triton-ascend

import os import torch import triton import triton.language as tl # Ensure Ascend NPU environment is set up. This is usually done via `source /path/to/Ascend/ascend-toolkit/set_env.sh` # For demonstration, we assume 'npu' device is available through torch_npu. # You might need to install torch and torch_npu compatible with your CANN version, e.g.: # pip install torch==2.6.0 --index-url https://download.pytorch.org/whl/cpu # pip install torch_npu==2.6.0 # The actual import `torch_npu` might be handled implicitly by Ascend's PyTorch backend setup. @triton.jit def add_kernel(x_ptr, y_ptr, output_ptr, n_elements, BLOCK_SIZE: tl.constexpr): pid = tl.program_id(axis=0) block_start = pid * BLOCK_SIZE offsets = block_start + tl.arange(0, BLOCK_SIZE) mask = offsets < n_elements x = tl.load(x_ptr + offsets, mask=mask) y = tl.load(y_ptr + offsets, mask=mask) output = x + y tl.store(output_ptr + offsets, output, mask=mask) def main(): if not torch.npu.is_available(): print("Ascend NPU not available. Please ensure CANN and torch_npu are correctly installed and configured.") return print(f"Using NPU device: {torch.npu.get_device_name(0)}") N = 1024 * 128 # Allocate memory on NPU x = torch.randn(N, device='npu', dtype=torch.float32) y = torch.randn(N, device='npu', dtype=torch.float32) output = torch.empty_like(x, device='npu') # Define the grid and block size BLOCK_SIZE = 1024 grid = lambda META: (triton.cdiv(N, META['BLOCK_SIZE']),) # Launch the kernel print("Launching Triton-Ascend kernel...") add_kernel[grid](x, y, output, N, BLOCK_SIZE=BLOCK_SIZE) # Verify results torch_output = x + y assert torch.allclose(output, torch_output, atol=1e-5, rtol=1e-5) print("Kernel execution successful and results verified!") if __name__ == '__main__': # It's crucial to set up the Ascend CANN environment variables before running. # Example: os.environ['ASCEND_TOOLKIT_PATH'] = '/usr/local/Ascend/ascend-toolkit' # Or ensure your shell environment has sourced the set_env.sh script. try: import torch_npu main() except ImportError: print("torch_npu not found. Please install it with `pip install torch_npu` (ensure compatibility with your Ascend CANN version).") except Exception as e: print(f"An error occurred: {e}")