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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/parallelism-ia
课程评论：没有评论
课程名称：Intel架构下的并行计算基础 课程概述：本课程将向您介绍现代Intel架构处理器中存在的多种并行性形式，并教授处理这些并行性在应用程序中的编程框架。您将能接触到现代多核处理器集群（Intel Xeon Phi架构），进行带有评分的编程练习实验。此课程适用于各种高性能计算（HPC）和数据中心工作负载及框架，包括人工智能（AI）。您将学习如何使用向量指令处理数据并行性，在共享内存中使用线程进行任务并行，利用消息传递在分布式内存中实现并行，并通过优化的数据容器处理内存架构并行性。这些知识将帮助您显著加速计算应用，同时保持代码的可移植性和未来适应性。 前提条件：需具备在Linux环境下用C/C++或Fortran编程的能力，以及Linux命令行熟练度（导航、文件复制、文本编辑器编辑文件、编译等）。 课程大纲： 第一部分：现代代码 描述：在介绍中，我们将学习... 第二部分：向量化 描述：... 第三部分：使用OpenMP进行多线程编程 描述：... 第四部分：内存流量 描述：... 第五部分：集群与MPI 描述：...
Part: 1
Title:Modern Code
Description:In the Introduction we will learn...
Part: 2
Title:Vectorization
Description:
Part: 3
Title:Multithreading with OpenMP
Description:
Part: 4
Title:Memory Traffic
Description:
Part: 5
Title:Clusters and MPI
Description:
This course will introduce you to the multiple forms of parallelism found in modern Intel architecture processors and teach you the programming frameworks for handling this parallelism in applications. You will get access to a cluster of modern manycore processors (Intel Xeon Phi architecture) for experiments with graded programming exercises. This course can apply to various HPC and datacenter workloads and framework including artificial intelligence (AI). You will learn how to handle data parallelism with vector instructions, task parallelism in shared memory with threads, parallelism in distributed memory with message passing, and memory architecture parallelism with optimized data containers. This knowledge will help you to accelerate computational applications by orders of magnitude, all the while keeping your code portable and future-proof. Prerequisite: programming in C/C++ or Fortran in the Linux environment and Linux shell proficiency (navigation, file copying, editing files in text-based editors, compilation).
