MCS 706 – High-Performance Computing and Parallel Processing

Wishlist Share
Share Course
Page Link
Share On Social Media

About Course

Course Description:

This core course examines the architecture, algorithms, and programming models for high-performance computing. Topics include parallel algorithms, distributed memory systems, and applications in scientific simulations and data-intensive computing. Students will gain hands-on experience with parallel programming techniques and explore the challenges of developing scalable and efficient solutions for high-performance computing environments. 

Course Objectives:

  • Develop a deep understanding of high-performance computing (HPC) architectures and programming models.
  • Learn to design and implement parallel algorithms for distributed and shared memory systems.
  • Explore the application of HPC techniques in scientific simulations, data-intensive computing, and other domains.
  • Gain practical experience in parallel programming using tools such as MPI and CUDA.
  • Prepare for advanced research and development in high-performance and parallel computing.
Show More

Course Content

Week 1: Introduction to High-Performance Computing

  • LO1: Define high-performance computing and explain its significance in modern computational science
  • LO2: Describe key concepts such as parallelism, scalability, and performance metrics in HPC systems
  • LO3: Analyze the role of HPC in solving complex scientific and data-intensive problems
  • Multiple-Choice Questions
  • True/False Questions
  • Scenario-Based Multiple-Choice Questions
  • Key Terms & Concepts Questions
  • Short Answer Questions
  • Written Assignment
  • Presentation Task
  • Role-Playing Activity
  • Peer Review Task
  • Exercises and Activities Adaptation

Week 2: Parallel Computing Architectures

Week 3: Parallel Programming Models

Week 4: Parallel Algorithms and Performance Analysis

Week 5: Message Passing Interface (MPI)

Week 6: Shared Memory Programming with OpenMP

Week 7: GPU Computing and Accelerators

Week 8: Midterm Test

Week 9: Distributed Computing Systems

Week 10: HPC Storage Systems and Data Management

Week 11: Fault Tolerance and Reliability in HPC

Week 12: HPC Applications in Scientific Computing

Week 13: Energy Efficiency in High-Performance Computing

Week 14: Emerging Trends in HPC

Week 15: Course Review

Week 16: Final Test

Want to receive push notifications for all major on-site activities?