Introduction to Computational Science Tools

Semester Goal:

Upon the successful conclusion of this colloquium students should have an increased awareness of computing, software, networking, and visualization resources available at Penn State, and the necessary skills to use appropriate hardware and software for problems within their respective disciplines. Successful students will obtain the necessary skills to make informed decisions regarding how to proceed computationally when they need to tackle a class or research project that can benefit from such techniques, as well as information needed for follow-up investigation of specific techniques or resources that may be applicable in their future work.

Outline and Objectives:

1. First Day and Course Description ( Nucciarone and Long) [1 session]
   • Software Education, What is HPC?, What is CSci?, ITS HelpDesk, and ITS Organization Info Slides,


2. High Performance Computing Overview
   • Historical development of parallel systems (Nucciarone) [1 session]
   • HPC Systems at PSU and National Labs (Nucciarone) [1 session]
   • GPU's, Cell Processors, and Multi-Core Chips (???) [1 session]
   
   
3. Networking and Collaboration
   • Networking, IPv6, Internet2, and the Future of the Internet (Leous) [1 session]
   • Collaborative Tools and their role in research computing (Leous, Adam Focht) [2 sessions]
   
   
4. LaTeX ( Anna Pechenkina) [1 session, Sept. 15]


5. Programming and Software
   • Matlab and Mathematica (Abdul and Vikas) [1 Lecture and 1 Lab]
   • Object Oriented Programming (OOP) ( Long) [1 session]
   • Software Engineering ( Long) [1 session]
   • Integrated Development Environments (IDE) and Version Control (Leous and Moore) [2 Lectures and 1 Lab]
   • Numerical libraries (Nucciarone) [2 sessions]
   • Profiling / debugging / code optimization (Nucciarone) [2 sessions]
   • Parallel Programming with MPI and OpenMP (Nucciarone) [3 sessions]
   
   
6. Statistics and Probability
   • Statistical Software and the R Project ( Prof. Altman ) [1 Lecture]
   • Statistical Software (Lemmon and Schafer) [1 Lecture]
   • Probability (?) [1 Lecture]
   
   
7. Graphics and Visualization
   • IDL Graphics Software (Abdul) [1 Lecture and 1 Lab]
   • Other Graphics Software (Ensight, Tecplot, or ?) [1 Lecture ]
   • Virtual Reality, Stereo Graphics, and Collaborative Environments (Otto) [2 sessions]
   
   
8. Wrap Up Session (Nucciarone and Long) [1 session]

Grading

And the end of each of the major sections of talks, there will be a roughly 10-15 min. quiz at the beginning of class where you will demonstrate some mastery of the previous week's topic. The course grade will be entirely based on these assignments. These CANNOT be made up. If you miss one, you get a 0 grade for that one.

Exam Policy

There will be no exams as part of this colloquium.

Class attendance

Class attendance is mandatory. Due to the rotation of presenters and topics throughout the semester, much of the information presented in class may not be available elsewhere or at alternate times. Quizzes or assignments missed due to unscheduled absence or leaving a class early cannot be made up. If you know that you will need to miss an upcoming class please contact the class coordinator via e-mail (beatnic@aset.psu.edu) or telephone (814 865-5333) at least one-week prior to the class in question to determine whether alternate arrangements can be made for that session.

Class cancellation

In the event of inclement weather you may check to see if classes are canceled by examining various Penn State resources such as the Penn State Portal (http://portal.psu.edu) or PSU Live ( http://live.psu.edu).

Academic Integrity Statement

All submitted work must be your own and not copied in whole or in part from another student or textbook. In addition, all material that is not your own (ideas or words) in papers must be properly cited. If you are not sure how to cite material in your paper, see your instructor. It is your responsibility to avoid plagiarism. Failure to comply with this rule could result in a failing grade and disciplinary procedures.

Penn State University's Definition and Expections: Academic integrity is the pursuit of scholarly activity in an open, honest and responsible manner. Academic integrity is a basic guiding principle for all academic activity at Penn State, and all members of the University community are expected to act in accordance with this principle. Consistent with this expectation, the University's Code of Conduct states that all students should act with personal integrity, respect other students' dignity, rights and property, and help create and maintain an environment in which all can succeed through the fruits of their efforts. Academic integrity includes a commitment not to engage in or tolerate acts of falsification, misrepresentation or deception. Such acts of dishonesty violate the fundamental ethical principles of the University community and compromise the worth of work completed by others.