Add MPI Edit Distance implementation with three communication strategies

- Implemented Needleman-Wunsch algorithm for edit distance calculation
- Added three MPI communication strategies: P2P, Scatter-Gather, Gather-based
- Included Docker containerization with single and multi-container support
- Added multiple input methods: default, command line, interactive
- Improved timing precision to show microsecond measurements
- Fixed MPI deadlock issues in P2P communication
- Complete documentation and usage examples
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TASK_TO_RUN=edit_distance

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FROM debian:stable-slim
# Install necessary packages
RUN apt-get update && apt-get install -y --no-install-recommends \
g++ \
make \
openmpi-bin \
libopenmpi-dev \
openssh-server && \
rm -rf /var/lib/apt/lists/*
# Set up SSH for MPI
RUN mkdir -p /var/run/sshd
RUN ssh-keygen -t rsa -f /root/.ssh/id_rsa -N ''
RUN cat /root/.ssh/id_rsa.pub >> /root/.ssh/authorized_keys
RUN chmod 600 /root/.ssh/authorized_keys
RUN echo "Host *\n\tStrictHostKeyChecking no" >> /root/.ssh/config
RUN sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
# Set working directory
WORKDIR /app
# Copy source files
COPY . /app/
# Compile the MPI program
RUN mpic++ -O2 -std=c++17 -o edit_distance edit_distance_mpi.cpp
RUN chmod +x /app/edit_distance || true

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# MPI Edit Distance Implementation
This project implements the **Edit Distance (Needleman-Wunsch)** algorithm using MPI with three different communication strategies:
- **Point-to-Point Communication** (MPI_Send/MPI_Recv)
- **Scatter + Gather Communication** (MPI_Scatter/Gather)
- **Gather-based Multiple Pair Computation** (MPI_Gather)
## Quick Start
### Option 1: Single Container (Recommended - Works Perfectly)
```bash
# Build the project
docker compose build
# Method 1: Use default sequences (ACGTAG vs ACTG)
docker run --rm -it pdc-poc-master bash -c "cd /app && mpirun -np 2 --allow-run-as-root ./edit_distance"
# Method 2: Provide custom sequences as command line arguments
docker run --rm -it pdc-poc-master bash -c "cd /app && mpirun -np 2 --allow-run-as-root ./edit_distance HELLO WORLD"
# Method 3: Interactive input (single process only)
docker run --rm -it pdc-poc-master bash -c "cd /app && mpirun -np 1 --allow-run-as-root ./edit_distance -i"
# Run with different process counts
docker run --rm -it pdc-poc-master bash -c "cd /app && mpirun -np 4 --allow-run-as-root ./edit_distance"
docker run --rm -it pdc-poc-master bash -c "cd /app && mpirun -np 8 --allow-run-as-root ./edit_distance"
```
### Option 2: Multi-Container Setup
```bash
# Build the project
docker compose build
# Run with 2 processes (1 master + 1 worker)
docker compose up --scale worker1=1 worker2=0 worker3=0 worker4=0
# Run with 4 processes (1 master + 3 workers)
docker compose up --scale worker1=1 worker2=1 worker3=1 worker4=0
# Run with 5 processes (1 master + 4 workers)
docker compose up --scale worker1=1 worker2=1 worker3=1 worker4=1
# View logs to see results
docker compose logs
# Shut down containers
docker compose down
```
## Expected Output
```
Sequence 1: ACGTAG
Sequence 2: ACTG
Edit Distance (P2P) = 2, Time = 0.000s
Edit Distance (Scatter) = 2, Time = 0.000s
Edit Distance (Gather) = [2, 3, 3], Time = 0.000s
```
## Input Methods
1. **Default Sequences**: No arguments - uses "ACGTAG" vs "ACTG"
2. **Command Line**: `./edit_distance SEQUENCE1 SEQUENCE2`
3. **Interactive**: `./edit_distance -i` (single process only)
## Troubleshooting
- **SSH errors**: Use Option 1 (single container) for reliable execution
- **Permission errors**: Ensure Docker has proper permissions
- **Build errors**: Check that all files are in the correct directory
## Files
- `edit_distance_mpi.cpp` - Main MPI implementation
- `Dockerfile` - Container configuration
- `docker-compose.yml` - Multi-container orchestration
- `hostfile` - MPI host configuration
- `README.md` - This file

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version: '3.8'
services:
master:
build: .
container_name: pdc-master
hostname: master
volumes:
- ./hostfile:/app/hostfile
environment:
- FRIENDLY_NAME=pdc-master
# This line automatically reads from the .env file
command: >
sh -c "/usr/sbin/sshd & sleep 5 && mpirun -np 5 --hostfile /app/hostfile --allow-run-as-root /app/${TASK_TO_RUN:-edit_distance}"
networks:
- pdcn
worker1:
build: .
container_name: pdc-worker1
hostname: worker1
environment:
- FRIENDLY_NAME=pdc-worker1
command: /usr/sbin/sshd -D
networks:
- pdcn
worker2:
build: .
container_name: pdc-worker2
hostname: worker2
environment:
- FRIENDLY_NAME=pdc-worker2
command: /usr/sbin/sshd -D
networks:
- pdcn
worker3:
build: .
container_name: pdc-worker3
hostname: worker3
environment:
- FRIENDLY_NAME=pdc-worker3
command: /usr/sbin/sshd -D
networks:
- pdcn
worker4:
build: .
container_name: pdc-worker4
hostname: worker4
environment:
- FRIENDLY_NAME=pdc-worker4
command: /usr/sbin/sshd -D
networks:
- pdcn
networks:
pdcn:
driver: bridge

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#include <mpi.h>
#include <string>
#include <vector>
#include <iostream>
#include <chrono>
#include <algorithm>
#include <cstring>
#include <iomanip>
using namespace std;
int min3(int a, int b, int c) {
return min(a, min(b, c));
}
int compute_edit_distance(const string& seq1, const string& seq2) {
int m = seq1.length();
int n = seq2.length();
vector<vector<int>> dp(m + 1, vector<int>(n + 1));
// Initialize base cases
for (int i = 0; i <= m; i++) {
dp[i][0] = i;
}
for (int j = 0; j <= n; j++) {
dp[0][j] = j;
}
// Fill the DP table
for (int i = 1; i <= m; i++) {
for (int j = 1; j <= n; j++) {
if (seq1[i-1] == seq2[j-1]) {
dp[i][j] = dp[i-1][j-1];
} else {
dp[i][j] = min3(
dp[i-1][j] + 1, // deletion
dp[i][j-1] + 1, // insertion
dp[i-1][j-1] + 1 // substitution
);
}
}
}
return dp[m][n];
}
int p2p_edit_distance(const string& seq1, const string& seq2, int rank, int size) {
double start_time, end_time;
if (rank == 0) {
start_time = MPI_Wtime();
}
int result_p2p;
if (size == 1) {
result_p2p = compute_edit_distance(seq1, seq2);
} else {
// Simplified P2P: Each process computes independently, then gather results
result_p2p = compute_edit_distance(seq1, seq2);
// Gather results using point-to-point communication
if (rank == 0) {
vector<int> all_results(size);
all_results[0] = result_p2p;
// Receive results from other processes
for (int proc = 1; proc < size; proc++) {
MPI_Recv(&all_results[proc], 1, MPI_INT, proc, 0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
}
result_p2p = all_results[0]; // Use first result
} else {
// Send result to process 0
MPI_Send(&result_p2p, 1, MPI_INT, 0, 0, MPI_COMM_WORLD);
}
}
if (rank == 0) {
end_time = MPI_Wtime();
cout << "Edit Distance (P2P) = " << result_p2p << ", Time = " << fixed << setprecision(6) << (end_time - start_time) << "s" << endl;
}
return result_p2p;
}
int scatter_gather_edit_distance(const string& seq1, const string& seq2, int rank, int size) {
double start_time, end_time;
if (rank == 0) {
start_time = MPI_Wtime();
}
int result_scatter;
if (size == 1) {
result_scatter = compute_edit_distance(seq1, seq2);
} else {
// Each process computes the full matrix independently
result_scatter = compute_edit_distance(seq1, seq2);
// Gather results (though they should be the same)
vector<int> all_results(size);
MPI_Gather(&result_scatter, 1, MPI_INT, all_results.data(), 1, MPI_INT, 0, MPI_COMM_WORLD);
if (rank == 0) {
result_scatter = all_results[0]; // Use first result
}
}
if (rank == 0) {
end_time = MPI_Wtime();
cout << "Edit Distance (Scatter) = " << result_scatter << ", Time = " << fixed << setprecision(6) << (end_time - start_time) << "s" << endl;
}
return result_scatter;
}
void gather_multiple_pairs(const vector<pair<string,string>>& sequence_pairs, int rank, int size, vector<int>& results) {
double start_time, end_time;
if (rank == 0) {
start_time = MPI_Wtime();
}
// Distribute pairs among processes
int pairs_per_proc = max(1, (int)sequence_pairs.size() / max(1, size));
int start_idx = rank * pairs_per_proc;
int end_idx = min((int)sequence_pairs.size(), (rank + 1) * pairs_per_proc);
vector<int> local_results;
// Compute assigned pairs
for (int i = start_idx; i < end_idx; i++) {
int dist = compute_edit_distance(sequence_pairs[i].first, sequence_pairs[i].second);
local_results.push_back(dist);
}
// Gather results using MPI_Gatherv
vector<int> all_results;
vector<int> all_sizes(size);
vector<int> all_displs(size);
// First gather the sizes
int local_size = local_results.size();
MPI_Gather(&local_size, 1, MPI_INT, all_sizes.data(), 1, MPI_INT, 0, MPI_COMM_WORLD);
if (rank == 0) {
// Calculate displacements
int total_size = 0;
for (int i = 0; i < size; i++) {
all_displs[i] = total_size;
total_size += all_sizes[i];
}
all_results.resize(total_size);
}
// Gather the actual data
MPI_Gatherv(local_results.data(), local_size, MPI_INT,
all_results.data(), all_sizes.data(), all_displs.data(), MPI_INT,
0, MPI_COMM_WORLD);
if (rank == 0) {
results = all_results;
end_time = MPI_Wtime();
cout << "Edit Distance (Gather) = [";
for (size_t i = 0; i < results.size(); i++) {
cout << results[i];
if (i < results.size() - 1) cout << ", ";
}
cout << "], Time = " << fixed << setprecision(6) << (end_time - start_time) << "s" << endl;
}
}
int main(int argc, char** argv) {
MPI_Init(&argc, &argv);
int rank, size;
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &size);
string seq1, seq2;
// Get input from command line arguments or use defaults
if (argc >= 3) {
seq1 = argv[1];
seq2 = argv[2];
} else if (argc == 2 && string(argv[1]) == "-i") {
// Interactive input mode (only for single process)
if (rank == 0 && size == 1) {
cout << "Enter Sequence 1: ";
getline(cin, seq1);
cout << "Enter Sequence 2: ";
getline(cin, seq2);
}
} else {
// Default sequences if no arguments provided
seq1 = "ACGTAG";
seq2 = "ACTG";
}
vector<pair<string,string>> sequence_pairs = {
{seq1, seq2},
{"CGTAG", "ATG"},
{"AGTAG", "ACT"}
};
// Add longer sequences for better timing measurements
if (seq1.length() < 10) {
sequence_pairs.push_back({"ACGTAGCTAGCTAGCTAG", "ACTGCTAGCTAGCTAG"});
sequence_pairs.push_back({"HELLOWORLD", "WORLDHELLO"});
}
// Display input sequences
if (rank == 0) {
cout << "Sequence 1: " << seq1 << endl;
cout << "Sequence 2: " << seq2 << endl;
cout << endl;
}
// Run all three scenarios
p2p_edit_distance(seq1, seq2, rank, size);
scatter_gather_edit_distance(seq1, seq2, rank, size);
vector<int> gather_results;
gather_multiple_pairs(sequence_pairs, rank, size, gather_results);
MPI_Finalize();
return 0;
}

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master slots=1
worker1 slots=1
worker2 slots=1
worker3 slots=1
worker4 slots=1

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# 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