Simplify copy and cast kernels#1165
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oleksandr-pavlyk merged 5 commits intomasterfrom Apr 11, 2023
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Functions should store typed pointers instead of typeless. The CastFnT effectively becomes a trivial call to convert_impl in its call operator. Also added few data movement optimizations.
Example where it helps: ``` In [1]: import dpctl, dpctl.tensor as dpt In [2]: x = dpt.arange(1234*7873, dtype=dpt.int32) In [3]: xx = dpt.permute_dims(dpt.reshape(x, (2, 617, 7873)), (1,2,0)) In [4]: yy = dpt.permute_dims(dpt.reshape(dpt.empty_like(x, dtype="f4"), (2, 617, 7873)), (1,2,0)) In [5]: %timeit yy[...] = xx 1.07 ms ± 93.8 µs per loop (mean ± std. dev. of 7 runs, 1,000 loops each) ``` in master the time is about 2.8 ms on Iris Xe.
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View rendered docs @ https://intelpython.github.io/dpctl/pulls/1165/index.html |
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_98 ran successfully. |
- CopyAndCastContigFactory changed to reflect that contiguous copying and casting is now possible for more than strictly different data types
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_105 ran successfully. |
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@ndgrigorian Good catch! |
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Deleted rendered PR docs from intelpython.github.com/dpctl, latest should be updated shortly. 🤞 |
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Array API standard conformance tests for dpctl=0.14.3dev0=py310h76be34b_105 ran successfully. |
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This PR works copy-and-cast functionality by simplifying underlying functors, removing specialized implementation for 2d arrays based on
CIndexer_arrayas it is only very marginally faster than general strided implementation based onCIndexer_vector.This PR also adds special implementation for copy-with-casting of contiguous arrays, making type casting of contiguous arrays several times faster.