Garantía de entrega
SKU/Artículo: AMZ-1789341078
Hands-On GPU Computing with Python: Explore the capabilities of GPUs for solving high performance computational problems
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.95 kg
0.95 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
Viaja desde
USA
USA
Sobre este producto
- Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda AccelerateKey FeaturesUnderstand effective synchronization strategies for faster processing using GPUs Write parallel processing scripts with PyCuda and PyOpenCL Learn to use the CUDA libraries like CuDNN for deep learning on GPUsBook DescriptionGPUs are proving to be excellent general purpose-parallel computing solutions for high performance tasks such as deep learning and scientific computing. This book will be your guide to getting started with GPU computing. It will start with introducing GPU computing and explain the architecture and programming models for GPUs. You will learn, by example, how to perform GPU programming with Python, and you'll look at using integrations such as PyCUDA, PyOpenCL, CuPy and Numba with Anaconda for various tasks such as machine learning and data mining. Going further, you will get to grips with GPU work flows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance. By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly.What you will learnUtilize Python libraries and frameworks for GPU acceleration Set up a GPU-enabled programmable machine learning environment on your system with Anaconda Deploy your machine learning system on cloud containers with illustrated examples Explore PyCUDA and PyOpenCL and compare them with platforms such as CUDA, OpenCL and ROCm. Perform data mining tasks with machine learning models on GPUs Extend your knowledge of GPU computing in scientific applicationsWho this book is forData Scientist, Machine Learning enthusiasts and professionals who wants to get started with GPU computation and perform the complex tasks with low-latency. Intermediate knowledge of Python programming is assumed.Table of ContentsIntroduction to GPU computingDesigning A GPU Computing StrategySetting up a GPU Computing Platform with NVIDIA and AMDFundamentals of GPU programmingSetting up your environment for GPU programmingWorking with PyCUDAWorking with PyOpenCLWorking with Anaconda and Anaconda AccelerateContainerization on GPU enabled platformsMachine Learning on GPUs: Use casesGPU Acceleration for Scientific Applications using Deepchem
U$S 82,43
49% OFF
U$S 42,27
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 82,43
49% OFF
U$S 42,27
¡Comprá en hasta 12 cuotas sin interés con todas tus tarjetas!
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
