ADD Second Question So,l.

reduceTreee.py

+from mpi4py import MPI
+import numpy as np
+import time 
+
+
+# Perform tree-based reduction on local_data using addition as the operation.
+def reduce_tree(local_data, rank, size, comm):
+
+    num_processes = size
+    my_rank = rank
+
+    print(f"[+] Process {my_rank} starting with local data: {local_data}")
+
+    step = 1
+    while step < num_processes:
+
+        # XOR operation to find partner
+        partner = my_rank ^ step  
+        
+        if partner < num_processes:
+            
+        
+            # Exchange data with the partner
+            recv_data = np.zeros_like(local_data)
+            comm.Sendrecv(local_data, dest=partner, recvbuf=recv_data, source=partner)
+            print(f"[+] Process {my_rank} received data from process {partner}: {recv_data}")
+            
+            # Combine received data with the local data
+            local_data += recv_data
+            
+            print(f"[+] Process {my_rank} updated local data: {local_data}")
+
+        
+        # Move to the next step 
+        step *= 2
+    
+    if my_rank == 0:
+        return local_data
+    else:
+        return None
+
+def main():
+    comm = MPI.COMM_WORLD
+    rank = comm.Get_rank()
+    size = comm.Get_size()
+
+    # Initialize the local data for each process
+    local_data = np.array([rank + 1], dtype=int)
+
+    # Start timer
+    start_time = time.time()
+
+    # Perform the tree based reduce operation
+    result = reduce_tree(local_data, rank, size, comm)
+    
+    # end timer
+    end_time = time.time()
+
+    # Elapsed time
+    elapsed_time = end_time - start_time
+
+    if rank == 0:
+        print(f"[+] Final result after reduction: {result}")
+        print(f"[+] Time taken for the reduction: {elapsed_time:.6f} seconds")
+
+# Run the main function
+if __name__ == "__main__":
+    main()