1.

Record Nr.

UNINA9910458434103321

Autore

Cheng John

Titolo

Professional CUDA C Programming [[electronic resource]]

Pubbl/distr/stampa

Hoboken, : Wiley, 2014

ISBN

1-118-73927-2

Descrizione fisica

1 online resource (527 p.)

Altri autori (Persone)

GrossmanMax

McKercherTy

Disciplina

004.35

004/.35

Soggetti

Computer architecture

Multiprocessors

Parallel processing (Electronic computers)

Parallel programming (Computer science)

Engineering & Applied Sciences

Computer Science

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

Cover; Title Page; Copyright; Contents; Chapter 1 Heterogeneous Parallel Computing with CUDA; Parallel Computing; Sequential and Parallel Programming; Parallelism; Computer Architecture; Heterogeneous Computing; Heterogeneous Architecture; Paradigm of Heterogeneous Computing; CUDA: A Platform for Heterogeneous Computing; Hello World from GPU; Is CUDA C Programming Difficult?; Summary; Chapter 2 CUDA Programming Model; Introducing the CUDA Programming Model; CUDA Programming Structure; Managing Memory; Organizing Threads; Launching a CUDA Kernel; Writing Your Kernel; Verifying Your Kernel

Handling ErrorsCompiling and Executing; Timing Your Kernel; Timing with CPU Timer; Timing with nvprof; Organizing Parallel Threads; Indexing Matrices with Blocks and Threads; Summing Matrices with a 2D Grid and 2D Blocks; Summing Matrices with a 1D Grid and 1D Blocks; Summing Matrices with a 2D Grid and 1D Blocks; Managing Devices; Using the Runtime API to Query GPU Information; Determining



the Best GPU; Using nvidia-smi to Query GPU Information; Setting Devices at Runtime; Summary; Chapter 3 CUDA Execution Model; Introducing the CUDA Execution Model; GPU Architecture Overview

The Fermi ArchitectureThe Kepler Architecture; Profile-Driven Optimization; Understanding the Nature of Warp Execution; Warps and Thread Blocks; Warp Divergence; Resource Partitioning; Latency Hiding; Occupancy; Synchronization; Scalability; Exposing Parallelism; Checking Active Warps with nvprof; Checking Memory Operations with nvprof; Exposing More Parallelism; Avoiding Branch Divergence; The Parallel Reduction Problem; Divergence in Parallel Reduction; Improving Divergence in Parallel Reduction; Reducing with Interleaved Pairs; Unrolling Loops; Reducing with Unrolling

Reducing with Unrolled WarpsReducing with Complete Unrolling; Reducing with Template Functions; Dynamic Parallelism; Nested Execution; Nested Hello World on the GPU; Nested Reduction; Summary; Chapter 4 Global Memory; Introducing the CUDA Memory Model; Benefits of a Memory Hierarchy; CUDA Memory Model; Memory Management; Memory Allocation and Deallocation; Memory Transfer; Pinned Memory; Zero-Copy Memory; Unified Virtual Addressing; Unified Memory; Memory Access Patterns; Aligned and Coalesced Access; Global Memory Reads; Global Memory Writes; Array of Structures versus Structure of Arrays

Performance TuningWhat Bandwidth Can a Kernel Achieve?; Memory Bandwidth; Matrix Transpose Problem; Matrix Addition with Unified Memory; Summary; Chapter 5 Shared Memory and Constant Memory; Introducing CUDA Shared Memory; Shared Memory; Shared Memory Allocation; Shared Memory Banks and Access Mode; Configuring the Amount of Shared Memory; Synchronization; Checking the Data Layout of Shared Memory; Square Shared Memory; Rectangular Shared Memory; Reducing Global Memory Access; Parallel Reduction with Shared Memory; Parallel Reduction with Unrolling

Parallel Reduction with Dynamic Shared Memory

Sommario/riassunto

Break into the powerful world of parallel GPU programming with this down-to-earth, practical guide  Designed for professionals across multiple industrial sectors, Professional CUDA C Programming  presents CUDA -- a parallel computing platform and programming model designed to ease the development of GPU programming -- fundamentals in an easy-to-follow format, and teaches readers how to think in parallel and implement parallel algorithms on GPUs. Each chapter covers a specific topic, and includes workable examples that demonstrate the development process, allowing readers to explore both the "



2.

Record Nr.

UNISA996204082603316

Titolo

East European Jewish affairs

Pubbl/distr/stampa

London, : Routledge, 1992-

ISSN

1743-971X

Disciplina

947.004924

Soggetti

Jews - Former Soviet republics

Jews - Soviet Union

Jews - Europe, Eastern

Ethnic relations

Jews

Periodicals.

Former Soviet republics Ethnic relations Periodicals

Soviet Union Ethnic relations Periodicals

Europe, Eastern Ethnic relations Periodicals

Eastern Europe

Soviet Union

Soviet Union Former Soviet republics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Periodico

Note generali

Refereed/Peer-reviewed



3.

Record Nr.

UNINA9910811205803321

Autore

Falconer Melanie

Titolo

College study hacks : 101 ways to study easier and faster / / by Melanie Falconer

Pubbl/distr/stampa

Ocala, Florida : , : Atlantic Publishing Group, Inc., , [2017]

©2017

ISBN

1-62023-192-1

Descrizione fisica

1 online resource (232 pages)

Disciplina

378.17

Soggetti

Study skills

College student orientation

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.