Distributed Computing With Python

Distributed Computing with Python PDF
Author: Francesco Pierfederici
Publisher: Packt Publishing Ltd
ISBN: 1785887041
Size: 13.13 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 170
View: 7455

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Book Description:

Distributed Computing With Python

by Francesco Pierfederici, Distributed Computing With Python Book available in PDF, EPUB, Mobi Format. Download Distributed Computing With Python books, Harness the power of multiple computers using Python through this fast-paced informative guide About This Book You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant Make use of Amazon Web Services along with Python to establish a powerful remote computation system Train Python to handle data-intensive and resource hungry applications Who This Book Is For This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks. What You Will Learn Get an introduction to parallel and distributed computing See synchronous and asynchronous programming Explore parallelism in Python Distributed application with Celery Python in the Cloud Python on an HPC cluster Test and debug distributed applications In Detail CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. Style and Approach This example based, step-by-step guide will show you how to make the best of your hardware configuration using Python for distributing applications.







Concurrent And Distributed Computing With Python

Concurrent and Distributed Computing with Python PDF
Author: Harish Garg
Publisher:
ISBN:
Size: 80.87 MB
Format: PDF, Kindle
Category :
Languages : en
Pages :
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Book Description:

Concurrent And Distributed Computing With Python

by Harish Garg, Concurrent And Distributed Computing With Python Book available in PDF, EPUB, Mobi Format. Download Concurrent And Distributed Computing With Python books, "Facing difficulty in implementing concurrent and multithreaded programs in your Python applications? Is this preventing you from implementing efficient code in your apps and benefiting from multiprocessing? This course will help you resolve these difficulties. You will start by exploring the basic concepts of concurrency and distributed computing, and you'll learn which Python libraries are relevant to these. You will not only learn to see Celery as a way to build-in concurrency into your apps, but also Pyro as an alternative to Celery. You will create processes and manage processes along with interprocess communication; combine coroutines with threads and processes; practice the management of process pools; implement asynchronous tasks/job queues using AsyncResult and Celery backends; invoke remote methods in your Python-based code, and use these skills and concepts when working with AWS for Python."--Resource description page.







Python Parallel Programming Cookbook

Python Parallel Programming Cookbook PDF
Author: Giancarlo Zaccone
Publisher: Packt Publishing Ltd
ISBN: 1789530067
Size: 65.76 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 370
View: 1198

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Book Description:

Python Parallel Programming Cookbook

by Giancarlo Zaccone, Python Parallel Programming Cookbook Book available in PDF, EPUB, Mobi Format. Download Python Parallel Programming Cookbook books, Implement effective programming techniques in Python to build scalable software that saves time and memory Key Features Design distributed computing systems and massive computational tasks coherently Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs Understand how to host your parallelized applications on the cloud Book Description Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. By the end of this book, you will be confident in building concurrent and high-performing applications in Python. What you will learn Synchronize multiple threads and processes to manage parallel tasks Use message passing techniques to establish communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational task Write efficient programs by adopting the event-driven programming model Explore cloud technology with Django and Google App Engine Apply parallel programming techniques that can lead to performance improvements Who this book is for The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of parallel computing.







Python Parallel Programming Cookbook Second Edition

Python Parallel Programming Cookbook   Second Edition PDF
Author: Giancarlo Zaccone
Publisher:
ISBN:
Size: 28.12 MB
Format: PDF, ePub, Mobi
Category :
Languages : en
Pages : 370
View: 5412

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Book Description:

Python Parallel Programming Cookbook Second Edition

by Giancarlo Zaccone, Python Parallel Programming Cookbook Second Edition Book available in PDF, EPUB, Mobi Format. Download Python Parallel Programming Cookbook Second Edition books, Implement effective programming techniques in Python to build scalable software that saves time and memory Key Features Design distributed computing systems and massive computational tasks coherently Learn practical recipes with concise explanations that address development pain points encountered while coding parallel programs Understand how to host your parallelized applications on the cloud Book Description Nowadays, it has become extremely important for programmers to understand the link between the software and the parallel nature of their hardware so that their programs run efficiently on computer architectures. Applications based on parallel programming are fast, robust, and easily scalable. This updated edition features cutting-edge techniques for building effective concurrent applications in Python 3.7. The book introduces parallel programming architectures and covers the fundamental recipes for thread-based and process-based parallelism. You'll learn about mutex, semaphores, locks, queues exploiting the threading, and multiprocessing modules, all of which are basic tools to build parallel applications. Recipes on MPI programming will help you to synchronize processes using the fundamental message passing techniques with mpi4py. Furthermore, you'll get to grips with asynchronous programming and how to use the power of the GPU with PyCUDA and PyOpenCL frameworks. Finally, you'll explore how to design distributed computing systems with Celery and architect Python apps on the cloud using PythonAnywhere, Docker, and serverless applications. By the end of this book, you will be confident in building concurrent and high-performing applications in Python. What you will learn Synchronize multiple threads and processes to manage parallel tasks Use message passing techniques to establish communication between processes to build parallel applications Program your own GPU cards to address complex problems Manage computing entities to execute distributed computational task Write efficient programs by adopting the event-driven programming model Explore cloud technology with Django and Google App Engine Apply parallel programming techniques that can lead to performance improvements Who this book is for The Python Parallel Programming Cookbook is for software developers who are well-versed with Python and want to use parallel programming techniques to write powerful and efficient code. This book will help you master the basics and the advanced of par...







Verteilte Systeme

Verteilte Systeme PDF
Author: Andrew S. Tanenbaum
Publisher:
ISBN: 9783827372932
Size: 57.35 MB
Format: PDF, ePub, Docs
Category : Distributed processing
Languages : de
Pages : 761
View: 5737

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Book Description:

Verteilte Systeme

by Andrew S. Tanenbaum, Verteilte Systeme Book available in PDF, EPUB, Mobi Format. Download Verteilte Systeme books,







Hands On Gpu Computing With Python

Hands On GPU Computing with Python PDF
Author: Avimanyu Bandyopadhyay
Publisher: Packt Publishing Ltd
ISBN: 1789342406
Size: 65.35 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 452
View: 3377

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Book Description:

Hands On Gpu Computing With Python

by Avimanyu Bandyopadhyay, Hands On Gpu Computing With Python Book available in PDF, EPUB, Mobi Format. Download Hands On Gpu Computing With Python books, Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key Features Understand effective synchronization strategies for faster processing using GPUs Write parallel processing scripts with PyCuda and PyOpenCL Learn to use the CUDA libraries like CuDNN for deep learning on GPUs Book Description GPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you’ll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly. What you will learn Utilize Python libraries and frameworks for GPU acceleration Set up a GPU-enabled programmable machine learning environment on your system with Anaconda Deploy your machine learning system on cloud containers with illustrated examples Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm. Perform data mining tasks with machine learning models on GPUs Extend your knowledge of GPU computing in scientific applications Who this book is for Data Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.







Einf Hrung In Machine Learning Mit Python

Einf  hrung in Machine Learning mit Python PDF
Author: Andreas C. Müller
Publisher: O'Reilly
ISBN: 3960101120
Size: 71.87 MB
Format: PDF
Category : Computers
Languages : de
Pages : 378
View: 2365

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Book Description:

Einf Hrung In Machine Learning Mit Python

by Andreas C. Müller, Einf Hrung In Machine Learning Mit Python Book available in PDF, EPUB, Mobi Format. Download Einf Hrung In Machine Learning Mit Python books, Machine Learning ist zu einem wichtigen Bestandteil vieler kommerzieller Anwendungen und Forschungsprojekte geworden, von der medizinischen Diagnostik bis hin zur Suche nach Freunden in sozialen Netzwerken. Um Machine-Learning-Anwendungen zu entwickeln, braucht es keine großen Expertenteams: Wenn Sie Python-Grundkenntnisse mitbringen, zeigt Ihnen dieses Praxisbuch, wie Sie Ihre eigenen Machine-Learning-Lösungen erstellen. Mit Python und der scikit-learn-Bibliothek erarbeiten Sie sich alle Schritte, die für eine erfolgreiche Machine-Learning-Anwendung notwendig sind. Die Autoren Andreas Müller und Sarah Guido konzentrieren sich bei der Verwendung von Machine-Learning-Algorithmen auf die praktischen Aspekte statt auf die Mathematik dahinter. Wenn Sie zusätzlich mit den Bibliotheken NumPy und matplotlib vertraut sind, hilft Ihnen dies, noch mehr aus diesem Tutorial herauszuholen. Das Buch zeigt Ihnen: - grundlegende Konzepte und Anwendungen von Machine Learning - Vor- und Nachteile weit verbreiteter maschineller Lernalgorithmen - wie sich die von Machine Learning verarbeiteten Daten repräsentieren lassen und auf welche Aspekte der Daten Sie sich konzentrieren sollten - fortgeschrittene Methoden zur Auswertung von Modellen und zum Optimieren von Parametern - das Konzept von Pipelines, mit denen Modelle verkettet und Arbeitsabläufe gekapselt werden - Arbeitsmethoden für Textdaten, insbesondere textspezifische Verarbeitungstechniken - Möglichkeiten zur Verbesserung Ihrer Fähigkeiten in den Bereichen Machine Learning und Data Science Dieses Buch ist eine fantastische, super praktische Informationsquelle für jeden, der mit Machine Learning in Python starten möchte – ich wünschte nur, es hätte schon existiert, als ich mit scikit-learn anfing! Hanna Wallach, Senior Researcher, Microsoft Research







Einf Hrung In Python

Einf  hrung in Python PDF
Author: Mark Lutz
Publisher: O'Reilly Germany
ISBN: 3897214881
Size: 52.16 MB
Format: PDF, ePub, Docs
Category : Python (Computer program language)
Languages : de
Pages : 624
View: 7031

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Book Description:

Einf Hrung In Python

by Mark Lutz, Einf Hrung In Python Book available in PDF, EPUB, Mobi Format. Download Einf Hrung In Python books,







Topics In Parallel And Distributed Computing

Topics in Parallel and Distributed Computing PDF
Author: Sushil K Prasad
Publisher: Morgan Kaufmann
ISBN: 0128039388
Size: 38.15 MB
Format: PDF, Mobi
Category : Computers
Languages : en
Pages : 360
View: 470

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Book Description:

Topics In Parallel And Distributed Computing

by Sushil K Prasad, Topics In Parallel And Distributed Computing Book available in PDF, EPUB, Mobi Format. Download Topics In Parallel And Distributed Computing books, Topics in Parallel and Distributed Computing provides resources and guidance for those learning PDC as well as those teaching students new to the discipline. The pervasiveness of computing devices containing multicore CPUs and GPUs, including home and office PCs, laptops, and mobile devices, is making even common users dependent on parallel processing. Certainly, it is no longer sufficient for even basic programmers to acquire only the traditional sequential programming skills. The preceding trends point to the need for imparting a broad-based skill set in PDC technology. However, the rapid changes in computing hardware platforms and devices, languages, supporting programming environments, and research advances, poses a challenge both for newcomers and seasoned computer scientists. This edited collection has been developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts into courses throughout computer science curricula. Contributed and developed by the leading minds in parallel computing research and instruction Provides resources and guidance for those learning PDC as well as those teaching students new to the discipline Succinctly addresses a range of parallel and distributed computing topics Pedagogically designed to ensure understanding by experienced engineers and newcomers Developed over the past several years in conjunction with the IEEE technical committee on parallel processing (TCPP), which held several workshops and discussions on learning parallel computing and integrating parallel concepts







Learn Quantum Computing With Python And Ibm Quantum Experience

Learn Quantum Computing with Python and IBM Quantum Experience PDF
Author: Robert Loredo
Publisher: Packt Publishing Ltd
ISBN: 1838986758
Size: 35.92 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 510
View: 3270

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Book Description:

Learn Quantum Computing With Python And Ibm Quantum Experience

by Robert Loredo, Learn Quantum Computing With Python And Ibm Quantum Experience Book available in PDF, EPUB, Mobi Format. Download Learn Quantum Computing With Python And Ibm Quantum Experience books, This book provides you with a step-by-step introduction to quantum computing using the IBM Quantum Experience platform. You will learn how to build quantum programs on your own, discover early use cases in your business, and help to get you or your company equipped with quantum computing skills.