Garantía de entrega
SKU/Artículo: AMZ-1805124544
GPU Programming with C++ and CUDA: Uncover effective techniques for writing efficient GPU-parallel C++ applications
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.65 kg
0.65 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Learn to solve parallel problems with GPU-accelerated C++ code and create reusable libraries that can be accessed from other programming languagesKey FeaturesHarness the power of GPU parallelism to accelerate real-world tasksUtilize CUDA streams and scale performance with custom C++ solutionsCreate reusable GPU libraries and expose them to Python seamlesslyBook DescriptionWritten by Paulo Motta, a senior researcher with decades of experience, this comprehensive GPU programming book is an essential guide for leveraging the power of parallelism to accelerate your computations. The first section introduces the concept of parallelism and provides practical advice on how to think about and utilize it effectively. Starting with a basic GPU program, you then gain hands-on experience in managing the device. This foundational knowledge is then expanded by parallelizing the program to illustrate how GPUs enhance performance.The second section explores GPU architecture and implementation strategies for parallel algorithms, and offers practical insights into optimizing resource usage for efficient execution.In the final section, you will explore advanced topics such as utilizing CUDA streams. You will also learn how to package and distribute GPU-accelerated libraries for the Python ecosystem, extending the reach and impact of your work.Combining expert insight with real-world problem solving, this book is a valuable resource for developers and researchers aiming to harness the full potential of GPU computing. The blend of theoretical foundations, practical programming techniques, and advanced optimization strategies it offers is sure to help you succeed in the fast-evolving field of GPU programming.What you will learnManage GPU devices and accelerate your applicationsApply parallelism effectively using CUDA and C++Choose between existing libraries and custom GPU solutionsPackage GPU code into libraries for use with PythonExplore advanced topics such as CUDA streamsImplement optimization strategies for resource-efficient executionWho this book is forC++ developers and programmers interested in accelerating applications using GPU programming will benefit from this book. It is suitable for those with solid C++ experience who want to explore high-performance computing techniques. Familiarity with operating system fundamentals will help when dealing with device memory and communication in advanced chapters.Table of ContentsIntroduction to Parallel ProgrammingGetting StartedHello CUDAHello again, but in parallelA closer look into the GPU worldData Management and PersistencePerformance strategiesUsing multiple GPUsExposing your code as a Python LibraryExploring the existing GPU models
U$S 60,73
44% OFF
U$S 33,74
IMPORTÁ FACIL
Comprando este producto podrás descontar el IVA con tu número de RUT
NO CONSUME FRANQUICIA
Si tu carrito tiene solo libros o CD’s, no consume franquicia y podés comprar hasta U$S 1000 al año.
U$S 60,73
44% OFF
U$S 33,74
Llega en 5 a 11 días hábiles
con envío
Tienes garantía de entrega
Compra protegida
Disfruta de una experiencia de compra segura y confiable
![]()
Garantía de entrega
Con Tiendamia todas tus compras cuentan con Garantía de Entrega o devolución total de tu dinero.
Compras 100% seguras y garantizadas, para que pidas lo que soñás y lo recibas del mundo a tu puerta.
Saber más.
Tarjetas prepagas, debito, y credito
Paga hasta en 12 cuotas sin interés con tarjetas de crédito.
Visa
Mastercard
American Express
Dinners
Discover
Lider
Midinero
OCA
OCA Blue
Tarjeta PREX
Pagos a través de PayPal
Paga en dólares con Tarjetas internacionales a través de PayPal.
PayPal
