programming with AsyncIO5. Realizing Parallelism with Distributed Systems 6. Maximizing Performance with GPU Programming using CUDA7. Embracing the Parallel Computing Revolution8. Scaling Your Data Science Applications with Dask9. Exploring the Potential of AI with Parallel Computing10. Hands-on Applications of Parallel ComputingAUTHOR BIO Fabio Nelli holds a Master's Degree in Chemistry and a Bachelor's Degree in IT and Automation Engineering. He currently works at various research institutes and private companies, where he delivers educational courses on data analysis and data visualization technologies. He contributes to writing articles on the web and writes in-depth books on the subject.