Verleger: Packt Publishing
Julia High Performance. Design and develop high performing programs with Julia
Avik Sengupta
Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia.You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia’s design makes them fast. The last chapter will give you a taste of Julia’s distributed computing capabilities.
Avik Sengupta
Julia is a high-level, high-performance dynamic programming language for numerical computing. If you want to understand how to avoid bottlenecks and design your programs for the highest possible performance, then this book is for you. The book starts with how Julia uses type information to achieve its performance goals, and how to use multiple dispatches to help the compiler emit high-performance machine code. After that, you will learn how to analyze Julia programs and identify issues with time and memory consumption. We teach you how to use Julia's typing facilities accurately to write high-performance code and describe how the Julia compiler uses type information to create fast machine code. Moving ahead, you'll master design constraints and learn how to use the power of the GPU in your Julia code and compile Julia code directly to the GPU. Then, you'll learn how tasks and asynchronous IO help you create responsive programs and how to use shared memory multithreading in Julia. Toward the end, you will get a flavor of Julia's distributed computing capabilities and how to run Julia programs on a large distributed cluster.By the end of this book, you will have the ability to build large-scale, high-performance Julia applications, design systems with a focus on speed, and improve the performance of existing programs.
Julia: High Performance Programming. Build powerful and fast systems with Julia
Ivo Balbaert, M E Sherrington, Avik Sengupta
In this learning path, you will learn to use an interesting and dynamic programming language—Julia! You will get a chance to tackle your numerical and data problems with Julia. You’ll begin the journey by setting up a running Julia platform before exploring its various built-in types. We’ll then move on to the various functions and constructs in Julia. We’ll walk through the two important collection types—arrays and matrices in Julia.You will dive into how Julia uses type information to achieve its performance goals, and how to use multiple dispatch to help the compiler emit high performance machine code. You will see how Julia’s design makes code fast, and you’ll see its distributed computing capabilities.By the end of this learning path, you will see how data works using simple statistics and analytics, and you’ll discover its high and dynamic performance—its real strength, which makes it particularly useful in highly intensive computing tasks. This learning path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Getting Started with Julia by Ivo Balvaert? Julia High Performance by Avik Sengupta? Mastering Julia by Malcolm Sherrington
Adrian Salceanu
Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing.After six years in the making, Julia has reached version 1.0. Now is the perfect time to learn it, due to its large-scale adoption across a wide range of domains, including fintech, biotech, education, and AI.Beginning with an introduction to the language, Julia Programming Projects goes on to illustrate how to analyze the Iris dataset using DataFrames. You will explore functions and the type system, methods, and multiple dispatch while building a web scraper and a web app. Next, you'll delve into machine learning, where you'll build a books recommender system. You will also see how to apply unsupervised machine learning to perform clustering on the San Francisco business database. After metaprogramming, the final chapters will discuss dates and time, time series analysis, visualization, and forecasting.We'll close with package development, documenting, testing and benchmarking.By the end of the book, you will have gained the practical knowledge to build real-world applications in Julia.
Christopher Pecoraro , Vincenzo Gambino
Jamstack (JavaScript, API, and Markup) enables web developers to create and publish modern and maintainable websites and web apps focused on speed, security, and accessibility by using tools such as Gatsby, Sanity, and Netlify. Developers working with Jamstack will be able to put their knowledge to good use with this practical guide to static site generation and content management. This Jamstack book takes a hands-on approach to implementation and related methodologies that will have you up and running with modern web development in no time.Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, you'll begin by building an event and venue schema structure, and then expand the functionality, exploring all that the Jamstack has to offer. You’ll learn how an example Jamstack is built, build structured content using Sanity to create a schema, use GraphQL to expose the content, and employ Gatsby to build an event website using page and template components and Tailwind CSS Framework. Lastly, you’ll deploy the website to both, a Netlify server and the Microsoft Static Web Apps Service, and interact with it using Amazon Alexa.By the end of this book, you'll have gained the knowledge and skills you need to install, configure, build, extend, and deploy a simple events website using Jamstack.
Jay Asher
Logic Pro is Apple’s flagship application for music creation, found in many professional music studios across the globe. It is a powerful digital audio workstation that comes with all the software tools that you need to create music that sounds great. In the previous version, Logic Pro 10.5, Apple had added impressive features to what was already a full package of tools, loops, FX plug-ins, and software instruments.Providing a comprehensive introduction if you’re new to Mac computer music creation, this practical guide will show you how to use Logic Pro and have you up to speed in no time.You’ll not only understand what Apple’s Logic Pro software can do but also get hands-on with using it to accomplish various musical tasks. The book starts by getting you up and running with the basic terminologies. As you progress, you’ll explore how to create audio and MIDI musical parts. To build on your knowledge further, the book will guide you through developing an automated mix. In addition to this, you’ll learn how to bounce mixes and audio files for distribution.By the end of this book, you’ll be well-versed with Logic Pro and have the skills you need to create professional-quality music.
JUNOS Automation Cookbook. Automate network devices on Juniper's operating system
Adam Chappell
The JUNOS Automation Cookbook is a companion guide for the complex field of automating tasks on JUNOS devices. With a foundation in industry-standrd XML, JUNOS provides an ideal environment for programmatic interation, allowing you to build upon the capabilities provided by Juniper, with your own original code.You will begin by learning about, and setting up, the industry-standard NETCONF remote procedure call mechanisms on your device. After initial setup, you'll walk through SLAX - Juniper's foundation scripting language - for manipulating XML representations of JUNOSconcepts and elements. You'll learn how to write your own SLAX scripts to customise the operating environment, and also how to write proactive event handlers that deal with situations as they happen.You'll then delve into PyEZ - Juniper's bridging framework to make automation accessible to Python code - allowing you to build automation applications in the popular scripting language. You'll witness some examples of how to write applications that can monitor configuration changes, implement BGP security policies and implement ad-hoc routing protocols, for those really tricky situations. You'll also leaarn how asynchronous I/O frameworks like Node.js can be used to implement automation applications that present an acceptable web interface. Along with way, you'll explore how to make use of the latest RESTful APIs that JUNOS provides, how to visualize aspects of your JUNOS network, and how to integrate your automation capabilities with enterprise-wide orchestration systems like Ansible. By the end of the book, you'll be able to tackle JUNOS automation challenges with confidence and understanding, and without hassle.
Toomey, Nikhil Borkar, Nikhil Akki, Juan Tomás...
Jupyter has garnered a strong interest in the data science community of late, as it makes common data processing and analysis tasks much simpler. This book is for data science professionals who want to master various tasks related to Jupyter to create efficient, easy-to-share, scientific applications.The book starts with recipes on installing and running the Jupyter Notebook system on various platforms and configuring the various packages that can be used with it. You will then see how you can implement different programming languages and frameworks, such as Python, R, Julia, JavaScript, Scala, and Spark on your Jupyter Notebook. This book contains intuitive recipes on building interactive widgets to manipulate and visualize data in real time, sharing your code, creating a multi-user environment, and organizing your notebook. You will then get hands-on experience with Jupyter Labs, microservices, and deploying them on the web. By the end of this book, you will have taken your knowledge of Jupyter to the next level to perform all key tasks associated with it.