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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/introduction-to-concurrent-programming
课程评论：没有评论
课程名称：CUDA并行编程导论 课程简介：本课程旨在帮助学生准备开发能够并行处理大量数据的代码。它将重点讲解并发编程的基础知识，如CPU/GPU架构、C和Python的多线程编程，以及CUDA软件和硬件的介绍。 课程大纲： 1. **课程概述** 本模块的目的是让学生了解课程的运行方式、主题、考核方式及期望。 2. **CPU和GPU上的并行编程核心原则** 为了创建能够更快处理大量数据的软件，操作系统、编程语言和框架需要采用策略以最大化数据的访问和修改速度，同时减少数据处于不正确状态的可能性。学生将学习经典的并发问题，如哲学家就餐问题，并讨论操作系统和编程语言如何处理这些问题，以及实际大数据的并发应用。 3. **C和Python的并行编程导论** 现代编程语言允许开发者创建复杂逻辑的软件，以并行方式处理数据，利用大多数计算机中的多个CPU核心。学生将开发简单的软件，使用C++和Python 3编程语言并发处理数据集。 4. **NVidia GPU硬件/软件** 本模块的目的是让学生理解CUDA所使用的硬件和软件基础，以便正确地开发软件，以最优方式利用GPU资源。 5. **GPU编程导论** 本模块的目的是使学生理解开发基于CUDA的软件的原则。 通过本课程的学习，学生将掌握并发编程的基本原理，理解并发操作的挑战，并能够使用现代编程语言开发高效的并行解决方案。
Part: 1
Title:Course Overview
Description:The purpose of this module is for students to understand how the course will be run, topics, how they will be assessed, and expectations.
Part: 2
Title:Core Principles of Parallel Programming on CPUs and GPUs
Description:In order to create software that process greater amounts of data at faster speeds, software operating systems, programming languages, and frameworks require strategies for accessing and modification of data in a manner that maximizes speed, while minimizing the possibility of data being in incorrect states. In this module, students will be presented canonical concurrency problems such as the Dining Philosophers. Additionally, they will learn how operating systems and programming languages handle these problems, and discuss real world big data concurrency applications.
Part: 3
Title:Introduction to Parallel Programming with C and Python
Description:Modern programming languages allow developers to create software with complex logic for manipulation of data in parallel, taking advantage of the multiple CPU cores in most computers. Students will develop simple software, written in the C++ and Python 3 programming languages, that process data sets concurrently.
Part: 4
Title:NVidia GPU Hardware/Software
Description:The purpose of this module is for students to understand the basis in hardware and software that CUDA uses. This is required to appropriately develop software to optimally take advantage of GPU resources.
Part: 5
Title:Introduction to GPU Programming
Description:The purpose of this module is for students to understand the principles of developing CUDA-based software.
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.
