Tabla de Contenidos: “…7.4 Variable scope importance for correctness in OpenMP -- 7.5 Function-level OpenMP: Making a whole function thread parallel -- 7.6 Improving parallel scalability with high-level OpenMP -- 7.6.1 How to implement high-level OpenMP -- 7.6.2 Example of implementing high-level OpenMP -- 7.7 Hybrid threading and vectorization with OpenMP -- 7.8 Advanced examples using OpenMP -- 7.8.1 Stencil example with a separate pass for the x and y directions -- 7.8.2 Kahan summation implementation with OpenMP threading -- 7.8.3 Threaded implementation of the prefix scan algorithm -- 7.9 Threading tools essential for robust implementations -- 7.9.1 Using Allinea/ARM MAP to get a quick high-level profile of your application -- 7.9.2 Finding your thread race conditions with Intel® Inspector -- 7.10 Example of a task-based support algorithm -- 7.11 Further explorations -- 7.11.1 Additional reading -- 7.11.2 Exercises -- Summary -- 8 MPI: The parallel backbone -- 8.1 The basics for an MPI program -- 8.1.1 Basic MPI function calls for every MPI program -- 8.1.2 Compiler wrappers for simpler MPI programs -- 8.1.3 Using parallel startup commands -- 8.1.4 Minimum working example of an MPI program -- 8.2 The send and receive commands for process-to-process communication -- 8.3 Collective communication: A powerful component of MPI -- 8.3.1 Using a barrier to synchronize timers -- 8.3.2 Using the broadcast to handle small file input -- 8.3.3 Using a reduction to get a single value from across all processes -- 8.3.4 Using gather to put order in debug printouts -- 8.3.5 Using scatter and gather to send data out to processes for work -- 8.4 Data parallel examples -- 8.4.1 Stream triad to measure bandwidth on the node -- 8.4.2 Ghost cell exchanges in a two-dimensional (2D) mesh -- 8.4.3 Ghost cell exchanges in a three-dimensional (3D) stencil calculation…”

Tabla de Contenidos: “…Different Worlds1.4 - Demographics of corporate data; 1.5 - Corporate data analysis; 1.6 - The life cycle of data - understanding data over time; 1.7 - A brief history of data; Paper Tape and Punch Cards; Magnetic Tapes; Disk Storage; Database Management System; Coupled Processors; Online Transaction Processing; Data Warehouse; Parallel Data Management; Data Vault; Big Data; The Great Divide; 2.1 - A brief history of big data; An Analogy - Taking the High Ground; Taking the High Ground; Standardization with the 360; Online Transaction Processing…”

Tabla de Contenidos: “…Front Cover; High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches; Copyright; Contents; Contributors; Acknowledgments; Foreword; Making a bet on many-core; 2013 Stampede-Intel Many-Core System - A First; HPC journey and revelation; Stampede users discover: Its parallel programming; This book is timely and important; Preface; Inspired by 61 cores: A new era in programming; Chapter 1: Introduction; Applications and techniques; SIMD and vectorization; OpenMP and nested parallelism; Latency optimizations; Python; Streams; Ray tracing; Tuning prefetching…”

Tabla de Contenidos: “…Performance-oriented architectureProgramming tools and runtimes; Our computing environments; Paths to performance; Running Hydro2D; Hydro2D's structure; Computation scheme; Data structures; Measuring performance; Optimizations; Memory usage; Thread-level parallelism; Arithmetic efficiency and instruction-level parallelism; Data-level parallelism; Summary; The coprocessor vs the processor; A rising tide lifts all boats; Performance strategies; Chapter 3: Better Concurrency and SIMD on HBM ; The application: HIROMB - BOOS -Model; Key usage: DMI ; HBM execution profile…”

Tabla de Contenidos:

Tabla de Contenidos: “…2.2 What you need to start; 2.3 Software development flow; 2.4 Compiling your applications; 2.5 Software flow; 2.6 Data types in C programming; 2.7 Inputs, outputs, and peripherals accesses; 2.8 Microcontroller interfaces; 2.9 The Cortex® microcontroller software interface standard (CMSIS); Chapter 3 - Technical Overview; 3.1 General information about the Cortex®-M3 and Cortex-M4 processors; 3.2 Features of the Cortex®-M3 and Cortex-M4 processors; Chapter 4 - Architecture; 4.1 Introduction to the architecture; 4.2 Programmer's model…”

“…You’ll learn how to Identify your best opportunities to use parallelism Share data safely between multiple threads Write applications using POSIX or Windows threads Hand-code synchronization and sharing Take advantage of automatic parallelization and OpenMP Overcome common obstacles to scaling Apply new approaches to writing correct, fast, scalable parallel code Multicore Application Programming isn’t wedded to a single approach or platform: It is for every experienced C programmer working with any contemporary multicore processor in any leading operating system environment…”

“…With this practical book, you will attain a solid understanding of threads and will discover how to put this powerful mode of programming to work in real-world applications. The primary advantage of threaded programming is that it enables your applications to accomplish more than one task at the same time by using the number-crunching power of multiprocessor parallelism and by automatically exploiting I/O concurrency in your code, even on a single processor machine. …”

Tabla de Contenidos: “…7.2.3 Pseudocode -- Summary -- Exercises -- Chapter 8: Overview of C++ -- 8.1 Introduction -- 8.2 ANSI Standard -- 8.3 Object-oriented Technology -- 8.4 Disadvantages of Conventional Programming -- 8.5 Programming Paradigms -- 8.5.1 Monolithic Programming -- 8.5.2 Procedural Programming -- 8.5.3 Structured Programming Approach -- 8.6 Basic Concepts of C++ -- 8.7 Structure of C++ Program -- 8.7.1 Include Files Section -- 8.7.2 Class Declaration or Definition -- 8.7.3 Class Function Definitions -- 8.7.4 The main() Function -- 8.8 Creating Source File, Compiling and Linking in C++ -- 8.9 IDE and its Features -- 8.10 Character Set in C++ -- 8.11 Types of Tokens -- 8.12 Keywords -- 8.13 Identifiers -- 8.13.1 Variable Declaration and Initialization -- 8.14 Dynamic Initialization -- 8.15 Data Types in C++ -- 8.16 Basic Data Type -- 8.17 Derived Data Type -- 8.17.1 Pointers -- 8.17.2 Functions -- 8.17.3 Arrays -- 8.17.4 References -- 8.18 User-defined Data Type -- 8.18.1 Structure and Classes -- 8.18.2 Union -- 8.18.3 Enumerated Data Type -- 8.19 The void Data Type -- 8.20 Type Modifiers -- 8.21 Wrapping Around -- 8.22 Constants -- 8.22.1 Literal Constant -- 8.22.2 Symbolic Constant -- 8.23 Constant Pointers -- 8.23.1 Constant Pointer -- 8.23.2 Pointer to Constant -- 8.23.3 Pointer and Variable both Constants -- Summary -- Exercises -- Chapter 9: Operators and Expressions -- 9.1 Introduction -- 9.2 Precedence of Operators in C++ -- 9.3 Expressions and their Evaluation -- 9.4 Referencing (&amp -- ) and Dereferencing (*) Operators -- 9.5 Scope Access Operator -- 9.6 Memory Management Operators -- 9.7 Comma Operator -- 9.8 Comma in Place of Curly Braces -- 9.9 Type Conversion -- 9.9.1 Implicit Type Conversion -- 9.9.2 Explicit Type Conversion -- Summary -- Exercises -- Chapter 10: Input and Output in C++ -- 10.1 Introduction -- 10.2 Streams in C++…”

“…What You Will Learn How the processor operates How computers represent data internally How programs interact with the operating system How to write and use dynamic code libraries How high-level programming languages implement their features…”

Tabla de Contenidos: “…-- Flowable and Subscriber -- Creating Flowable from scratch -- Creating Flowable from Observable -- BackpressureStrategy.MISSING and onBackpressureXXX() -- Operator onBackpressureBuffer() -- Operator onBackpressureDrop() -- Operator onBackpressureLatest() -- Generating Flowable with backpressure at source -- ConnectableFlowable -- Processor -- Learning Buffer, Throttle, and Window operators -- The buffer() operator -- The window() operator -- The throttle() operators -- Summary -- Chapter 5: Asynchronous Data Operators and Transformations -- Operator -- The filtering/suppressing operators -- The debounce operator -- The distinct operators - distinct, distinctUntilChanged -- The elementAt operator -- Filtering emissions - filter operator -- The first and last operator -- The ignoreElements operator -- The transforming operators -- The map operator -- Casting emissions (cast operator) -- The flatMap operator -- The defaultIfEmpty operator -- The switchIfEmpty operator -- The startWith operator -- Sorting emissions (sorted operator) -- Accumulating data - scan operator -- Reducing operators -- Counting emissions (count operator) -- Accumulating emissions - reduce operator -- The collection operators -- The error handling operators -- The utility operators -- Summary -- Chapter 6: More on Operators and Error Handling -- Combining producers (Observable/Flowable) -- The startWith operator -- Zipping emissions - zip operator -- The zipWith operator -- The combineLatest operator -- Merging Observables/Flowables - merge operator -- Concatenating producers (Observable/Flowable) -- Ambiguously combining producers -- Grouping -- flatMap, concatMap - In details -- When to use flatMap operator -- When to use concatMap operator -- Understanding switchMap operator…”

Tabla de Contenidos: “…Front Cover -- Multicore and GPU Programming: An Integrated Approach -- Copyright -- Dedication -- Contents -- List of Tables -- Preface -- What Is in This Book -- Using This Book as a Textbook -- Software and Hardware Requirements -- Sample Code -- Chapter 1: Introduction -- 1.1 The era of multicore machines -- 1.2 A taxonomy of parallel machines -- 1.3 A glimpse of contemporary computing machines -- 1.3.1 The cell BE processor -- 1.3.2 Nvidia's Kepler -- 1.3.3 AMD's APUs -- 1.3.4 Multicore to many-core: tilera's TILE-Gx8072 and intel's xeon phi -- 1.4 Performance metrics -- 1.5 Predicting and measuring parallel program performance -- 1.5.1 Amdahl's law -- 1.5.2 Gustafson-barsis's rebuttal -- Exercises -- Chapter 2: Multicore and parallel program design -- 2.1 Introduction -- 2.2 The PCAM methodology -- 2.3 Decomposition patterns -- 2.3.1 Task parallelism -- 2.3.2 Divide-and-conquer decomposition -- 2.3.3 Geometric decomposition -- 2.3.4 Recursive data decomposition -- 2.3.5 Pipeline decomposition -- 2.3.6 Event-based coordination decomposition -- 2.4 Program structure patterns -- 2.4.1 Single-program, multiple-data -- 2.4.2 Multiple-program, multiple-data -- 2.4.3 Master-worker -- 2.4.4 Map-reduce -- 2.4.5 Fork/join -- 2.4.6 Loop parallelism -- 2.5 Matching decomposition patterns with program structure patterns -- Exercises -- Chapter 3: Shared-memory programming: threads -- 3.1 Introduction -- 3.2 Threads -- 3.2.1 What is a thread? …”

Tabla de Contenidos: “…Integers -- Specifying integer literals -- Using bitset to show bit patterns -- Determining integer byte order -- Floating point types -- Specifying floating point literals -- Characters and strings -- Character types -- Using character macros -- Specifying character literals -- Specifying string literals -- Unicode literals -- Raw strings -- String byte order -- Boolean -- void -- Initializers -- Default values -- Declarations without a type -- Storage classes -- Using type aliases -- Aggregating data in record types -- Structures -- Initializing -- Structure fields -- Using structure names -- Determining alignment -- Storing data in the same memory with unions -- Accessing runtime type information -- Determining type limits -- Converting between types -- Type conversions -- Promoting conversions -- Narrowing conversions -- Narrowing to bool -- Converting signed types -- Casting -- Casting away const-ness -- Casting without runtime checks -- Casting pointers without runtime checks -- Casting with runtime checks -- Casting with list initializer -- Using C casts -- Using C++ types -- Summary -- Chapter 4: Working with Memory, Arrays, and Pointers -- Using memory in C++ -- Using C++ pointer syntax -- Using null pointers -- Types of memory -- Pointer arithmetic -- Using arrays -- Function parameters -- Multidimensional arrays -- Passing multidimensional arrays to functions -- Using arrays of characters -- Comparing strings -- Preventing buffer overruns -- Using pointers in C++ -- Accessing out of bounds -- Pointers to deallocated memory -- Converting pointers -- Constant pointers -- Changing the type pointed to -- Allocating memory in code -- Allocating individual objects -- Allocating arrays of objects -- Handling failed allocations -- Using other versions of the new operator -- Memory lifetime -- The Windows SDK and pointers…”

“…The book begins with coverage of Backtrack Programming, together with a set of data structures whose links perform "delightful dances" and are ideally suited to this domain. …”

Tabla de Contenidos: “…-- 1.5 Example Code and Datasets -- 1.6 Parting Words -- Part 1 The Stuff You'll Always Use -- Chapter 2 The Data Science Road Map -- 2.1 Frame the Problem -- 2.2 Understand the Data: Basic Questions -- 2.3 Understand the Data: Data Wrangling -- 2.4 Understand the Data: Exploratory Analysis -- 2.5 Extract Features -- 2.6 Model -- 2.7 Present Results -- 2.8 Deploy Code -- 2.9 Iterating -- 2.10 Glossary -- Chapter 3 Programming Languages -- 3.1 Why Use a Programming Language? …”