83fb0c8c47
Co-authored-by: Julia Jiang <56359287+jujiang-del@users.noreply.github.com>
454 rivejä
14 KiB
ReStructuredText
454 rivejä
14 KiB
ReStructuredText
.. meta::
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:description: This chapter describes the complex math functions that are accessible in HIP.
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:keywords: AMD, ROCm, HIP, CUDA, complex math functions, HIP complex math functions
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.. _complex_math_api_reference:
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********************************************************************************
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HIP complex math API
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********************************************************************************
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HIP provides built-in support for complex number operations through specialized types and functions,
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available for both single-precision (float) and double-precision (double) calculations. All complex types
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and functions are available on both host and device.
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For any complex number ``z``, the form is:
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.. math::
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z = x + yi
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where ``x`` is the real part and ``y`` is the imaginary part.
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Complex Number Types
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====================
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A brief overview of the specialized data types used to represent complex numbers in HIP, available
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in both single and double precision formats.
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Type
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- Description
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* - ``hipFloatComplex``
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- | Complex number using single-precision (float) values
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| (note: ``hipComplex`` is an alias of ``hipFloatComplex``)
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* - ``hipDoubleComplex``
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- Complex number using double-precision (double) values
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Complex Number Functions
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========================
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.. note::
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Changes have been made to small vector constructors for ``hipComplex`` and ``hipFloatComplex``
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initialization, such as ``float2`` and ``int4``. If your code previously relied
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on a single value to initialize all components within a vector or complex type, you might need
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to update your code.
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A comprehensive collection of functions for creating and manipulating complex numbers, organized by
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functional categories for easy reference.
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Type Construction
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-----------------
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Functions for creating complex number objects and extracting their real and imaginary components.
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.. tab-set::
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.. tab-item:: Single Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipFloatComplex``
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| ``make_hipFloatComplex(``
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| ``float a,``
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| ``float b``
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| ``)``
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- | Creates a complex number
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| (note: ``make_hipComplex`` is an alias of ``make_hipFloatComplex``)
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| :math:`z = a + bi`
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* - | ``float``
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| ``hipCrealf(``
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| ``hipFloatComplex z``
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| ``)``
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- | Returns real part of z
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| :math:`\Re(z) = x`
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* - | ``float``
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| ``hipCimagf(``
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| ``hipFloatComplex z``
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| ``)``
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- | Returns imaginary part of z
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| :math:`\Im(z) = y`
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.. tab-item:: Double Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipDoubleComplex``
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| ``make_hipDoubleComplex(``
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| ``double a,``
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| ``double b``
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| ``)``
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- | Creates a complex number
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| :math:`z = a + bi`
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* - | ``double``
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| ``hipCreal(``
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| ``hipDoubleComplex z``
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| ``)``
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- | Returns real part of z
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| :math:`\Re(z) = x`
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* - | ``double``
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| ``hipCimag(``
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| ``hipDoubleComplex z``
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| ``)``
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- | Returns imaginary part of z
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| :math:`\Im(z) = y`
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Basic Arithmetic
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----------------
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Operations for performing standard arithmetic with complex numbers, including addition,
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subtraction, multiplication, division, and fused multiply-add.
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.. tab-set::
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.. tab-item:: Single Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipFloatComplex``
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| ``hipCaddf(``
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| ``hipFloatComplex p,``
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| ``hipFloatComplex q``
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| ``)``
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- | Addition of two single-precision complex values
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| :math:`(a + bi) + (c + di) = (a + c) + (b + d)i`
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* - | ``hipFloatComplex``
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| ``hipCsubf(``
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| ``hipFloatComplex p,``
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| ``hipFloatComplex q``
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| ``)``
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- | Subtraction of two single-precision complex values
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| :math:`(a + bi) - (c + di) = (a - c) + (b - d)i`
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* - | ``hipFloatComplex``
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| ``hipCmulf(``
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| ``hipFloatComplex p,``
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| ``hipFloatComplex q``
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| ``)``
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- | Multiplication of two single-precision complex values
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| :math:`(a + bi)(c + di) = (ac - bd) + (bc + ad)i`
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* - | ``hipFloatComplex``
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| ``hipCdivf(``
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| ``hipFloatComplex p,``
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| ``hipFloatComplex q``
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| ``)``
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- | Division of two single-precision complex values
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| :math:`\frac{a + bi}{c + di} = \frac{(ac + bd) + (bc - ad)i}{c^2 + d^2}`
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* - | ``hipFloatComplex``
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| ``hipCfmaf(``
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| ``hipComplex p,``
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| ``hipComplex q,``
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| ``hipComplex r``
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| ``)``
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- | Fused multiply-add of three single-precision complex values
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| :math:`(a + bi)(c + di) + (e + fi)`
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.. tab-item:: Double Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipDoubleComplex``
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| ``hipCadd(``
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| ``hipDoubleComplex p,``
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| ``hipDoubleComplex q``
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| ``)``
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- | Addition of two double-precision complex values
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| :math:`(a + bi) + (c + di) = (a + c) + (b + d)i`
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* - | ``hipDoubleComplex``
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| ``hipCsub(``
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| ``hipDoubleComplex p,``
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| ``hipDoubleComplex q``
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| ``)``
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- | Subtraction of two double-precision complex values
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| :math:`(a + bi) - (c + di) = (a - c) + (b - d)i`
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* - | ``hipDoubleComplex``
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| ``hipCmul(``
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| ``hipDoubleComplex p,``
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| ``hipDoubleComplex q``
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| ``)``
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- | Multiplication of two double-precision complex values
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| :math:`(a + bi)(c + di) = (ac - bd) + (bc + ad)i`
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* - | ``hipDoubleComplex``
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| ``hipCdiv(``
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| ``hipDoubleComplex p,``
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| ``hipDoubleComplex q``
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| ``)``
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- | Division of two double-precision complex values
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| :math:`\frac{a + bi}{c + di} = \frac{(ac + bd) + (bc - ad)i}{c^2 + d^2}`
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* - | ``hipDoubleComplex``
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| ``hipCfma(``
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| ``hipDoubleComplex p,``
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| ``hipDoubleComplex q,``
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| ``hipDoubleComplex r``
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| ``)``
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- | Fused multiply-add of three double-precision complex values
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| :math:`(a + bi)(c + di) + (e + fi)`
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Complex Operations
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------------------
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Functions for complex-specific calculations, including conjugate determination and magnitude
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(absolute value) computation.
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.. tab-set::
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.. tab-item:: Single Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipFloatComplex``
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| ``hipConjf(``
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| ``hipFloatComplex z``
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| ``)``
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- | Complex conjugate
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| :math:`\overline{a + bi} = a - bi`
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* - | ``float``
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| ``hipCabsf(``
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| ``hipFloatComplex z``
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| ``)``
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- | Absolute value (magnitude)
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| :math:`|a + bi| = \sqrt{a^2 + b^2}`
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* - | ``float``
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| ``hipCsqabsf(``
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| ``hipFloatComplex z``
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| ``)``
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- | Squared absolute value
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| :math:`|a + bi|^2 = a^2 + b^2`
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.. tab-item:: Double Precision
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipDoubleComplex``
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| ``hipConj(``
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| ``hipDoubleComplex z``
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| ``)``
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- | Complex conjugate
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| :math:`\overline{a + bi} = a - bi`
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* - | ``double``
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| ``hipCabs(``
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| ``hipDoubleComplex z``
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| ``)``
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- | Absolute value (magnitude)
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| :math:`|a + bi| = \sqrt{a^2 + b^2}`
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* - | ``double``
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| ``hipCsqabs(``
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| ``hipDoubleComplex z``
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| ``)``
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- | Squared absolute value
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| :math:`|a + bi|^2 = a^2 + b^2`
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Type Conversion
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---------------
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Utility functions for conversion between single-precision and double-precision complex number formats.
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.. list-table::
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:header-rows: 1
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:widths: 40 60
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* - Function
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- Description
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* - | ``hipFloatComplex``
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| ``hipComplexDoubleToFloat(``
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| ``hipDoubleComplex z``
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| ``)``
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- Converts double-precision to single-precision complex
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* - | ``hipDoubleComplex``
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| ``hipComplexFloatToDouble(``
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| ``hipFloatComplex z``
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| ``)``
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- Converts single-precision to double-precision complex
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Example Usage
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=============
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The following example demonstrates using complex numbers to compute the Discrete Fourier Transform (DFT)
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of a simple signal on the GPU. The DFT converts a signal from the time domain to the frequency domain.
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The kernel function ``computeDFT`` shows various HIP complex math operations in action:
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* Creating complex numbers with ``make_hipFloatComplex``
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* Performing complex multiplication with ``hipCmulf``
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* Accumulating complex values with ``hipCaddf``
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The example also demonstrates proper use of complex number handling on both host and device, including
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memory allocation, transfer, and validation of results between CPU and GPU implementations.
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.. code-block:: cpp
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#include <hip/hip_runtime.h>
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#include <hip/hip_complex.h>
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#include <iostream>
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#include <vector>
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#include <cmath>
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#define HIP_CHECK(expression) \
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{ \
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const hipError_t err = expression; \
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if (err != hipSuccess) { \
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std::cerr << "HIP error: " \
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<< hipGetErrorString(err) \
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<< " at " << __LINE__ << "\n"; \
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exit(EXIT_FAILURE); \
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} \
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}
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// Kernel to compute DFT
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__global__ void computeDFT(const float* input,
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hipFloatComplex* output,
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const int N)
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{
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int k = blockIdx.x * blockDim.x + threadIdx.x;
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if (k >= N) return;
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hipFloatComplex sum = make_hipFloatComplex(0.0f, 0.0f);
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for (int n = 0; n < N; n++) {
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float angle = -2.0f * M_PI * k * n / N;
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hipFloatComplex w = make_hipFloatComplex(cosf(angle), sinf(angle));
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hipFloatComplex x = make_hipFloatComplex(input[n], 0.0f);
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sum = hipCaddf(sum, hipCmulf(x, w));
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}
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output[k] = sum;
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}
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// CPU implementation of DFT for verification
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std::vector<hipFloatComplex> cpuDFT(const std::vector<float>& input) {
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const int N = input.size();
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std::vector<hipFloatComplex> result(N);
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for (int k = 0; k < N; k++) {
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hipFloatComplex sum = make_hipFloatComplex(0.0f, 0.0f);
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for (int n = 0; n < N; n++) {
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float angle = -2.0f * M_PI * k * n / N;
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hipFloatComplex w = make_hipFloatComplex(cosf(angle), sinf(angle));
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hipFloatComplex x = make_hipFloatComplex(input[n], 0.0f);
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sum = hipCaddf(sum, hipCmulf(x, w));
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}
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result[k] = sum;
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}
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return result;
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}
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int main() {
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const int N = 256; // Signal length
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const int blockSize = 256;
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// Generate input signal: sum of two sine waves
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std::vector<float> signal(N);
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for (int i = 0; i < N; i++) {
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float t = static_cast<float>(i) / N;
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signal[i] = sinf(2.0f * M_PI * 10.0f * t) + // 10 Hz component
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0.5f * sinf(2.0f * M_PI * 20.0f * t); // 20 Hz component
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}
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// Compute reference solution on CPU
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std::vector<hipFloatComplex> cpu_output = cpuDFT(signal);
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// Allocate device memory
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float* d_signal;
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hipFloatComplex* d_output;
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HIP_CHECK(hipMalloc(&d_signal, N * sizeof(float)));
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HIP_CHECK(hipMalloc(&d_output, N * sizeof(hipFloatComplex)));
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// Copy input to device
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HIP_CHECK(hipMemcpy(d_signal, signal.data(), N * sizeof(float),
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hipMemcpyHostToDevice));
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// Launch kernel
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dim3 grid((N + blockSize - 1) / blockSize);
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dim3 block(blockSize);
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computeDFT<<<grid, block>>>(d_signal, d_output, N);
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HIP_CHECK(hipGetLastError());
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// Get GPU results
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std::vector<hipFloatComplex> gpu_output(N);
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HIP_CHECK(hipMemcpy(gpu_output.data(), d_output, N * sizeof(hipFloatComplex),
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hipMemcpyDeviceToHost));
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// Verify results
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bool passed = true;
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const float tolerance = 1e-5f; // Adjust based on precision requirements
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for (int i = 0; i < N; i++) {
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float diff_real = std::abs(hipCrealf(gpu_output[i]) - hipCrealf(cpu_output[i]));
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float diff_imag = std::abs(hipCimagf(gpu_output[i]) - hipCimagf(cpu_output[i]));
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if (diff_real > tolerance || diff_imag > tolerance) {
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passed = false;
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break;
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}
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}
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std::cout << "DFT Verification: " << (passed ? "PASSED" : "FAILED") << "\n";
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// Cleanup
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HIP_CHECK(hipFree(d_signal));
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HIP_CHECK(hipFree(d_output));
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return passed ? 0 : 1;
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}
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