diff --git a/host.py b/host.py
index 13dd2c0..1841e24 100644
--- a/host.py
+++ b/host.py
@@ -72,12 +72,15 @@ def _flash_attn_forward(
     FP8_MAX: tl.constexpr = torch.finfo(q.dtype).max
     is_varlen = True if cu_seqlens_q is not None else False
 
+    # The kernel writes every (row < seqlen_q, full head_dim) element of the
+    # output (causal early-exit rows are explicitly zeroed inside the kernel),
+    # so we can skip the redundant memset of torch.zeros and use torch.empty.
     if IS_FP8:
-        o = torch.zeros(
+        o = torch.empty(
             (q.shape[:-1] + v.shape[-1:]), dtype=torch.float32, device=q.device
         )
     else:
-        o = torch.zeros((q.shape[:-1] + v.shape[-1:]), dtype=q.dtype, device=q.device)
+        o = torch.empty((q.shape[:-1] + v.shape[-1:]), dtype=q.dtype, device=q.device)
     if is_varlen:
         # Layout is thd.
         # q and k are [total_tokens, num_head, head_dim_qk].
diff --git a/kernel_jit.py b/kernel_jit.py
index 610b36c..a87a2fd 100644
--- a/kernel_jit.py
+++ b/kernel_jit.py
@@ -895,8 +895,25 @@ def _get_config(
     # TODO: pe + dropout is not tuned
     if has_pe and has_dropout_or_fp32 and "pe_dropout_or_fp32" in fwd_cfg:
         return fwd_cfg["pe_dropout_or_fp32"]
-    elif has_pe and "pe" in fwd_cfg:
-        return fwd_cfg["pe"]
+    elif has_pe:
+        # MLA prefill (head_dim_qk=192/v=128) tuned for gfx942 (MI300X).
+        # The stock "pe" config uses BLOCK_M=256, which produces too few
+        # workgroups (batch*heads*cdiv(seqlen,256)) to fill the 304 CUs for the
+        # short prefill seqlens seen here, leaving the GPU under-occupied.
+        # Halving BLOCK_M to 128 doubles workgroup count (better occupancy) and
+        # enabling 2-stage software pipelining (num_stages=2) overlaps the K/V
+        # loads with the QK/PV MFMA chain. waves_per_eu=1 + num_warps=4 keeps
+        # register/LDS pressure low enough to actually realize 2 pipeline stages
+        # (num_stages>=3 overflows the 64KB LDS for this 192/128 head config).
+        return {
+            "BLOCK_M": 128,
+            "BLOCK_N": 64,
+            "PRELOAD_V": True,
+            "waves_per_eu": 1,
+            "num_warps": 4,
+            "num_ctas": 1,
+            "num_stages": 2,
+        }
     elif enable_dropout or dtype == torch.float32:
         return fwd_cfg["dropout_or_fp32"]
     else: