code: def static_persistent_matmul_no_scf_kernel(
      a_ptr,
      b_ptr,
      c_ptr,  #
      M,
      N,
      K,  #
      stride_am,
      stride_ak,  #
      stride_bk,
      stride_bn,  #
      stride_cm,
      stride_cn,  #
      BLOCK_M: tl.constexpr,
      BLOCK_N: tl.constexpr,
      BLOCK_K: tl.constexpr,  #
      FLOAT16_OUTPUT: tl.constexpr,
      USE_TMA_EPILOGUE: tl.constexpr,  #
      NUM_SMS: tl.constexpr,
      USE_TMA_LOAD: tl.constexpr,  #
  ):
      start_tile = tl.program_id(axis=0)
      m_tiles = tl.cdiv(M, BLOCK_M)
      n_tiles = tl.cdiv(N, BLOCK_N)
      num_tiles = m_tiles * n_tiles
      offs_k = tl.arange(0, BLOCK_K)
      pre_pid_m = start_tile // n_tiles
      pre_pid_n = start_tile % n_tiles
      block_offset_m = pre_pid_m * BLOCK_M
      block_offset_n = pre_pid_n * BLOCK_N
  
      if USE_TMA_LOAD:
          a_block_ptr = tl.make_block_ptr(
              base=a_ptr,
              shape=(M, K),
              strides=(stride_am, stride_ak),
              offsets=(block_offset_m, 0),
              block_shape=(BLOCK_M, BLOCK_K),
              order=(1, 0),
          )
          b_block_ptr = tl.make_block_ptr(
              base=b_ptr,
              shape=(K, N),
              strides=(stride_bk, stride_bn),
              offsets=(0, block_offset_n),
              block_shape=(BLOCK_K, BLOCK_N),
              order=(0, 1),
          )
      if USE_TMA_EPILOGUE:
          c_block_ptr = tl.make_block_ptr(
              base=c_ptr,
              shape=(M, N),
              strides=(stride_cm, stride_cn),
              offsets=(block_offset_m, block_offset_n),
              block_shape=(BLOCK_M, BLOCK_N),
              order=(1, 0),
          )
  
      for tile_id in range(start_tile, num_tiles, NUM_SMS):
          pid_m = tile_id // n_tiles
          pid_n = tile_id % n_tiles
  
          if USE_TMA_LOAD:
              a_block_ptr = tl.advance(
                  a_block_ptr, [(pid_m - pre_pid_m) * BLOCK_M, 0]
              )
              b_block_ptr = tl.advance(
                  b_block_ptr, [0, (pid_n - pre_pid_n) * BLOCK_N]
              )
              a = tl.load(a_block_ptr)
              b = tl.load(b_block_ptr)
          else:
              offs_am = pid_m * BLOCK_M + tl.arange(0, BLOCK_M)
              offs_bn = pid_n * BLOCK_N + tl.arange(0, BLOCK_N)
              a_ptrs = a_ptr + (
                  offs_am[:, None] * stride_am
                  + offs_k[None, :] * stride_ak
              )
              b_ptrs = b_ptr + (
                  offs_k[:, None] * stride_bk
                  + offs_bn[None, :] * stride_bn
              )
              a = tl.load(a_ptrs)
              b = tl.load(b_ptrs)
  
          c = tl.dot(a, b)
  
          if FLOAT16_OUTPUT:
              c = c.to(tl.float16)
  
          if USE_TMA_EPILOGUE:
              c_block_ptr = tl.advance(
                  c_block_ptr,
                  [
                      (pid_m - pre_pid_m) * BLOCK_M,
                      (pid_n - pre_pid_n) * BLOCK_N,
                  ],
              )
              tl.store(c_block_ptr, c)
          else:
              offs_m = pid_m * BLOCK_M + tl.arange(0, BLOCK_M)
              offs_n = pid_n * BLOCK_N + tl.arange(0, BLOCK_N)
              c_ptrs = (
                  c_ptr
                  + offs_m[:, None] * stride_cm
                  + offs_n[None, :] * stride_cn
              )
              tl.store(c_ptrs, c)
  
          pre_pid_m = pid_m
          pre_pid_n = pid_n
  
imports: import itertools
  import pytest
  import torch
  from torch.testing import assert_close
  import triton
  import triton.language
  from triton.runtime import driver
label_desc: Use image node_id 11 for calling a global function with example usage: static_persistent_matmul_no_scf_kernel(a_ptr, b_ptr, c_ptr, M, N, K, stride_am, stride_ak, stride_bk, stride_bn, stride_cm, stride_cn, BLOCK_M, BLOCK_N, BLOCK_K, FLOAT16_OUTPUT, USE_TMA_EPILOGUE, NUM_SMS, USE_TMA_LOAD) without return types