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This book presents a hybrid static-dynamic approach for efficient performance analysis of parallel applications on HPC systems. Performance analysis is essential to finding performance bottlenecks and understanding the performance behaviors of parallel applications on HPC systems. However, current performance analysis techniques usually incur significant overhead. Our book introduces a series of approaches for lightweight performance analysis. We combine static and dynamic analysis to reduce the overhead of performance analysis. Based on this hybrid static-dynamic approach, we then propose several innovative techniques for various performance analysis scenarios, including communication analysis, memory analysis, noise analysis, computation analysis, and scalability analysis. Through these specific performance analysis techniques, we convey to readers the idea of using static analysis to support dynamic analysis. To gain the most from the book, readers should have a basic grasp of parallel computing, computer architecture, and compilation techniques.
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Unlock the power of multi-core mobile devices to build responsive and reactive Android applications About This Book Construct scalable and performant applications to take advantage of multi-thread asynchronous techniques Explore the high-level Android asynchronous constructs available on the Android SDK Choose the most appropriate asynchronous technique to implement your next outstanding feature Who This Book Is For This book is for Android developers who want to learn how to build multithreaded and reliable Android applications using high-level and advanced asynchronous techniques and concepts. No prior knowledge of concurrent and asynchronous programming is required. This book will also be great for Java experts who are new to Android. Whether you are a beginner at Android development or a seasoned Android programmer, this book will guide you through the most basic and advanced asynchronous constructs used in Android programming. What You Will Learn Get familiar with the android process model and low-level concurrent constructs delivered by the Android SDK Use AsyncTask and loader framework to load data in the background, delivering progress results in the meantime Create services that interact with your activity without compromising the UI rendering Learn the working of Android concurrency on the Native Layer Interact with nearby devices over Bluetooth and WiFi communications channels Create and compose tasks with RxJava to execute complex asynchronous work in a predictable way Get accustomed to the use of the Android Loader construct to deliver up-to-date results In Detail Asynchronous programming has acquired immense importance in Android programming, especially when we want to make use of the number of independent processing units (cores) available on the most recent Android devices. With this guide in your hands you'll be able to bring the power of Asynchronous programming to your own projects, and make your Android apps more powerful than ever before! To start with, we will discuss the details of the Android Process model and the Java Low Level Concurrent Framework, delivered by Android SDK. We will also guide you through the high-level Android-specific constructs available on the SDK: Handler, AsyncTask, and Loader. Next, we will discuss the creation of IntentServices, Bound Services and External Services, which can run in the background even when the user is not interacting with it. You will also discover AlarmManager and JobSchedule...
Parallel programs (Computer programs) --- Application software. --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software --- Parallel computer programs --- Parallel processing (Electronic computers) --- Computer programs --- Android (Electronic resource) --- Android operating system (Electronic resource) --- Android OS (Electronic resource) --- Google Android (Electronic resource) --- Android mobile operating system (Electronic resource)
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This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs and constraints of the available options. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algorithms and deep dives into several applications make the book equally useful for researchers, students and practitioners.
Machine learning --- Data mining --- Parallel algorithms --- Parallel programs (Computer programs) --- Apprentissage automatique --- Exploration de données (Informatique) --- Algorithmes parallèles --- Programmes parallèles (Logiciels) --- Exploration de données (Informatique) --- Algorithmes parallèles --- Programmes parallèles (Logiciels) --- Machine Learning --- Machine learning. --- Data mining. --- Parallel algorithms. --- Parallel computer programs --- Parallel processing (Electronic computers) --- Computer programs --- Algorithms --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Learning, Machine --- Artificial intelligence --- Machine theory
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A distributed system is driven by separate components that are executed in parallel, and protocols for such systems form a major aspect of system design in today’s world of wireless and mobile networking. Process algebras are languages for the description of elementary parallel systems and are used to study the behavioural properties of distributed systems, but they often lack the ability to handle data. This textbook guides students through algebraic specification and verification of distributed systems, and some of the most prominent formal verification techniques. The author employs µCRL as the vehicle, a language developed to combine process algebra and abstract data types. Chapters 2 and 3 explain the basics of abstract data types and process algebra, and guide the reader through the syntax and semantics of µCRL; Chap. 4 examines abstraction from internal behaviour; Chap. 5 covers specifications of standard protocols; Chap. 6 shows how to transform protocol specifications into labelled transition systems; Chap. 7 explains algorithms on labelled transition systems; and Chap. 8 presents symbolic verification techniques; finally, the Appendix gives a brief overview of the µCRL toolset. The book evolved from introductory courses on protocol verification taught to undergraduate and graduate students of computer science, and the text is supported throughout with examples and exercises; full solutions are provided in an appendix, while exercise sheets, lab exercises, example specifications and lecturer slides will be available on the author's website. Researchers in the field can use the book as a broad overview of the state of the art in algebraic specification and verification of distributed systems on the basis of a modern verification tool.
Electronic data processing --- Parallel processing (Electronic computers) --- Parallel programs (Computer programs) --- Distributed processing. --- Verification. --- Parallel program verification --- Verification of parallel programs --- High performance computing --- Multiprocessors --- Parallel programming (Computer science) --- Supercomputers --- Distributed computer systems in electronic data processing --- Distributed computing --- Distributed processing in electronic data processing --- Computer networks --- Computer network architectures. --- Computer science. --- Logic design. --- Algebra --- Software engineering. --- Information theory. --- Computer System Implementation. --- Mathematical Logic and Formal Languages. --- Logics and Meanings of Programs. --- Symbolic and Algebraic Manipulation. --- Software Engineering. --- Theory of Computation. --- Data processing. --- Communication theory --- Communication --- Cybernetics --- Computer software engineering --- Engineering --- Design, Logic --- Design of logic systems --- Digital electronics --- Electronic circuit design --- Logic circuits --- Machine theory --- Switching theory --- Informatics --- Science --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- Traitement réparti. --- Parallélisme (Informatique) --- Architecture, Computer. --- Mathematical logic. --- Computer logic. --- Computer science—Mathematics. --- Computers. --- Computer science logic --- Logic, Symbolic and mathematical --- Algebra of logic --- Logic, Universal --- Mathematical logic --- Symbolic and mathematical logic --- Symbolic logic --- Mathematics --- Algebra, Abstract --- Metamathematics --- Set theory --- Syllogism --- Architecture, Computer --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Computer systems --- Calculators --- Cyberspace --- ALGEBRA - data processing --- Computer Science --- Information theory --- Logic design --- Software Engineering --- 681.3*C24 --- 681.3*D13 --- 681.3*D2 --- 681.3*I6 --- 681.3*I6 Simulation and modeling (Computing methodologies)--See also {681.3*G3} --- Simulation and modeling (Computing methodologies)--See also {681.3*G3} --- 681.3*D2 Software engineering: protection mechanisms; standards--See also {681.3*K63}; {681.3*K51} --- Software engineering: protection mechanisms; standards--See also {681.3*K63}; {681.3*K51} --- 681.3*D13 Concurrent programming --- Concurrent programming --- 681.3*C24 Distributed systems: distributed databases; distributed applications; networkoperating systems --- Distributed systems: distributed databases; distributed applications; networkoperating systems --- Distributed processing --- Verification --- ALGEBRA
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