diff --git a/dsv4/kernels/attention/fmha.py b/dsv4/kernels/attention/fmha.py
index 44178667..f42693d4 100644
--- a/dsv4/kernels/attention/fmha.py
+++ b/dsv4/kernels/attention/fmha.py
@@ -505,16 +505,13 @@ class FmhaKernel:
             # Compute LSE: lse = ln(row_sum) + row_max * ln(2)
             # Only when emitting un-normalized output (D5a path).
             # When normalize=True, LSE is not needed (in-kernel normalization).
-            # Each thread writes its row's LSE. With 128 softmax threads and 128 rows,
-            # each thread (sfw_idx) owns exactly one row.
-            # mLSE shape is (T, 1, 1). mLSE[i, 0, 0] writes row i's LSE.
             if const_expr(not self.normalize):
                 _row_max_safe = row_max
                 if row_max == -cutlass.Float32.inf:
                     _row_max_safe = Float32(0.0)
-                _ln2 = Float32(0.6931471805599453)  # ln(2)
-                lse_val = cute.math.log(row_sum, fastmath=True) + _row_max_safe * _ln2
                 if sfw_idx == 0:
+                    _ln2 = Float32(0.6931471805599453)  # ln(2)
+                    lse_val = cute.math.log(row_sum, fastmath=True) + _row_max_safe * _ln2
                     mLSE[0] = lse_val
 
             tmem.relinquish_alloc_permit()