[Coursera]High Performance Scientific Computing #1 - 2014-03-31@UW
本帖最后由 EroicaCMCS 于 2014-4-7 14:37 编辑 |
UW的High Performance Scientific Computing开课了（现在刚开了一个星期），不知道有没有感兴趣的小伙伴？
介绍了很多很实用的工具，(第一周让大家熟悉git, unix shell, ipython), 理论方面（比如并行算法）涉及的比较少，至少现在看起来是这样的。
下面附 course welcome page:
Welcome to High Performance Scientific Computing!
Thank you for joining the High Performance Scientific Computing course! Please take a few moments to read through the course welcome page followed by watching the course orientation and week one lecture videos. There is a lot of useful information there about the course.
For now, you should plan to allocate between five and ten hours per week on the course. There will be roughly 2.5 hours of lectures per week, as well as quizzes (graded automatically) for each lecture.
In this course you will explore how computation and simulation are increasingly important in all aspects of science and engineering. At the same time, writing efficient computer programs to take full advantage of current computers is becoming increasingly difficult. Along the way there will also be discussion of software engineering tools such as debuggers, unit testing, makefiles, and the use of version control systems. After all, your time is more valuable than computer time, and a program that runs fast is totally useless if it produces the wrong results. High performance programming is also an important aspect of high performance scientific computing, and so another main theme of the course is the use of basic tools and techniques to improve your efficiency as a computational scientist.
There is no textbook; the course is self-contained. Course notes and resources can be found linked on the navigation bar. Course lecture notes are available online, next to the lecture links. The notes should be read through thoroughly and routinely as all the course content is contained therein. You are also encouraged to interact with each other within the discussion forums in order to solve the suggested homework problems. Homework will not be collected or graded, but sample solutions will be available after the suggested completion dates.
Only freely available open source software will be used in this course, and the course notes include instructions for downloading and installing what you need. There are also instructions for two other options that allow you to avoid installing multiple software packages individually: you can either use a virtual machine VM on the free VirtualBox software, or do your computing “in the cloud” on Amazon Web Services (for which you will need to set up your own account).
Again, welcome, and I hope that you enjoy this course!
Dr. Randall J. LeVeque
Mon 31 Mar 2014 1:01 AM PDT