CS52500 - Parallel ComputingSpring 2017
Days/Time: TTh / 12:00-1:15 pm
Credit Hours: 3
Parallel Computing deals with emerging trends in the use of large scale computing platforms ranging from desktop multicore processors, tightly coupled SMPs, message passing platforms, and state-of-the-art virtualized cloud computing environments.
Parallel computing for science and engineering applications: parallel programming and performance evaluation, parallel libraries and problem-solving environments, models of parallel computing and run-time support systems, and selected applications. Spring 2014 Syllabus
Part 1: Parallel and distributed computing architectures; shared memory processors; distributed memory processors; multicore processors. Part 2: Parallel Programming; programming models; OpenMP for shared memory programs; MPI library for message passing; thread based programming. Part 3: Parallel algorithms; sorting; matrix-vector multiplication; matrix computations; graph algorithms. Part 4: Applications of these algorithms from various domains will be discussed.
A bachelor degree in computer science or an equivalent field. Students not in the Computer Science master's program should seek department permission to register.
Approx. 6 assignments
1 Midterm and 1 Final
**Updated Dec. 2, 2013** Introduction to Parallel Computing - Ananth Grama, Anshul Gupta, George Karypis and Vipin Kumar; 2nd ed., Addison Wesley, ISBN: 0-201-64865-2, 2003. Disclaimer: Please visit the Listing of Textbooks by College or School for the most up-to-date textbook information.
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