Welcome to the Course Pack for CMSC 180: Introduction to Parallel Computing, a core required course in the Bachelor of Science in Computer Science curriculum at UPLB. In line with the curriculum guidelines of the Association for Computing Machinery / IEEE Computer Society which recognize the growing importance of parallel and distributed computing in undergraduate education, this course prepares us to think and build systems that compute at scale.

 On this page we will find:

• The learning outcomes for the course

• The main topics and hands-on activities we will engage in

• A collection of recent course guides documenting the semester offerings

• A curated list of references to deepen our understanding

Parallel computing is a vast terrain of ideas, techniques, and systems working together toward faster and more efficient computation. Enumerated below are the general topics that we will explore throughout the semester. Each topic links to its own Topic Pack, which contains the learning objectives, guiding questions, topic outline, lecture handouts, and reference materials that will help us navigate this exciting computational frontier.

Read the introductory handout: Learning to Think in Parallel*

1. Why We Think Faster Together: The Story of Parallel Computing
   Overview and Motivation

2. Connected Minds, Connected Machines: How Parallel Systems Talk and Think
   Parallel Programming Platforms and architectures

3. Speaking the Same Language: How Parallel Programs Coordinate and Communicate
   Parallel Programming Models and Paradigms

4. Chasing Speed: How We Measure, Break, and Redefine Performance
   Performance Metrics and Scalability

5. Breaking Problems Apart: The Art of Designing Parallel Algorithms
   Principles of Parallel Algorithm Design: Foundations

6. Counting the Cost of Speed: Why Every Second (and Processor) Matters
   Principles of Parallel Algorithm Design: Performance and Cost

7. When Processors Talk: The Hidden Conversations of Parallel Programs
   Basic Communication Operations

8. Making It All Work Together: The Midterm Integration of Parallel Thinking
   Midterm Integration

9. Reading the Future: How We Predict Parallel Performance
   Analytical Modeling of Parallel Platforms: Introduction

10. Reading the Numbers: How We Test If Our Models Tell the Truth
    Analytical Modeling of Parallel Platforms: Performance Evaluation

11. Sorting in Sync: How We Teach Computers to Agree on Order
    Parallel Sorting Algorithms: Foundations

12. Beyond the Basics: How Smart Sorting Scales in Parallel Worlds
    Advanced Parallel Sorting Algorithms

13. When Equations Meet Experience: The Art of Parallel Wisdom
    Integrating Analytical and Algorithmic Insights

14. The Big Picture: How It All Connects in Parallel Thinking
    Course Integration

Read the concluding handout: When We Think Together*

Note: Links marked with an asterisk (*) lead to materials accessible only to members of the University community. Please log in with your official University account to view them.

As we work through CMSC 180, we’re not just learning how to write parallel code—we’re cultivating a mindset of scale, coordination, and efficiency. We will discover how algorithms can be transformed to exploit multiple processors, how design decisions impact performance, and how system architecture influences correctness. UPLB hopes that we carry this experience forward into CMSC 280 and beyond, where we will refine these skills into leadership in high performance computing.