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所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-to-use-hpc-systems-and-supercomputers/
课程评论：没有评论
课程名称：科学计算大师班：并行与分布式计算 课程概述：欢迎参加本平台上首个高性能计算（HPC）系统课程。该课程旨在介绍HPC系统及其软件栈，特别设计用来帮助您利用并行和分布式编程以及计算资源，加速复杂问题的解决。您可以将所学知识应用到机器学习、深度学习、数据科学和大数据等领域。HPC集群通常由大量计算机（称为“节点”）组成，虽然从外部看集群像一个单一系统，但内部工作非常复杂。与更一般的客户端-服务器计算模型不同，集群计算利用多个机器提供更强大的计算环境，通常通过一个操作系统实现。 您将学习到： - 超级计算的历史、实例及超级计算机与HPC集群的比较 - 高性能计算集群的组成部分，如登录节点、计算节点、主节点和存储节点等 - HPC网络的基本构造及其优势 - PBS（可排程批处理系统）基础，包括基本命令、任务提交、作业状态等 - Slurm系统的使用，包括分布式MPI和GPU作业的调度 - OpenMP的基本概念，如工作共享构造及并行for循环 - GPU及CUDA编程基础，提供简单易懂的示例帮助理解 - AMD GPU及HIP的并行编程入门，涵盖基本概念到高级实现 - AWS HPC的建设与应用，利用云技术的优势构建HPC集群 此外，课程还将提供Zoom直播课堂，讲解并行与分布式计算以及HPC系统软件栈的不同方面，包括Slurm、PBS Pro、OpenMP、MPI和CUDA。购买该课程的学生还将获得科学编程学校的交互式学习模块的免费访问权限。 免责声明：课程结合了一大学期的知识（价值2500-6000美元），提供的是高水平的概述。请加入我们的问答直播社区，随时获得其他学生和讲师的免费帮助。本课程是科学计算大师课程的一个组成部分。
Welcome to the First-ever High Performance Computing (HPC) Systems course on the Udemy platform. The goal main of this course is to introduce you with the HPC systems and its software stack. This course has been specially designed to enable you to utilize parallel & distributed programming and computing resources to accelerate the solution of a complex problem with the help of HPC systems and Supercomputers. You can then use your knowledge in Machine learning, Deep learning, Data Sciences, Big data and so on.HPC clusters typically have a large number of computers (often called ‘nodes') and, in general, most of these nodes would be configured identically. Though from the out side the cluster may look like a single system, the internal workings to make this happen can be quite complex. This idea should not be confused with a more general client-server model of computing as the idea behind clusters is quite unique. Cluster computing utilize multiple machines to provide a more powerful computing environment perhaps through a single operating system.WHAT DO YOU LEARN?A Little bit of Supercomputing history, Supercomputing examples, Supercomputers vs. HPC clusters, HPC clusters computers, Benefits of using cluster computing.Components of a High Performance Systems (HPC) cluster, Properties of Login node(s), Compute node(s), Master node(s), Storage node(s), HPC networks and so on.Introduction to PBS, PBS basic commands, PBS `qsub`, PBS `qstat`, PBS `qdel` command, PBS `qalter`, PBS job states, PBS variables, PBS interactive jobs, PBS arrays, PBS MATLAB exampleIntroduction to Slurm, Slurm commands, A simple Slurm job, Slurm distrbuted MPI and GPU jobs, Slurm multi-threaded OpenMP jobs, Slurm interactive jobs, Slurm array jobs, Slurm job dependenciesOpenMP basics, Open MP - clauses, worksharing constructs, OpenMP- Hello world!, reduction and parallel `for-loop`, section parallelization, vector addition, MPI - hello world! send/ receive and `ping-pong` Parallel programming - GPU and CUDA: Finally, it gives you a concise beginner friendly guide to the GPUs - graphics processing units, GPU Programming - CUDA, CUDA - hello world and so on! We understand that CUDA is a difficult API, particularly the memory models. We have added some easy to understand CUDA lessons with examples to make your life easy and comfortable to grasp the basics fast!Parallel programming - AMD GPU and HIP (New! Aug 2023): Learn parallel programming on AMD GPU's with ROCm and HIP from basic concepts to advance implementations. We will start our discussion by looking at basic concepts including AMD GPU programming, execution model, and memory model. Then we will show you how to implement algorithms using ROCm and HIP.AWS HPC: With the recent advantage of the faster Cloud technologies, AWS provides the most elastic and scalable cloud infrastructure to run your HPC applications. With virtually unlimited capacity, engineers, researchers, and HPC system owners can innovate beyond the limitations of on-premises HPC infrastructure. We have added lectures to show and tell you on how to build a AWS HPC cluster and how to run codes -easily!Based on your earlier feedback, we are introducing a Zoom live class lecture series on this course through which we will explain different aspects of the Parallel and distributed computing and the High Performance Computing (HPC) systems software stack: Slurm, PBS Pro, OpenMP, MPI and CUDA! Live classes will be delivered through the Scientific Programming School, which is an interactive and advanced e-learning platform for learning scientific coding. Students purchasing this course will receive free access to the interactive version (with Scientific code playgrounds) of this course from the Scientific Programming School (SCIENTIFIC PROGRAMMING IO). Instructions to join are given in the additional contents section.DISCLAIMERWe created here a total of one university semester worth of knowledge (valued USD $2500-6000) into one single video course, and hence, it's a high-level overview. Don't forget to join our Q & A live community where you can get free help anytime from other students and the instructor. This awesome course is a component of the Learn Scientific Computing master course.
