CS525: Parallel Computing
Spring 2017.

Ananth Grama, ayg@cs.purdue.edu, 494 6964
Tu/Th 12:00 - 1:15 PM
WANG 2555

Office Hours:
W, 1:30 - 3:00, and by appointment.

TA: Venkata Subramanya Tadigadaga, vtadigad@purdue.edu
Office Hours:
TBA

Course Announcements:

Important announcements relating to the course will be made here. Please look at this area of the web page periodically. Announcements will include (but are not limited to) release of assignments, erratas, and grades.

Course Contents

CS525, 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 . The course consists of four major parts:
  • Parallel Programming: Programming models and language support for programming parallel platforms is discussed. Message passing using MPI, thread-based programming using POSIX threads, and directive-based programming using OpenMP are discussed.
  • Parallel and distributed platforms: This part of the class outlines parallel computing hardware. Topics covered include processor and memory architectures, multicore, SMP, and message passing hardware, interconnection networks, and evaluation metrics for architectures. Cost models for communication are also developed.
  • Parallel and Distributed Algorithms: Starting from design principles for parallel algorithms, this part develops parallel algorithms for a variety of problems. Various metrics for evaluating these algorithms are also discussed.
  • Applications: A variety of parallel applications from diverse domains such as data analysis, graphics and visualization, particle dynamics, and discrete event and direct numerical simulations will be discussed.

Syllabus and Lecture Notes.

Academic Dishonesty Policy:

Please read this policy before starting as I intend on enforcing it strictly.

Grading Policy

Your grade will be determined using the following grading rubric:

Two Midterms: 50%
Five Homeworks: 30%
Final Project: 20%