courseraПрограммирование

Introduction to Concurrent Programming with GPUs

Курс от Johns Hopkins University

Начальный≈ 19.5 чАнглийский

О курсе

This course will help prepare students for developing code that can process large amounts of data in parallel. It will focus on foundational aspects of concurrent programming, such as CPU/GPU architectures, multithreaded programming in C and Python, and an introduction to CUDA software/hardware.

Навыки, которые вы освоите

C++ (Programming Language)Hardware Architecture Python Programming Development Environment OS Process Management Programming Principles Algorithms C and C++Computer Architecture Program Development Data Sharing Data Access

Программа курса

5 модулей · 66 учебных материалов

01Course Overview11 материалов

GPU Programming Specialization

Course OverviewЧтение Course OutlineЧтение GPU Programming Specialization OverviewВидео

Course Technical and Programming Expectations

Course ExpectationsВидео

Учитесь у экспертов

Chancellor Thomas Pascale

Instructor and Software Engineer

В каталоге вашей программы

Инвестируйте в себя

Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 19.5 ч

5 модулей

Язык: Английский

Субтитры: Арабский, Французский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Нидерландский, Корейский, Немецкий, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Хинди, Японский, Казахский, Польский

Introduction to Concurrent Programming with GPUs

О курсе

Навыки, которые вы освоите

Программа курса

GPU Programming Specialization

Course Technical and Programming Expectations

Учитесь у экспертов

Chancellor Thomas Pascale

Coursera Lab and Assignment Usage

Concurrent Programming with Modern CPUs

Concurrent Programming Pitfalls

Concurrent Programming Problems and Algorithms

Concurrent Programming Patterns

Serial Vs Parallel Programming and Flynn's Taxonomy

Syntax and Parallel Programming Patterns of Python 3

Screen Capture of Execution of Multithreaded Python 3

Syntax and Parallel Programming Patterns of C++

Screen Capture of Execution of Multithreaded C++

Overview of NVidia versus integrated GPUs

GUI/UI Tools for Identifying Installed GPU Hardware

NVidia Hardware Architectures

Installation of CUDA on Linux

CUDA Software Layers and Compilation

Compilation of CUDA Code

CUDA Runtime and Driver APIs

Code Syntax for Determining Target Environment

CUDA Software Keywords

CUDA Programming in Text Editors and Integrated Development Environments

Complex CUDA Software Project Structure and Best Practices