ENEE759K/CMSC751: Parallel Algorithmics, Spring 2009
Time and Location
Instructor: Dr. U. Vishkin
- E-mail: email@example.com
- Office hours: T 3:30-5:00 (by appointment) at AVW 2365.
Video recording of all lectures
Grader for Dry Homework
Tutorial, Manual, Software Tools and Other
Homework 1: Exercises 1-5. Due: Feb 26.
Homework 2: Exercises 6-10. Due: March 5.
Homework 3: Exercises 11-16. Due: March 12.
Homework 4: Exercises 17-23. Due: March 26.
Homework 5: Exercises 24-28. Due: April 2.
Homework 6: Exercises 29-33. Due: April 14.
Homework 7: Exercises 34-39. Due: April 28.
Homework 8: Exercises 40-46. Due: May 7.
- Introduction to the theory of parallel algorithms.
The course will highlight parallel algorithmic thinking for obtaining
good speed-ups with respect to serial algorithms.
- Close examination of one of the most exciting applied research questions
facing computer science and engineering:
Will the upcoming ``Billion-transistor-per-chip'' era provide a way for
building a truly parallel computer system on-chip?
The examination has 3 parts: (i) operational (i.e., how will the system
work?), (ii) functional (i.e, for what application it will be useful?), and
(iii) facilitating science and technology (e.g., algorithms,
Of Special Interest
- 6 parallel programming assignments will be given.
- To be run on the Paraleap, the UMD XMT 64-processor computer.
- Basic knowledge and understanding of algorithms and data structures
and computing systems.
- Class notes and research papers will be provided by the instructor.
Please download and print out the first item (104 pages) under
J. JaJa, An Introduction to Parallel Algorithms, Addison Wesley, 1992.
D.E. Culler and J.P. Singh, Parallel Computer Architecture, Morgan Kaufmann,
1999. The following quote appears under the title Potential Breakthroughs:
..."breakthrough may come from architecture" ... "that is,
to truly design a machine that can look to the programmer like a PRAM".
- J.L. Hennessy and D.A. Patterson. Computer Architecture a Quantitative
Approach, 4th Edition. Morgan-Kaufmann, San Francisco, 2007.
Some Core Topics:
- Introduction to Parallel Algorithms:
Performance of Parallel Algorithms, Optimality Notions
- Basic Techniques: Balanced Trees, Pointer Jumping, Divide-and-Conquer,
Partitioning, Pipelining, Accelerated Cascading,
- Trees and Lists: List Ranking, The Euler Tour Techniques,
Tree Connection, Evaluation of Arithmetic Expressions
- Searching, Merging and Sorting
- Graphs: Connected Components, Transitive Closure, Paths Problems
- Strings: Some string matching algorithms
- Introduction to Parallel Processing:
Principles of available multi-processors, thread-level parallel (TLP) systems and instruction-level
parallel (ILP) systems, and Parallel Models
- Studies on limits of ILP extractable from serial code
- Introduction to published expectations from the upcoming
(i) Over 4 orders-of-magnitute of potential improvement over the CPU of the first PC.
(ii) Large on-chip memories will enable high bandwidth and low latency.
(iii) Low overhead hardware/software mechanisms
- Suggestions and possibilities for putting it all together.
Can fine-grained large scale on-chip parallel computing be harnessed
towards faster completion time of a single general-purpose computing
- 10% - Written homework.
- 30% - Programming projects. You must submit all programming projects
to get a grade.
- 25% - 1st mid-term exam. Exam date: April 7, in class.
- 35% - 2nd mid-term exam. Exam date: May 5, in class.
- There will not be a final exam.