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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/cuda-at-scale-for-the-enterprise
课程评论：没有评论
课程名称：企业级大规模CUDA 概述：本课程旨在帮助学生学习如何超越最常见的消费级GPU安装，扩展GPU和管理CPU的使用。学生将学习如何管理异步工作流程，发送和接收事件以封装数据传输和控制信号。此外，学生将通过应用GPU进行数据排序和图像处理，实施自己的软件，运用这些技术和库。 课程结束时，学员将能够做到以下几点： - 开发能够使用多个CPU和GPU的软件 - 利用CUDA的事件和流功能开发异步工作流程的软件 - 运用CUDA计算模型解决经典的编程挑战，包括数据排序和图像处理 成功完成本课程需要具备并行编程的理解以及C/C++编程经验。 该课程对高性能计算、数据处理和机器学习领域的软件开发者和数据科学家非常适用。 课程大纲： 第一部分：课程概述 描述：本模块的目的是让学生了解课程的运行方式、主题、评估方式及期望。 第二部分：多CPU/GPU系统 描述：在专业环境中，单个CPU管理单个GPU的配置并不能有效解决复杂挑战。学生将应用CUDA的能力，允许多个CPU之间的通信和在多个GPU上管理软件内核，从而扩大输入数据的大小和计算复杂性。学生将学习此类同步处理的优缺点。 第三部分：CUDA事件和流 描述：学生将学习在程序中使用CUDA事件和流，以实现异步数据和控制流。这将允许更具交互性和持久性的软件，包括分析用户界面、近实时视频或金融数据流以及动态商业处理系统。 第四部分：使用GPU进行排序 描述：本模块的目的是让学生理解CUDA所用的硬件和软件基础。这是适当开发软件以最佳利用GPU资源所必需的。 第五部分：使用Nvidia编程原语的图像处理 描述：本模块的目的是让学生理解开发基于CUDA的软件的原则。
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:Multiple CPU/GPU Systems
Description:In professional settings, use of one CPU managing one GPU, is not a viable configuration to solve complex challenges. Students will apply CUDA capabilities for allowing multiple CPUs to communicate and manage software kernels on multiple GPUs. This will allow for scaling the size of input data and computational complexity. Students will learn the advantages and limitations of this form of synchronous processing.
Part: 3
Title:CUDA Events and Streams
Description:Students will learn to utilize CUDA events and streams in their programs, to allow for asynchronous data and control flows. This will allow more interactive and long-lasting software, including analytic user interfaces, near live-streaming video or financial feeds, and dynamic business processing systems.
Part: 4
Title:Sorting Using GPUs
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:Image Processing using Nvidia Programming Primitives
Description:The purpose of this module is for students to understand the principles of developing CUDA-based software.
This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. Also, students will walk through application of GPUs to sorting of data and processing images, implementing their own software using these techniques and libraries. By the end of the course, you will be able to do the following: - Develop software that can use multiple CPUs and GPUs - Develop software that uses CUDA’s events and streams capability to create asynchronous workflows - Use the CUDA computational model to to solve canonical programming challenges including data sorting and image processing To be successful in this course, you should have an understanding of parallel programming and experience programming in C/C++. This course will be extremely applicable to software developers and data scientists working in the fields of high performance computing, data processing, and machine learning.
