diff --git a/vllm/attention/ops/triton_flash_attention.py b/vllm/attention/ops/triton_flash_attention.py
index f94211116a746..8c8d957b1e31b 100644
--- a/vllm/attention/ops/triton_flash_attention.py
+++ b/vllm/attention/ops/triton_flash_attention.py
@@ -20,6 +20,7 @@
 
 """
 
+import subprocess
 import torch
 import triton
 import triton.language as tl
@@ -206,105 +207,91 @@ def _attn_fwd_inner(
                                                    (0, BLOCK_N))
     return acc, l_i, m_i
 
+def get_gfx_version():
+    try:
+        # Run the rocminfo command
+        result = subprocess.run(['rocminfo'], stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
+        output = result.stdout
+
+        # Parse the output to find the gfx version
+        for line in output.splitlines():
+            line = line.strip()
+            if line.startswith("Name: gfx"):
+                gfx_version = line.split("Name:")[1].strip()
+                return gfx_version
+    except Exception as e:
+        print(f"Error: {e}")
+    return None
+
+def is_hip():
+    return triton.runtime.driver.active.get_current_target().backend == "hip"
+
+
+def is_cdna():
+    return is_hip() and triton.runtime.driver.active.get_current_target().arch in ('gfx940', 'gfx941', 'gfx942',
+                                                                                   'gfx90a', 'gfx908')
+
+
+def is_rdna():
+    return is_hip() and triton.runtime.driver.active.get_current_target().arch in ("gfx1030", "gfx1100", "gfx1101",
+                                                                                   "gfx1102", "gfx1200", "gfx1201")
+
+
+def get_cdna_autotune_configs():
+    return [
+        triton.Config({'BLOCK_M': 128, 'BLOCK_N': 128, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+        triton.Config({'BLOCK_M': 128, 'BLOCK_N': 64, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+        triton.Config({'BLOCK_M': 128, 'BLOCK_N': 64, 'waves_per_eu': 3, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+        triton.Config({'BLOCK_M': 128, 'BLOCK_N': 64, 'waves_per_eu': 1, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+        triton.Config({'BLOCK_M': 128, 'BLOCK_N': 32, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+        # Fall-back config.
+        triton.Config({'BLOCK_M': 16, 'BLOCK_N': 16, 'waves_per_eu': 1, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=4),
+    ], ['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL']
+
+
+def get_rdna_autotune_configs():
+    return [
+        triton.Config({'BLOCK_M': 32, 'BLOCK_N': 32, 'waves_per_eu': 4, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        triton.Config({'BLOCK_M': 32, 'BLOCK_N': 32, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        triton.Config({'BLOCK_M': 32, 'BLOCK_N': 16, 'waves_per_eu': 4, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        triton.Config({'BLOCK_M': 32, 'BLOCK_N': 16, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        triton.Config({'BLOCK_M': 16, 'BLOCK_N': 16, 'waves_per_eu': 4, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        triton.Config({'BLOCK_M': 16, 'BLOCK_N': 16, 'waves_per_eu': 2, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+        # Fall-back config.
+        triton.Config({'BLOCK_M': 16, 'BLOCK_N': 16, 'waves_per_eu': 1, 'PRE_LOAD_V': False}, num_stages=1,
+                      num_warps=2),
+    ], ['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL']
+
+
+def get_autotune_configs():
+    if is_rdna():
+        return get_rdna_autotune_configs()
+    elif is_cdna():
+        return get_cdna_autotune_configs()
+    else:
+        raise ValueError("Unknown Device Type")
+
+
+autotune_configs, autotune_keys = get_autotune_configs()
 
 @triton.autotune(
-    configs=[
-        triton.Config(
-            {
-                "BLOCK_M": 256,
-                "BLOCK_N": 64,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=8,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 128,
-                "BLOCK_N": 128,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 256,
-                "BLOCK_N": 128,
-                "waves_per_eu": 2,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=8,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 1,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 3,
-                "PRE_LOAD_V": True,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 128,
-                "BLOCK_N": 64,
-                "waves_per_eu": 3,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 64,
-                "BLOCK_N": 64,
-                "waves_per_eu": 4,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=8,
-        ),
-        triton.Config(
-            {
-                "BLOCK_M": 32,
-                "BLOCK_N": 32,
-                "waves_per_eu": 4,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=8,
-        ),
-        # TODO: This config fails with head_size not pow2 with data mismatches.
-        #    triton.Config({'BLOCK_M': 32, 'BLOCK_N': 16, 'waves_per_eu': 1,
-        #                   'PRE_LOAD_V': False}, num_stages=1, num_warps=4),
-        triton.Config(
-            {
-                "BLOCK_M": 16,
-                "BLOCK_N": 16,
-                "waves_per_eu": 1,
-                "PRE_LOAD_V": False,
-            },
-            num_stages=1,
-            num_warps=4,
-        ),
-    ],
-    key=['IS_CAUSAL', 'dropout_p', 'BLOCK_DMODEL'],
+    configs=autotune_configs,
+    key=autotune_keys,
+    use_cuda_graph=True,
 )
+
 @triton.jit
 def attn_fwd(
     Q,
@@ -795,8 +782,8 @@ def forward(
             HQ=nheads_q,
             HK=nheads_k,
             ACTUAL_BLOCK_DMODEL=head_size,
-            MAX_SEQLENS_Q=max_seqlens_q,
-            MAX_SEQLENS_K=max_seqlens_k,
+            MAX_SEQLENS_Q=0,
+            MAX_SEQLENS_K=0,
             IS_CAUSAL=causal,
             VARLEN=True,
             BLOCK_DMODEL=padded_d_model,