stm32f407-openocd/Drivers/CMSIS/DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c

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/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_dot_prod_f32.c
* Description: Floating-point dot product
*
* $Date: 05 October 2021
* $Revision: V1.9.1
*
* Target Processor: Cortex-M and Cortex-A cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "dsp/basic_math_functions.h"
/**
@ingroup groupMath
*/
/**
@defgroup BasicDotProd Vector Dot Product
Computes the dot product of two vectors.
The vectors are multiplied element-by-element and then summed.
<pre>
sum = pSrcA[0]*pSrcB[0] + pSrcA[1]*pSrcB[1] + ... + pSrcA[blockSize-1]*pSrcB[blockSize-1]
</pre>
There are separate functions for floating-point, Q7, Q15, and Q31 data types.
*/
/**
@addtogroup BasicDotProd
@{
*/
/**
@brief Dot product of floating-point vectors.
@param[in] pSrcA points to the first input vector.
@param[in] pSrcB points to the second input vector.
@param[in] blockSize number of samples in each vector.
@param[out] result output result returned here.
@return none
*/
#if defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE)
#include "arm_helium_utils.h"
void arm_dot_prod_f32(
const float32_t * pSrcA,
const float32_t * pSrcB,
uint32_t blockSize,
float32_t * result)
{
f32x4_t vecA, vecB;
f32x4_t vecSum;
uint32_t blkCnt;
float32_t sum = 0.0f;
vecSum = vdupq_n_f32(0.0f);
/* Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
while (blkCnt > 0U)
{
/*
* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1]
* Calculate dot product and then store the result in a temporary buffer.
* and advance vector source and destination pointers
*/
vecA = vld1q(pSrcA);
pSrcA += 4;
vecB = vld1q(pSrcB);
pSrcB += 4;
vecSum = vfmaq(vecSum, vecA, vecB);
/*
* Decrement the blockSize loop counter
*/
blkCnt --;
}
blkCnt = blockSize & 3;
if (blkCnt > 0U)
{
/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
mve_pred16_t p0 = vctp32q(blkCnt);
vecA = vld1q(pSrcA);
vecB = vld1q(pSrcB);
vecSum = vfmaq_m(vecSum, vecA, vecB, p0);
}
sum = vecAddAcrossF32Mve(vecSum);
/* Store result in destination buffer */
*result = sum;
}
#else
void arm_dot_prod_f32(
const float32_t * pSrcA,
const float32_t * pSrcB,
uint32_t blockSize,
float32_t * result)
{
uint32_t blkCnt; /* Loop counter */
float32_t sum = 0.0f; /* Temporary return variable */
#if defined(ARM_MATH_NEON) && !defined(ARM_MATH_AUTOVECTORIZE)
f32x4_t vec1;
f32x4_t vec2;
f32x4_t accum = vdupq_n_f32(0);
#if !defined(__aarch64__)
f32x2_t tmp = vdup_n_f32(0);
#endif
/* Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
vec1 = vld1q_f32(pSrcA);
vec2 = vld1q_f32(pSrcB);
while (blkCnt > 0U)
{
/* C = A[0]*B[0] + A[1]*B[1] + A[2]*B[2] + ... + A[blockSize-1]*B[blockSize-1] */
/* Calculate dot product and then store the result in a temporary buffer. */
accum = vmlaq_f32(accum, vec1, vec2);
/* Increment pointers */
pSrcA += 4;
pSrcB += 4;
vec1 = vld1q_f32(pSrcA);
vec2 = vld1q_f32(pSrcB);
/* Decrement the loop counter */
blkCnt--;
}
#if defined(__aarch64__)
sum = vpadds_f32(vpadd_f32(vget_low_f32(accum), vget_high_f32(accum)));
#else
tmp = vpadd_f32(vget_low_f32(accum), vget_high_f32(accum));
sum = vget_lane_f32(tmp, 0) + vget_lane_f32(tmp, 1);
#endif
/* Tail */
blkCnt = blockSize & 0x3;
#else
#if defined (ARM_MATH_LOOPUNROLL) && !defined(ARM_MATH_AUTOVECTORIZE)
/* Loop unrolling: Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
** a second loop below computes the remaining 1 to 3 samples. */
while (blkCnt > 0U)
{
/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
/* Calculate dot product and store result in a temporary buffer. */
sum += (*pSrcA++) * (*pSrcB++);
sum += (*pSrcA++) * (*pSrcB++);
sum += (*pSrcA++) * (*pSrcB++);
sum += (*pSrcA++) * (*pSrcB++);
/* Decrement loop counter */
blkCnt--;
}
/* Loop unrolling: Compute remaining outputs */
blkCnt = blockSize % 0x4U;
#else
/* Initialize blkCnt with number of samples */
blkCnt = blockSize;
#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
#endif /* #if defined(ARM_MATH_NEON) */
while (blkCnt > 0U)
{
/* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
/* Calculate dot product and store result in a temporary buffer. */
sum += (*pSrcA++) * (*pSrcB++);
/* Decrement loop counter */
blkCnt--;
}
/* Store result in destination buffer */
*result = sum;
}
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
/**
@} end of BasicDotProd group
*/