Added support for topographical ordering of hostnames in mpi run, made the slurm sbatch scripts more generic and added convenience

scripts to convert nccl output to excel

Author: harishvs

.gitignore

@@ -153,3 +153,8 @@ wandb/
 
 # Enroot container image
 *.sqsh
+
+*.csv
+submitted_jobs*.txt
+topo_sorted_hostnames.txt
+micro-benchmarks/nccl-tests/slurm/topology-aware-nccl-tests/hostnames.txt

micro-benchmarks/nccl-tests/README.md

@@ -128,6 +128,9 @@ You can skip this part if you use pre-built image on `public.ecr.aws/hpc-cloud/n
 
 ## 2. Running the NCCL Tests
 
+Note: For topology aware NCCL tests, with features like export to csv, 
+passing in a topologically sorted hostfile to mpirun, look in slurm/topology-aware-nccl-tests
+
 ### Slurm with container
 
 Copy the file `slurm/nccl-tests.sbatch` or its content on your cluster then submit a preprocessing jobs with the command below:
@@ -317,4 +320,4 @@ The formula defines the maximum theoretical bandwidth that can be achieved on di
 * `n` : number of ranks participating to the operation. (similar to nranks for Algbw and Busbw)
 * `t` : time to complete the operation. (similar to sec for Algbw and Busbw)
 * `S` : number of elements being communicated (similar to count for Algbw and Busbw)
-* `B` : theoretical peak bandwidth.
+* `B` : theoretical peak bandwidth.

micro-benchmarks/nccl-tests/nccl_to_csv.py

@@ -0,0 +1,172 @@
+#!/usr/bin/env python3
+"""
+Complete NCCL to CSV Converter
+Parses NCCL output and creates CSV files with results and summary
+"""
+
+import re
+import csv
+import sys
+from pathlib import Path
+
+def parse_nccl_output(file_path):
+    """Parse NCCL test output and extract performance data"""
+    
+    data = []
+    avg_bandwidth = None
+    
+    # Pattern to match NCCL performance lines (flexible for different test types)
+    # Handles both allreduce/reducescatter format and allgather/alltoall format
+    # Note: alltoall uses N/A for in-place errors, so we handle that case
+    pattern = r'^\s*(\d+)\s+(\d+)\s+(float|double|int|half)\s+(sum|prod|max|min|none)\s+(-?\d+)\s+(\d+\.?\d*)\s+(\d+\.?\d*)\s+(\d+\.?\d*)\s+(\d+|N/A)\s+(\d+\.?\d*)\s+(\d+\.?\d*)\s+(\d+\.?\d*)\s+(\d+|N/A)'
+    
+    # Pattern to match average bandwidth line
+    avg_pattern = r'# Avg bus bandwidth\s*:\s*(\d+\.?\d*)'
+    
+    try:
+        with open(file_path, 'r') as f:
+            for line_num, line in enumerate(f, 1):
+                # Check for performance data
+                match = re.match(pattern, line.strip())
+                if match:
+                    size_bytes = int(match.group(1))
+                    count = int(match.group(2))
+                    data_type = match.group(3)
+                    operation = match.group(4)
+                    root = int(match.group(5))
+                    
+                    # Out-of-place metrics
+                    oop_time_us = float(match.group(6))
+                    oop_algbw = float(match.group(7))
+                    oop_busbw = float(match.group(8))
+                    oop_error = 0 if match.group(9) == 'N/A' else int(match.group(9))
+                    
+                    # In-place metrics  
+                    ip_time_us = float(match.group(10))
+                    ip_algbw = float(match.group(11))
+                    ip_busbw = float(match.group(12))
+                    ip_error = 0 if match.group(13) == 'N/A' else int(match.group(13))
+                    
+                    data.append({
+                        'Size_Bytes': size_bytes,
+                        'Size_KB': round(size_bytes / 1024, 2),
+                        'Size_MB': round(size_bytes / (1024 * 1024), 2),
+                        'Count': count,
+                        'Data_Type': data_type,
+                        'Operation': operation,
+                        'Root': root,
+                        'OOP_Time_us': oop_time_us,
+                        'OOP_AlgBW_GBps': oop_algbw,
+                        'OOP_BusBW_GBps': oop_busbw,
+                        'OOP_Errors': oop_error,
+                        'IP_Time_us': ip_time_us,
+                        'IP_AlgBW_GBps': ip_algbw,
+                        'IP_BusBW_GBps': ip_busbw,
+                        'IP_Errors': ip_error
+                    })
+                
+                # Check for average bandwidth
+                avg_match = re.search(avg_pattern, line)
+                if avg_match:
+                    avg_bandwidth = float(avg_match.group(1))
+    
+    except FileNotFoundError:
+        print(f"Error: File {file_path} not found")
+        return None, None
+    except Exception as e:
+        print(f"Error reading file: {e}")
+        return None, None
+    
+    if not data:
+        print("No NCCL performance data found in the file")
+        return None, None
+        
+    return data, avg_bandwidth
+
+def write_csv(data, filename):
+    """Write data to CSV file"""
+    
+    if not data:
+        return False
+    
+    try:
+        with open(filename, 'w', newline='') as csvfile:
+            fieldnames = list(data[0].keys())
+            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+            writer.writeheader()
+            writer.writerows(data)
+        return True
+    except Exception as e:
+        print(f"Error writing CSV file {filename}: {e}")
+        return False
+
+def create_summary_data(data, avg_bandwidth=None):
+    """Create summary statistics from performance data"""
+    
+    if not data:
+        return None
+        
+    oop_busbw_values = [row['OOP_BusBW_GBps'] for row in data]
+    ip_busbw_values = [row['IP_BusBW_GBps'] for row in data]
+    
+    summary_data = [
+        {'Metric': 'Total Test Points', 'Value': len(data)},
+        {'Metric': 'Min Message Size (Bytes)', 'Value': min(row['Size_Bytes'] for row in data)},
+        {'Metric': 'Max Message Size (Bytes)', 'Value': max(row['Size_Bytes'] for row in data)},
+        {'Metric': 'Peak OOP Bus BW (GB/s)', 'Value': round(max(oop_busbw_values), 2)},
+        {'Metric': 'Peak IP Bus BW (GB/s)', 'Value': round(max(ip_busbw_values), 2)},
+        {'Metric': 'Avg OOP Bus BW (GB/s)', 'Value': round(sum(oop_busbw_values) / len(oop_busbw_values), 2)},
+        {'Metric': 'Avg IP Bus BW (GB/s)', 'Value': round(sum(ip_busbw_values) / len(ip_busbw_values), 2)},
+        {'Metric': 'Total Errors', 'Value': sum(row['OOP_Errors'] + row['IP_Errors'] for row in data)}
+    ]
+    
+    if avg_bandwidth is not None:
+        summary_data.append({'Metric': 'NCCL Reported Avg Bus BW (GB/s)', 'Value': avg_bandwidth})
+    
+    return summary_data
+
+def main():
+    if len(sys.argv) != 2:
+        print("Usage: python nccl_to_excel.py <nccl_output_file>")
+        print("Example: python nccl_to_excel.py nccl-tests-container_3480.out")
+        sys.exit(1)
+    
+    input_file = sys.argv[1]
+    base_name = Path(input_file).stem
+    
+    print(f"Parsing NCCL output from: {input_file}")
+    
+    # Parse the NCCL output
+    data, avg_bandwidth = parse_nccl_output(input_file)
+    
+    if data is None:
+        sys.exit(1)
+    
+    print(f"Found {len(data)} performance data points")
+    if avg_bandwidth:
+        print(f"Average bus bandwidth: {avg_bandwidth} GB/s")
+    
+    # Create main results CSV file
+    results_file = f"{base_name}_results.csv"
+    if write_csv(data, results_file):
+        print(f"Results exported to: {results_file}")
+    else:
+        print("Error writing results file")
+        sys.exit(1)
+    
+    # Create summary CSV file
+    summary_data = create_summary_data(data, avg_bandwidth)
+    if summary_data:
+        summary_file = f"{base_name}_summary.csv"
+        if write_csv(summary_data, summary_file):
+            print(f"Summary exported to: {summary_file}")
+        else:
+            print("Error writing summary file")
+    
+    print("\nFiles created:")
+    print(f"- {results_file} (detailed performance data)")
+    print(f"- {summary_file} (summary statistics)")
+    print("\nYou can open these CSV files in Excel, LibreOffice Calc, or any spreadsheet application")
+
+if __name__ == "__main__":
+    main()