Math 627 - Introduction to Parallel Computing

Companion Course

Basic Information

• Matthias K. Gobbert, Math/Psyc 416, (410) 455-2404, gobbert@math.umbc.edu,
  office hours: TuTh 03:00-04:00 or by appointment
• Classes: room MP 401, day and time TuTh 04:00-05:15; see the detailed schedule for more information.
• Prerequisites: Math 630, fluency in programming C, C++, or Fortran and proficiency in using the Unix/Linux operating system, or consent of instructor
• Copies of the following books are on reserve in the library.
  • Required textbook: Peter S. Pacheco, Parallel Programming with MPI, Morgan Kaufmann, 1997. Associated webpage: http://nexus.cs.usfca.edu/mpi
  • Recommended book: William Gropp, Ewing Lusk, and Anthony Skjellum, Using MPI: Portable Parallel Programming with the Message-Passing Interface, second edition, MIT Press, 1999. Associated webpage: http://www-unix.mcs.anl.gov/mpi/usingmpi/examples/main.htm
• Grading policy:
  

  Homework and Quizzes	Participation	Class Project
  45%	10%	45%

  • The homework includes the computer assignments that are vital to understanding the course material. A late assignment accrues a deduction of 10% of the possible score for each day late until my receiving it; I reserve the right to exclude any problem from scoring on late homework, for instance, if we discuss it in class. The quizzes will generally be unannounced and brief and will include the use of learning groups assigned by the instructor. For instance, they may be designed to initiate class discussion or to give me feedback on your learning. They may be technical or non-technical in nature.
  • The graded participation component rewards your professional behavior and active involvement in all aspects of the course. Examples of expected professional behavior include attending class regularly, reading assigned material when requested, cooperating with formal issues such as submitting requested material on time, and participating actively in class, specifically in group work. In this course, professional behavior also includes adhering to good user behaviors on the shared computing facilities that you will work on.
  • It is increasingly important at this point in your education to learn how to work on a larger project on your own (with guidance by the instructor) and to present your results in the form of a professional-grade type-set report and a prepared oral class presentation. The class project will include all these components: substantial work on an individual project; a written report (in the form of a technical report); and an oral class presentation.
  Additional details or changes will be announced as necessary. See also general policies and procedures for more information.
• Blackboard is a course management system that allows for posting and communicating among registered participants of a course. To log in, I suggest to go to myUMBC and then use the Blackboard link on the left. Then look for this course under "My Courses". We will actively only use the "Course Documents" area. I will post PDF files of the lectures for each class and possibly appropriate additional notes in this area. I will also use Blackboard to send e-mail to the class, which goes to your UMBC account by default. Therefore, you must either check your UMBC e-mail regularly or have the mail forwarded to an account that you check frequently.

Overview

This course will both introduce the basic aspects of parallel programming and the algorithmic considerations involved in designed scalable parallel numerical methods. The programming will use the Message Passing Interface (MPI), the most common library of parallel communication commands today for any type of parallel machine architecture. We will discuss several application examples in detail that show how parallel computing can be used to solve large application problems in practice.

Registered students in this course will gain access to the resources in the UMBC High Performance Computing Facility (HPCF; www.umbc.edu/hpcf). Installed in Fall 2009, the current machine is the 86-node distributed-memory cluster tara with two quad-core Intel Nehalem processors and 24 GB per node, an InfiniBand interconnect, and 160 TB central storage. This class is intended to familiarize students with this cluster, if you expect to use it for your research in the future. One of the side benefits of this class is to help in the creation of a user community of campus.

Learning Goals

• understand and remember the key ideas, concepts, definitions, and theorems of the subject. Examples include understanding the purpose of parallel computing and why it can work, being aware of potential limitations, and knowing the major types of hardware available. This information will be communicated in class and in the textbook, but also in additional reading. --> This information will be discussed in the lecture as well as in the textbook and other assigned reading.
• have experience writing code for a Linux cluster using MPI in C, C++, and/or Fortran that correctly solves problems in scientific computing. The sample problems are taken from mathematics and your code has to compile without error or warning, run without error, and give mathematically correct results first of all. In addition, it needs to run on a Linux cluster without error and you need to be able to explain its scalability, i.e., why or why not it executes faster on several processors than in serial. We will have problems stated in different ways and from various sources to provide you with exposure to as many issues as possible. --> This is the main purpose of the homework and most learning will take place here.
• have gained proficiency in delivering code written by you to others for compilation and use. This includes the concept of providing a README file that gives instructions how to compile and run the code as well as of providing a sample output file to allow the user to check the results. We will work together in class to discuss best practices to transfer code for homework problems of increasing complexity. --> You will submit your homework code by e-mail to the instructor and it needs to compile and run in parallel for credit; this is complemented by a report that shows and explains your results.
• have some experience how to learn information from a research paper and to discuss it with peers. Group work requiring communication for effective collaboration with peers and supervisors is a vital professional skill, and the development of professional skills is a declared learning goal of this course. --> I will supply some research papers carefully selected for their readability and relevance to the course. Learning from research papers is a crucial skill to develop.
• have experience with independent work and presenting it both in a written report and in an oral presentation. It is vital to gain experience with setting your own goals, estimating a realistic time line, working with peers and supervisors on regular updates and giving and receiving suggestions, submitting and editing a written report to standards of a research paper, and presenting your results in an oral presentation as part of a conference session. --> The class project will cover all of these components, and we will discuss the various steps necessary in class. Reading the research papers above will give you a frame of reference for how the report should look like.

Other Information

• Detailed schedule
• General policies and procedures including grading guidelines
• Guidelines on how to report on computer results

• The recommended literature on my homepage
• A brief introduction to Unix/Linux at UMBC
• My introduction to Matlab at UMBC
• An introduction to LaTeX including a sample file and a template file for project reports.
• UMBC High Performance Computing Facility (HPCF) including general information, list of project, technical reports page, and user information.

UMBC Academic Integrity Policy