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Copy file name to clipboardExpand all lines: doc/specs/stdlib_intrinsics.md
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@@ -15,7 +15,7 @@ The `stdlib_intrinsics` module provides replacements for some of the well known
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#### Description
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The `stdlib_sum` function can replace the intrinsic `sum` for `real`or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential as well as reducing the round-off error. This procedure is recommended when summing large arrays, for repetitive summation of smaller arrays consider the classical `sum`.
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The `stdlib_sum` function can replace the intrinsic `sum` for `real`, `complex`or `integer` arrays. It follows a chunked implementation which maximizes vectorization potential as well as reducing the round-off error. This procedure is recommended when summing large arrays, for repetitive summation of smaller arrays consider the classical `sum`.
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#### Syntax
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#### Description
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The `stdlib_sum_kahan` function can replace the intrinsic `sum` for `real`, `complex`or `integer` arrays. It follows a chunked implementation which maximizes vectorization potential complemented by an `elemental` kernel based on the [kahan summation](https://doi.org/10.1145%2F363707.363723) strategy to reduce the round-off error:
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The `stdlib_sum_kahan` function can replace the intrinsic `sum` for `real`or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential complemented by an `elemental` kernel based on the [kahan summation](https://doi.org/10.1145%2F363707.363723) strategy to reduce the round-off error:
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```fortran
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elemental subroutine kahan_kernel_<kind>(a,s,c)
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#### Argument(s)
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`x`: 1D array of either `real`, `complex`or `integer` type. This argument is `intent(in)`.
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`x`: 1D array of either `real`or `complex` type. This argument is `intent(in)`.
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`dim` (optional): scalar of type `integer` with a value in the range from 1 to n, where n equals the rank of `x`.
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#### Description
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The `stdlib_dot_product` function can replace the intrinsic `dot_product` for 1D `real`or `complex` arrays. It follows a chunked implementation which maximizes vectorization potential as well as reducing the round-off error. This procedure is recommended when crunching large arrays, for repetitive products of smaller arrays consider the classical `dot_product`.
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The `stdlib_dot_product` function can replace the intrinsic `dot_product` for 1D `real`, `complex`or `integer` arrays. It follows a chunked implementation which maximizes vectorization potential as well as reducing the round-off error. This procedure is recommended when crunching large arrays, for repetitive products of smaller arrays consider the classical `dot_product`.
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