From 502073282bfa50b9aa8a451360d585bc2566acbe Mon Sep 17 00:00:00 2001
From: Kaleb Phipps <kaleb.phipps@kit.edu>
Date: Tue, 3 Dec 2024 13:11:23 +0100
Subject: [PATCH] fix comment

---
 2_psrs_cdist/solutions/A1/cdist_symmetric.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/2_psrs_cdist/solutions/A1/cdist_symmetric.py b/2_psrs_cdist/solutions/A1/cdist_symmetric.py
index 1c60615..af24da8 100644
--- a/2_psrs_cdist/solutions/A1/cdist_symmetric.py
+++ b/2_psrs_cdist/solutions/A1/cdist_symmetric.py
@@ -63,9 +63,10 @@ def dist_symmetric(x: torch.Tensor, y: torch.Tensor, comm: MPI.Comm = MPI.COMM_W
 
         # --- Ring Communication Pattern ---
         # Calculate distances in a "ring" pattern. Each process calculates distances for its local x chunk against its
-        # local y chunk (diagonal calculation). Then, through `size - 1` iterations, each process sends its y chunk to
-        # the next process in the "ring" while receiving a new y chunk from the previous process. This continues until
-        # each process has calculated distances between its x chunk and all chunks of y across all processes.
+        # local y chunk (diagonal calculation). Then, through `(size + 1) // 2` iterations, each process sends its y
+        # chunk to the next process in the "ring" while receiving a new y chunk from the previous process. This
+        # continues until each process has calculated distances between its x chunk and all chunks of y across all
+        # processes.
         x_ = x
         stationary = y
 
@@ -76,7 +77,7 @@ def dist_symmetric(x: torch.Tensor, y: torch.Tensor, comm: MPI.Comm = MPI.COMM_W
         local_distances[:, cols[0]: cols[1]] = d_ij
 
         print(f"Rank [{rank}/{size}]: Start tile-wise ring communication...")
-        # Remaining `(size+1) // 2` iterations: Send rank-local part of y to next process in circular fashion.
+        # Remaining `(size + 1) // 2` iterations: Send rank-local part of y to next process in circular fashion.
         # We can perform less iterations due to the symmetric nature of the metric.
         for iter_idx in range(1, (size + 2) // 2):
             print(f"Rank [{rank}/{size}]: Starting iteration {iter_idx}")
-- 
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