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