184 lines
4.8 KiB
ReStructuredText
184 lines
4.8 KiB
ReStructuredText
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.. DO NOT EDIT.
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.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
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.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
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.. "getting-started/tutorials/07-libdevice-function.py"
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.. LINE NUMBERS ARE GIVEN BELOW.
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.. only:: html
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.. note::
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:class: sphx-glr-download-link-note
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Click :ref:`here <sphx_glr_download_getting-started_tutorials_07-libdevice-function.py>`
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to download the full example code
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.. rst-class:: sphx-glr-example-title
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.. _sphx_glr_getting-started_tutorials_07-libdevice-function.py:
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Libdevice function
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===============
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Triton can invoke a custom function from an external library.
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In this example, we will use the `libdevice` library to apply `asin` on a tensor.
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Please refer to https://docs.nvidia.com/cuda/libdevice-users-guide/index.html regarding the semantics of all available libdevice functions.
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In `trition/language/libdevice.py`, we try to aggregate functions with the same computation but different data types together.
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For example, both `__nv_asin` and `__nvasinf` calculate the principal value of the arc sine of the input, but `__nv_asin` operates on `double` and `__nv_asinf` operates on `float`.
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Using triton, you can simply call `tl.libdevice.asinf`.
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triton automatically selects the correct underlying device function to invoke based on input and output types.
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.. GENERATED FROM PYTHON SOURCE LINES 15-17
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asin Kernel
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--------------------------
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.. GENERATED FROM PYTHON SOURCE LINES 17-39
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.. code-block:: default
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import torch
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import triton
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import triton.language as tl
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@triton.jit
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def asin_kernel(
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x_ptr,
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y_ptr,
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n_elements,
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BLOCK_SIZE: tl.constexpr,
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):
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pid = tl.program_id(axis=0)
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block_start = pid * BLOCK_SIZE
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offsets = block_start + tl.arange(0, BLOCK_SIZE)
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mask = offsets < n_elements
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x = tl.load(x_ptr + offsets, mask=mask)
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x = tl.libdevice.asin(x)
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tl.store(y_ptr + offsets, x, mask=mask)
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.. GENERATED FROM PYTHON SOURCE LINES 40-43
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Using the default libdevice library path
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--------------------------
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We can use the default libdevice library path encoded in `triton/language/libdevice.py`
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.. GENERATED FROM PYTHON SOURCE LINES 43-61
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.. code-block:: default
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torch.manual_seed(0)
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size = 98432
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x = torch.rand(size, device='cuda')
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output_triton = torch.zeros(size, device='cuda')
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output_torch = torch.asin(x)
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assert x.is_cuda and output_triton.is_cuda
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n_elements = output_torch.numel()
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grid = lambda meta: (triton.cdiv(n_elements, meta['BLOCK_SIZE']),)
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asin_kernel[grid](x, output_triton, n_elements, BLOCK_SIZE=1024)
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print(output_torch)
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print(output_triton)
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print(
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f'The maximum difference between torch and triton is '
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f'{torch.max(torch.abs(output_torch - output_triton))}'
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)
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.. rst-class:: sphx-glr-script-out
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Out:
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.. code-block:: none
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tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:0')
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tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:0')
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The maximum difference between torch and triton is 2.384185791015625e-07
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.. GENERATED FROM PYTHON SOURCE LINES 62-65
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Customize the libdevice library path
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--------------------------
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We can also customize the libdevice library path by passing the path to the `libdevice` library to the `asin` kernel.
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.. GENERATED FROM PYTHON SOURCE LINES 65-75
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.. code-block:: default
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output_triton = torch.empty_like(x)
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asin_kernel[grid](x, output_triton, n_elements, BLOCK_SIZE=1024,
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extern_libs={'libdevice': '/usr/local/cuda/nvvm/libdevice/libdevice.10.bc'})
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print(output_torch)
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print(output_triton)
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print(
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f'The maximum difference between torch and triton is '
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f'{torch.max(torch.abs(output_torch - output_triton))}'
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)
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.. rst-class:: sphx-glr-script-out
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Out:
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.. code-block:: none
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tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:0')
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tensor([0.4105, 0.5430, 0.0249, ..., 0.0424, 0.5351, 0.8149], device='cuda:0')
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The maximum difference between torch and triton is 2.384185791015625e-07
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.. rst-class:: sphx-glr-timing
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**Total running time of the script:** ( 0 minutes 0.253 seconds)
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.. _sphx_glr_download_getting-started_tutorials_07-libdevice-function.py:
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.. only :: html
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.. container:: sphx-glr-footer
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:class: sphx-glr-footer-example
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.. container:: sphx-glr-download sphx-glr-download-python
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:download:`Download Python source code: 07-libdevice-function.py <07-libdevice-function.py>`
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.. container:: sphx-glr-download sphx-glr-download-jupyter
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:download:`Download Jupyter notebook: 07-libdevice-function.ipynb <07-libdevice-function.ipynb>`
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.. only:: html
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.. rst-class:: sphx-glr-signature
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`Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_
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