Yanqing Ji

CPEN435 - Parallel and Cloud Computing

Course Description:

This course is designed to provide junior or senior students in electrical/computer engineering, computer science, and other engineering with fundamentals in parallel and cloud computing. Students will gain hands-on programming experience solving compute and storage-intensive problems in a variety of disciplines on Amazon’s cloud computing platform.

Prerequisites: CPEN 231 and CPSC 122.

Course Instructor Information:

Name: Yanqing Ji, Professor of Electrical & Computer Engineering

Office: Herak Center for Engineering Room 247

Office Phone: (509) 313 - 3529

Email: ji@gonzaga.edu

Office Hours: 11:00am–12:00pm (M, W & F); or stop by.

Textbooks:

1. Ananth Grama, Anshul Gupta, George Karypis and Vipin Kumar, Introduction to Parallel Computing, 2^nd Edition, Addison Wesley, 2003. (ISBN: 0-201064865-2)

2. Rajkumar Buyya, Christian Vecchiola, S. Thamarai Selvi, Matering Cloud Computing: Foundations and Applications Programming, 1^st Edition, Morgan Kaufmann, 2013 (ISBN-13: 978-0124114548)

Specific Topics:

· Parallel programming platforms

· Principles of parallel algorithm design

· Analytical modeling of parallel programs

· Programming using the message-passing paradigm (MPI)

· Programming shared address space platforms (POSIX Thread)

· Introduction to cloud computing

· Amazon web services

· Big data

· Hadoop platform

· MapReduce programming paradigm

· Other advanced topics.

Quick Resources:

1. Ian Foster, Designing and Building Parallel Programs, Available at http://www.mcs.anl.gov/~itf/dbpp/

2. The Message Passing Interface (MPI): http://www-unix.mcs.anl.gov/mpi/tutorial/

3. POSIX thread (pthread) tutorials:

a. http://www.yolinux.com/TUTORIALS/LinuxTutorialPosixThreads.html

b. https://computing.llnl.gov/tutorials/pthreads/

4. Amazon web services: http://aws.amazon.com/

5. Hadoop: https://hadoop.apache.org/

6. MapReduce: http://lintool.github.io/MapReduceAlgorithms/MapReduce-book-final.pdf

7. More tutorial links

https://computing.llnl.gov/tutorials/parallel_comp/

https://computing.llnl.gov/tutorials/mpi/

https://computing.llnl.gov/tutorials/mpi_performance/

Grade Point Distribution:

Homework & labs: 20%

Project: 15%

Exams (highest 2 out of 3): 40%

Final: 25%

Grading Scale:

94-100 A

90-93 A-

86-89 B+

82-85 B

78-81 B-

74-77 C+

70-73 C

66-69 C-

62-65 D+

58-61 D

0-57 F

Makeup Exam and Homework Policy: No makeup exams. Late submission of homework is not accepted except unavoidable conditions (e.g., sickness).

Class Attendance Policy: Students are referred to read the Gonzaga University Undergraduate Catalogue regarding the class attendance policy (page 38) – “… the maximum allowable absence is two class hours (100 minutes) for each class credit, … the grade given for excessive absences is a “V”, which has the same effect as “F” (Fail) and is counted in the GPA”.