JUNOHUB-test/question1/req.md

Problem Statement: MPI Edit Distance Implementation

Objective

Implement the Edit Distance (Needleman-Wunsch global alignment) algorithm using MPI with three different communication strategies and compare their performance.

Requirements

1. Algorithm Implementation

• Implement the Needleman-Wunsch algorithm for global sequence alignment
• Calculate edit distance between two DNA/protein sequences
• Use dynamic programming approach

2. MPI Communication Strategies

Strategy 1: Point-to-Point Communication

• Use MPI_Send and MPI_Recv for data distribution
• Distribute computation across multiple processes
• Collect results using point-to-point communication

Strategy 2: Scatter + Gather Communication

• Use MPI_Scatter to distribute data
• Use MPI_Gather to collect results
• Implement collective communication patterns

Strategy 3: Gather-based Multiple Pair Computation

• Process multiple sequence pairs in parallel
• Use MPI_Gather to collect results from all processes
• Implement load balancing across processes

3. Input/Output Format

Input:

Sequence 1: ACGTAG
Sequence 2: ACTG

Output:

Edit Distance (P2P) = 2, Time = 0.000s
Edit Distance (Scatter) = 2, Time = 0.000s
Edit Distance (Gather) = [2, 3, 3], Time = 0.000s

4. Performance Requirements

• Measure execution time for each strategy
• Support different numbers of MPI processes (2, 4, 8)
• Compare performance across communication strategies

5. Docker Environment

• Containerize the application
• Support both single-container and multi-container execution
• Provide easy setup and execution instructions

Expected Results

• Correct edit distance calculations for all strategies
• Performance comparison showing time differences
• Scalable implementation that works with different process counts
• Clean, readable output matching the specified format