tensor.zeros to use async memset #1806
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This is akin to _full_usm_ndarray, but does not take fill_value, hence does not require castings. It dispatches straight to handler::memset.
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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=0.18.0dev0=py310hdf72452_344 ran successfully. |
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@oleksandr-pavlyk |
Bitwise zero values, and 1-byte wide types now use memset, instead of using fill. ``` In [1]: import dpctl.tensor as dpt, dpctl.tensor._tensor_impl as ti In [2]: res = dpt.empty(10**6, dtype="i8") In [3]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(0, dst=res, sycl_queue=res.sycl_queue)[0].wait() 243 µs ± 22.6 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [4]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(0, dst=res, sycl_queue=res.sycl_queue)[0].wait() 229 µs ± 14 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [5]: %timeit -n 2000 -r 11 ti._zeros_usm_ndarray(dst=res, sycl_queue=res.sycl_queue)[0].wait() 227 µs ± 23 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [6]: %timeit -n 2000 -r 11 ti._zeros_usm_ndarray(dst=res, sycl_queue=res.sycl_queue)[0].wait() 233 µs ± 25.9 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [7]: %timeit -n 2000 -r 11 ti._zeros_usm_ndarray(dst=res, sycl_queue=res.sycl_queue)[0].wait() 301 µs ± 54.1 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [8]: %timeit -n 2000 -r 11 ti._zeros_usm_ndarray(dst=res, sycl_queue=res.sycl_queue)[0].wait() 236 µs ± 17.2 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [9]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(0, dst=res, sycl_queue=res.sycl_queue)[0].wait() 240 µs ± 35.2 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [10]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(1, dst=res, sycl_queue=res.sycl_queue)[0].wait() 243 µs ± 17.6 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [11]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(1, dst=res, sycl_queue=res.sycl_queue)[0].wait() 263 µs ± 39.9 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [12]: %timeit -n 2000 -r 11 ti._full_usm_ndarray(0, dst=res, sycl_queue=res.sycl_queue)[0].wait() 239 µs ± 26.4 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) In [13]: %timeit -n 2000 -r 11 ti._zeros_usm_ndarray(dst=res, sycl_queue=res.sycl_queue)[0].wait() 224 µs ± 18.1 µs per loop (mean ± std. dev. of 11 runs, 2,000 loops each) ```
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Array API standard conformance tests for dpctl=0.18.0dev0=py310hdf72452_345 ran successfully. |
ndgrigorian
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Aug 22, 2024
ndgrigorian
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Co-authored-by: ndgrigorian <46709016+ndgrigorian@users.noreply.github.com>
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Array API standard conformance tests for dpctl=0.18.0dev0=py310hdf72452_346 ran successfully. |
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Addressed outstanding FIXME note to use async call to populate array with zeros.
Added optimization for
_full_usm_ndarrayto usehandler::memsetinstead ofhandler::fillfor 1-byte wide types and for other types when fill value is bitwise zero.