diff --git a/benchmarks/triton_kernels_benchmark/flash_attention_fwd_benchmark.py b/benchmarks/triton_kernels_benchmark/flash_attention_fwd_benchmark.py
index 5cc9998b1..a45875dde 100644
--- a/benchmarks/triton_kernels_benchmark/flash_attention_fwd_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/flash_attention_fwd_benchmark.py
@@ -227,7 +227,7 @@ def benchmark(Z, H, N_CTX, D_HEAD, provider):
         _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(
             lambda: torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=None, dropout_p=0.0, is_causal=
                                                                      False, scale=sm_scale), warmup=10, rep=10,
-            quantiles=quantiles, fast_flush=False)
+            quantiles=quantiles)
 
     elif provider == 'triton':
         triton_fn = lambda: forward(q, k, v, causal, sm_scale)
@@ -240,8 +240,7 @@ def benchmark(Z, H, N_CTX, D_HEAD, provider):
             ), attn_mask=None, dropout_p=0.0, is_causal=False, scale=sm_scale).to(torch.float32)
         atol = 1e-1 if N_CTX == 16384 else 1e-2
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=atol, rtol=1e-3, err_msg='triton to torch')
-        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                              fast_flush=False)
+        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
 
     elif provider == 'xetla':
         module_name = f'flash_attn_causal_{causal}'.lower()
@@ -256,8 +255,7 @@ def benchmark(Z, H, N_CTX, D_HEAD, provider):
         l = torch.empty((size_ml, ), device='xpu', dtype=torch.float)
 
         xetla_fn = lambda: func(q, k, v, out, dropout_mask, bias, m, l, Z, H, D_HEAD, N_CTX, N_CTX, sm_scale)
-        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(xetla_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                              fast_flush=False)
+        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(xetla_fn, warmup=10, rep=10, quantiles=quantiles)
 
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
diff --git a/benchmarks/triton_kernels_benchmark/gemm_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_benchmark.py
index bfc00eb01..159d05a69 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_benchmark.py
@@ -254,14 +254,13 @@ def benchmark(B, M, N, K, provider):
 
     if provider == 'onednn':
         _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(lambda: torch.matmul(a, b), warmup=10, rep=10,
-                                                                 quantiles=quantiles, fast_flush=False)
+                                                                 quantiles=quantiles)
     elif provider == 'triton':
         triton_fn = lambda: matmul(a, b)
         torch_fn = lambda: torch.matmul(a, b).to(torch.float32)
         rtol = 1e-2 if a.dtype == torch.bfloat16 else 1e-3
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=rtol, err_msg='triton to torch')
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                                 fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     elif provider == 'xetla':
         if B == 1:
             c = torch.empty((M, N), device='xpu', dtype=torch.float32)
@@ -276,8 +275,7 @@ def benchmark(B, M, N, K, provider):
         xetla_fn = lambda: func(a, b, c, acc, cnt)
         torch_fn = lambda: torch.matmul(a, b).to(torch.float32)
         # benchmark_suit.assert_close(xetla_fn(), torch_fn(), atol=1e-4, rtol=1.0, err_msg='xetla to torch')
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(xetla_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                                 fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(xetla_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/gemm_postop_addmatrix_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_postop_addmatrix_benchmark.py
index 6add18b32..b431405ee 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_postop_addmatrix_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_postop_addmatrix_benchmark.py
@@ -271,8 +271,7 @@ def benchmark(B, M, N, K, provider):
         torch_fn = lambda: torch.matmul(a, b).to(torch.float32) + d
         rtol = 1e-2 if a.dtype == torch.bfloat16 else 1e-3
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=rtol, err_msg='triton to torch')
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                                 fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/gemm_postop_gelu_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_postop_gelu_benchmark.py
index 9953cf535..2904ed679 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_postop_gelu_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_postop_gelu_benchmark.py
@@ -273,8 +273,7 @@ def benchmark(B, M, N, K, provider):
         torch_fn = lambda: torch.nn.functional.gelu(torch.matmul(a, b).to(torch.float32))
         rtol = 1e-2 if a.dtype == torch.bfloat16 else 1e-3
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=rtol, err_msg='triton to torch')
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                                 fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/gemm_preop_exp_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_preop_exp_benchmark.py
index 1ed4f8472..bff1b4399 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_preop_exp_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_preop_exp_benchmark.py
@@ -261,8 +261,7 @@ def benchmark(B, M, N, K, provider):
         torch_fn = lambda: torch.matmul(torch.exp(a), b).to(torch.float32)
         rtol = 1e-2 if a.dtype == torch.bfloat16 else 1e-3
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=rtol, err_msg='triton to torch')
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                                 fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/gemm_splitk_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_splitk_benchmark.py
index 5fa957f69..daba442eb 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_splitk_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_splitk_benchmark.py
@@ -158,14 +158,13 @@ def benchmark(M, N, K, provider):
 
     if provider == 'onednn':
         _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(lambda: torch.matmul(a, b), warmup=10, rep=10,
-                                                              quantiles=quantiles, fast_flush=False)
+                                                              quantiles=quantiles)
     elif provider == 'triton':
         triton_fn = lambda: matmul(a, b)
         torch_fn = lambda: torch.matmul(a, b).to(torch.float32)
         rtol = 1e-2 if a.dtype == torch.bfloat16 else 1e-3
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=rtol, err_msg='triton to torch')
-        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                              fast_flush=False)
+        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/gemm_streamk_benchmark.py b/benchmarks/triton_kernels_benchmark/gemm_streamk_benchmark.py
index 7eb0b651f..603659ded 100644
--- a/benchmarks/triton_kernels_benchmark/gemm_streamk_benchmark.py
+++ b/benchmarks/triton_kernels_benchmark/gemm_streamk_benchmark.py
@@ -274,13 +274,12 @@ def benchmark(M, N, K, provider):
 
     if provider == 'onednn':
         _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(lambda: torch.matmul(a, b), warmup=10, rep=10,
-                                                              quantiles=quantiles, fast_flush=False)
+                                                              quantiles=quantiles)
     elif provider == 'triton':
         triton_fn = lambda: matmul(a, b)
         torch_fn = lambda: torch.matmul(a, b).to(torch.float32)
         benchmark_suit.assert_close(triton_fn(), torch_fn(), atol=1e-4, rtol=1e-2, err_msg='triton to torch')
-        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles,
-                                                              fast_flush=False)
+        _, min_ms, max_ms, mean, cv = benchmark_suit.do_bench(triton_fn, warmup=10, rep=10, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')
 
diff --git a/benchmarks/triton_kernels_benchmark/prefix_sums.py b/benchmarks/triton_kernels_benchmark/prefix_sums.py
index f3beb0707..bb3d2069f 100644
--- a/benchmarks/triton_kernels_benchmark/prefix_sums.py
+++ b/benchmarks/triton_kernels_benchmark/prefix_sums.py
@@ -44,7 +44,7 @@ def benchmark(M, N, AXIS, provider):
 
     if provider == 'triton':
         triton_fn = lambda: scan_kernel[(1, )](x, BLOCK_SIZE_M=M, BLOCK_SIZE_N=N, AXIS=AXIS)
-        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, quantiles=quantiles, fast_flush=False)
+        _, min_ms, max_ms, mean_ms, cv = benchmark_suit.do_bench(triton_fn, quantiles=quantiles)
     else:
         raise NotImplementedError(f'Unsupported provider {provider}')