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Build fast and efficient Android apps that run as reliably as clockwork in a multi-device world About This Book Wide coverage of various topics that help in developing optimal applications Explore the concepts of Advanced Native Coding in depth A must-have for professional-standard Android developers for whom performance failures and the sloppy use of resources are simply unacceptable Who This Book Is For This book is aimed at developers with an advanced knowledge of Android and who want to test their skills and learn new techniques to increase the performance of their applications. We assume they are comfortable working with the entire Android SDK, and have been doing it for a few years. They need to be familiar with frameworks such as NDK to use native code, which is crucial for app performance What You Will Learn Create Android applications that squeeze the most from the limited resource capacity of devices Swap code that isn't performing Efficient memory management by identifying problems such as leaks Reap the benefits of multithreaded and asynchronous programming Maximize the security and encryption mechanisms natively provided by Android Perform efficient network operations and techniques to retrieve data from servers Master the NDK to write native code that can perform faster operations In Detail Performant applications are one of the key drivers of success in the mobile world. Users may abandon an app if it runs slowly. Learning how to build applications that balance speed and performance with functionality and UX can be a challenge; however, it's now more important than ever to get that balance right. Android High Performance will start you thinking about how to wring the most from any hardware your app is installed on, so you can increase your reach and engagement. The book begins by providing an introduction to state–of-the-art Android techniques and the importance of performance in an Android application. Then, we will explain the Android SDK tools regularly used to debug and profile Android applications. We will also learn about some advanced topics such as building layouts, multithreading, networking, and security. Battery life is one of the biggest bottlenecks in applications; and this book will show typical examples of code that exhausts battery life, how to prevent this, and how to measure battery consumption from an application in every kind of situation to ensure your apps don't drain more than they should. This book explains techniques for building optimized and efficient systems that do not drain the battery, cause memory leaks, or slow down with time. Style and approach The book follows a tutorial-based approach to take the reader from the basic fundamentals of debugging to advanced performance-improvement concepts.
Unique and clever ideas are important when building a hot-selling Android app, but the real drivers for success are speed, efficiency, and power management. With this practical guide, you’ll learn the major performance issues confronting Android app developers, and the tools you need to diagnose problems early. Customers are finally realizing that apps have a major role in the performance of their Android devices. Author Doug Sillars not only shows you how to use Android-specific testing tools from companies including Google, Qualcomm, and AT&T, but also helps you explore potential remedies. You’ll discover ways to build apps that run well on all 19,000 Android device types in use. Understand how performance issues affect app sales and retention Build an Android device lab to maximize UI, functional, and performance testing Improve the way your app interacts with device hardware Optimize your UI for fast rendering, scrolling, and animations Track down memory leaks and CPU issues that affect performance Upgrade communications with the server, and learn how your app performs on slower networks Apply Real User Monitoring (RUM) to ensure that every device is delivering the optimal user experience
Today's Android apps developers are often running into the need to refine, improve and optimize their apps performances. As more complex apps can be created, it is even more important for developers to deal with this critical issue. Android allows developers to write apps using Java, C or a combination of both with the Android SDK and the Android NDK. Pro Android Apps Performance Optimization reveals how to fine-tune your Android apps, making them more stable and faster. In this book, you'll learn the following: How to optimize your Java code with the SDK, but also how to write and optimize native code using advanced features of the Android NDK such as using ARM single instruction multiple data (SIMD) instructions (in C or assembly) How to use multithreading in your application, how make best use of memory and how to maximize battery life How to use to some OpenGL optimizations and to Renderscript, a new feature in Android 3.0 (Honeycomb) and expanded in Android 4.0 (Ice Cream Sandwich). After reading and using this book, you'll be a better coder and your apps will be better-coded. Better-performing apps mean better reviews and eventually, more money for you as the app developer or your indie shop. What you’ll learn How to optimize your applications in Java How to optimize your applications using the NDK How to best use memory to maximize performance How to maximize battery life How and when to use multi-threading How to benchmark and profile your code How to optimize OpenGL code and use Renderscript Who this book is for Android developers already familiar with Java and Android SDK, who want to go one step further and learn how to maximize performance. Table of Contents Optimizing Java code Getting started with the Android NDK Using advanced NDK features Using memory efficiently Multithreading and synchronization Benchmarking and profiling your application Maximizing battery life OpenGL optimizations Renderscript
In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs
This book will help you understand what "programming for performance" means, and use effective coding patterns and techniques to optimize your .NET applications. You will begin by understanding what "high performance coding" means, and the different performance concerns. You will see how CLR works and get an understanding of concepts such as memory management, garbage collection, and thread life cycles. You will proceed to learn about the theoretical and practical concepts of PLINQ programming. You will also see what Big Data is, and how to architect a Big Data solution to manipulate large datasets. Finally, you will learn how to launch and analyze a profile session and execute tests against a code block or application for performance analysis. By the end of this book, you will have a complete understanding of efficient programming using high-performance techniques, and will able to write highly optimized applications.
Leverage Scala and the functional paradigm to build performant software About This Book Get the first book to explore Scala performance techniques in depth! Real-world inspired use cases illustrate and support the techniques studied and the language features This book is written by Vincent Theron and Michael Diamant, software engineers with several years of experience in the high-frequency trading and programmatic advertising industries Who This Book Is For This book assumes a basic exposure to the Scala programming language and the Java Virtual Machine. You should be able to read and understand moderately advanced Scala code. No other knowledge is required. What You Will Learn Analyze the performance of JVM applications by developing JMH benchmarks and profiling with Flight Recorder Discover use cases and performance tradeoffs of Scala language features, and eager and lazy collections Explore event sourcing to improve performance while working with stream processing pipelines Dive into asynchronous programming to extract performance on multicore systems using Scala Future and Scalaz Task Design distributed systems with conflict-free replicated data types (CRDTs) to take advantage of eventual consistency without synchronization Understand the impact of queues on system performance and apply the Free monad to build systems robust to high levels of throughput In Detail Scala is a statically and strongly typed language that blends functional and object-oriented paradigms. It has experienced growing popularity as an appealing and pragmatic choice to write production-ready software in the functional paradigm. Scala and the functional programming paradigm enable you to solve problems with less code and lower maintenance costs than the alternatives. However, these gains can come at the cost of performance if you are not careful. Scala High Performance Programming arms you with the knowledge you need to create performant Scala applications. Starting with the basics of understanding how to define performance, we explore Scala's language features and functional programming techniques while keeping a close eye on performance throughout all the topics. We introduce you as the newest software engineer at a fictitious financial trading company, named MV Trading. As you learn new techniques and approaches to reduce latency and improve throughput, you'll apply them to MV Trading's business problems. By the end of the book, you will be well prepared to write production-ready, performant Scala software using the functional paradigm to solve real-world problems. Style and approach This step-by-step guide will help you create high performance applications using Scala. Packed with lots of code samples, tips and tricks, every topic is explained in a detailed, easy-to-understand manner.
High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high performance computing (HPC) applications. Omitting tedious details, the book discusses hardware architecture concepts and programming techniques that are the most pertinent to application developers for achieving high performance. Even though the text concentrates on C and Fortran, the techniques described can be applied to other languages, such as C++ and Java. Drawing on their experience with chips from AMD and systems, interconnects, and software from Cray Inc., the authors explore the problems that create bottlenecks in attaining good performance. They cover techniques that pertain to each of the three levels of parallelism: Message passing between the nodes Shared memory parallelism on the nodes or the multiple instruction, multiple data (MIMD) units on the accelerator Vectorization on the inner level After discussing architectural and software challenges, the book outlines a strategy for porting and optimizing an existing application to a large massively parallel processor (MPP) system. With a look toward the future, it also introduces the use of general purpose graphics processing units (GPGPUs) for carrying out HPC computations. A companion website at contains all the examples from the book, along with updated timing results on the latest released processors.

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