Syllabus
Instructor: Dan Watson
Office: Main 402b
Communications: Phone: 797-2440, E-mail: Dan.Watson@usu.edu
Office Hours: MWF 11-12
Prerequisite: Permission of instructor.
Course Page: All assignments and other information dealing with the course are posted on the course page (http://www.cs.usu.edu/~watson/cs7550).
Text: V. Kumar, et al. Introduction to Parallel Computing: Design and Analysis of Algorithms. Benjamin Cummins, 1994. Selected portions as available on electronic reserve. Additional readings and texts as needed.
Course Objectives:
Explores the design of large-scale parallel processing systems generally suited for multi-processor implementation. Emphasizes interconnections patterns among the processing elements in parallel processors. Prerequisite: permission of instructor. (3 credits)Programming: This course has a heavy programming component. Students should be familiar with unix, vi, c/c++, qsub, and mpi. There will be 12 programming projects throughout the semester. It is assumed that the student taking a PhD-level class will be able to learn background information quickly and independently.
Exams: There will be 5 exams throughout the semester, covering reading and practical information gained through the programming projects.
Project: There will be an independent coding project on parallel applications decided on and performed by the student, due at the end of the semester, presented in an oral defense format.
Grading:
| Homework (12 at 20 points each) |
240 |
| Exams (5 at 40 points each |
200 |
| Independent Project (1 at 40 points) |
40 |
| Total | 480 |
You may be given an B if either your overall average is below 90%.
You may be given an C if either your overall average is below 80%.
You may be given an D if either your overall average is below 70%.
You may be given an F if either your overall average is below 50%.
Current scores can be
checked at any time by going to the Eagle system. Special
announcements about the class are e-mailed to you, so it is suggested that you
check your e-mail daily.
Course Obejectives:
| In this course, students will learn about: |
| Interconnection Models |
| Parallel Machine Models |
| Single-Stage Network Comparisons |
| Partitioning Single-Stage Networks |
| Multistage Networks |
| Shuffle Exchange Networks |
| Recursive Networks |
| Fault-Tolerant Networks |
| Data-Manipulator Networks |
| Flat Neighborhood Networks |
Late Work: I do not accept late work.
All assignments are due at 11:59:59 p.m. on the date specified.
Cheating: This course adheres to the departmental cheating policy.
Incompletes: According to university policy, incompletes are not to be given for poor performance. There will be no incompletes given except for conditions beyond the student's control. Such conditions have to have written documentation. The term "conditions beyond the student's control" includes (1) incapacitating illnesses that prevent a student from attending classes for a period of at least two weeks; (2) a death in the immediate family; (3) financial responsibilities requiring a student to alter course schedule to secure employment; (4) change in work schedule as required by an employer; or (5) other emergencies of this nature. When an incomplete is given, it is anticipated that the remaining work will be finished within two or three weeks. If the course must be retaken to make up the work, an incomplete is not appropriate. There are provisions in case of emergency to permit a student to withdraw (grade of W) from a course after the regular drop period when it is not feasible to give an I.
ADA Statement: If a student has a disability that will likely require some accommodation by the instructor, the student must contact the instructor and document the disability through the Disability Resource Center, preferably during the first week of the course. Any requests for special considerations relating to attendance, pedagogy, taking of examinations, etc. must be discussed with and approved by the instructor. In cooperation with the Disability Resource Center, course materials can be provided in alternative formats, e.g. large print, audio, diskette, or Braille.
Class Fees: There is no class fee associated with this class.
Late Adds: The last day to add this class, including audits, is September 20th.
Drop Date: The last day to drop
this class, without a notation, is September 20th.