Day 5: Parallel and Distributed Computing

Learning Objectives

• CSN-2.A: For sequential, parallel, and distributed computing: a. Compare problem solutions. b. Determine the efficiency of solutions.
• CSN-2.B: Describe benefits and challenges of parallel and distributed computing.

Essential Questions

• How can tasks be divided across multiple computing devices?
• What are the benefits and challenges of parallel and distributed computing?
• How do we measure the efficiency of different computing approaches?

Materials Needed

• Presentation slides on parallel and distributed computing
• Task cards for parallel processing activity
• Stopwatches or timers
• Worksheet for calculating speedup
• Exit ticket templates

Vocabulary

• Sequential computing
• Parallel computing
• Distributed computing
• Speedup
• Efficiency
• Task decomposition
• Synchronization
• Scalability
• Amdahl's Law
• Overhead

Procedure (50 minutes)

Opening (8 minutes)

1. Review and Connection (3 minutes)

   • Review network concepts from previous lessons
   • Connect to today's focus on how networks enable parallel and distributed computing

2. Warm-up Activity (5 minutes)

   • Present a task that would take a long time for one person (e.g., sorting a large deck of cards)
   • Ask students: "How could we make this faster by involving more people?"
   • Discuss strategies for dividing the work
   • Introduce the concept of parallel processing

Main Activities (32 minutes)

3. Lecture: Parallel and Distributed Computing Concepts (12 minutes)

   • Define the three computational models:
     • Sequential computing: Operations performed one at a time in order
     • Parallel computing: Program broken into smaller operations performed simultaneously
     • Distributed computing: Multiple devices used to run a program
   • Explain key concepts:
     • Task decomposition: Breaking problems into smaller tasks
     • Speedup: Sequential time divided by parallel time
     • Amdahl's Law: Speedup limited by sequential portion
     • Overhead: Additional time required for coordination
   • Discuss real-world applications:
     • Scientific simulations
     • Weather forecasting
     • Video rendering
     • Big data processing
     • Cryptocurrency mining
   • Explain challenges of parallel/distributed computing:
     • Coordination overhead
     • Synchronization issues
     • Communication costs
     • Programming complexity

4. Demonstration: How Tasks Can Be Split Across Systems (8 minutes)

   • Show examples of problems that can be parallelized:
     • Searching through data
     • Matrix operations
     • Image processing
     • Simulation calculations
   • Demonstrate how to calculate speedup:
     • Speedup = Sequential time / Parallel time
   • Show how adding more processors affects speedup
   • Illustrate Amdahl's Law with examples
   • Discuss the limits of parallelization

5. Activity: Modeling Parallel Problem-Solving (12 minutes)

   • Divide class into groups of 4-5 students
   • Assign each group a task that can be parallelized (e.g., sorting numbers, counting words, finding specific items)
   • Have groups perform the task in two ways:
     • Sequential: One person does the entire task
     • Parallel: Task is divided among group members
   • Groups should time both approaches
   • Have groups calculate the speedup achieved
   • Discuss factors that affected the speedup:
     • Overhead of dividing the work
     • Communication between group members
     • Portions that couldn't be parallelized

Closing (10 minutes)

6. Discussion: Efficiency Gains and Challenges (5 minutes)

   • Lead a discussion on what students observed in the activity
   • Ask groups to share their speedup results
   • Discuss why the speedup wasn't perfectly proportional to the number of people
   • Connect to real-world parallel and distributed systems
   • Address any misconceptions about parallelization

7. Exit Ticket: Parallel Processing Design (5 minutes)

   • Present students with a problem scenario
   • Students design a solution that uses parallel processing
   • Students explain how they would divide the task
   • Students identify potential challenges in their approach
   • Collect responses before students leave

Assessment

• Formative: Quality of parallel problem-solving activity
• Exit Ticket: Appropriateness of parallel processing design

Differentiation

For Advanced Students

• Ask them to analyze more complex parallelization scenarios
• Have them calculate theoretical vs. actual speedup
• Challenge them to identify and resolve synchronization issues

For Struggling Students

• Focus on simpler parallelization examples
• Provide more structured templates for the activity
• Use more concrete analogies and visual aids

Homework/Extension

• Research a real-world application of parallel or distributed computing
• Calculate theoretical speedup for different scenarios
• Create an infographic explaining parallel vs. distributed computing

Teacher Notes

• Use everyday analogies to help students understand parallel processing (e.g., multiple checkout lines at a store)
• Be prepared to address questions about specific parallel computing technologies
• Make connections to students' experiences with slow-running applications
• Consider demonstrating parallel processing with a simple program if time allows
• Emphasize that understanding these concepts helps with designing efficient solutions