641 lines
18 KiB
C
641 lines
18 KiB
C
/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_conv_f32.c
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* Description: Convolution of floating-point sequences
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*
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* $Date: 18. March 2019
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* $Revision: V1.6.0
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*
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* Target Processor: Cortex-M cores
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* -------------------------------------------------------------------- */
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/*
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* Copyright (C) 2010-2019 ARM Limited or its affiliates. All rights reserved.
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the License); you may
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* not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an AS IS BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "arm_math.h"
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/**
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@ingroup groupFilters
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*/
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/**
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@defgroup Conv Convolution
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Convolution is a mathematical operation that operates on two finite length vectors to generate a finite length output vector.
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Convolution is similar to correlation and is frequently used in filtering and data analysis.
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The CMSIS DSP library contains functions for convolving Q7, Q15, Q31, and floating-point data types.
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The library also provides fast versions of the Q15 and Q31 functions.
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@par Algorithm
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Let <code>a[n]</code> and <code>b[n]</code> be sequences of length <code>srcALen</code> and
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<code>srcBLen</code> samples respectively. Then the convolution
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<pre>
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c[n] = a[n] * b[n]
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</pre>
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@par
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is defined as
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\image html ConvolutionEquation.gif
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@par
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Note that <code>c[n]</code> is of length <code>srcALen + srcBLen - 1</code> and is defined over the interval <code>n=0, 1, 2, ..., srcALen + srcBLen - 2</code>.
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<code>pSrcA</code> points to the first input vector of length <code>srcALen</code> and
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<code>pSrcB</code> points to the second input vector of length <code>srcBLen</code>.
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The output result is written to <code>pDst</code> and the calling function must allocate <code>srcALen+srcBLen-1</code> words for the result.
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@par
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Conceptually, when two signals <code>a[n]</code> and <code>b[n]</code> are convolved,
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the signal <code>b[n]</code> slides over <code>a[n]</code>.
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For each offset \c n, the overlapping portions of a[n] and b[n] are multiplied and summed together.
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@par
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Note that convolution is a commutative operation:
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<pre>
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a[n] * b[n] = b[n] * a[n].
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</pre>
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@par
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This means that switching the A and B arguments to the convolution functions has no effect.
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@par Fixed-Point Behavior
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Convolution requires summing up a large number of intermediate products.
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As such, the Q7, Q15, and Q31 functions run a risk of overflow and saturation.
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Refer to the function specific documentation below for further details of the particular algorithm used.
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@par Fast Versions
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Fast versions are supported for Q31 and Q15. Cycles for Fast versions are less compared to Q31 and Q15 of conv and the design requires
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the input signals should be scaled down to avoid intermediate overflows.
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@par Opt Versions
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Opt versions are supported for Q15 and Q7. Design uses internal scratch buffer for getting good optimisation.
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These versions are optimised in cycles and consumes more memory (Scratch memory) compared to Q15 and Q7 versions
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*/
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/**
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@addtogroup Conv
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@{
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*/
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/**
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@brief Convolution of floating-point sequences.
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@param[in] pSrcA points to the first input sequence
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@param[in] srcALen length of the first input sequence
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@param[in] pSrcB points to the second input sequence
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@param[in] srcBLen length of the second input sequence
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@param[out] pDst points to the location where the output result is written. Length srcALen+srcBLen-1.
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@return none
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*/
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void arm_conv_f32(
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const float32_t * pSrcA,
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uint32_t srcALen,
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const float32_t * pSrcB,
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uint32_t srcBLen,
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float32_t * pDst)
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{
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#if (1)
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//#if !defined(ARM_MATH_CM0_FAMILY)
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const float32_t *pIn1; /* InputA pointer */
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const float32_t *pIn2; /* InputB pointer */
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float32_t *pOut = pDst; /* Output pointer */
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const float32_t *px; /* Intermediate inputA pointer */
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const float32_t *py; /* Intermediate inputB pointer */
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const float32_t *pSrc1, *pSrc2; /* Intermediate pointers */
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float32_t sum; /* Accumulators */
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uint32_t blockSize1, blockSize2, blockSize3; /* Loop counters */
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uint32_t j, k, count, blkCnt; /* Loop counters */
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#if defined (ARM_MATH_LOOPUNROLL)
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float32_t acc0, acc1, acc2, acc3; /* Accumulators */
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float32_t x0, x1, x2, x3, c0; /* Temporary variables to hold state and coefficient values */
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#endif
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/* The algorithm implementation is based on the lengths of the inputs. */
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/* srcB is always made to slide across srcA. */
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/* So srcBLen is always considered as shorter or equal to srcALen */
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if (srcALen >= srcBLen)
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{
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/* Initialization of inputA pointer */
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pIn1 = pSrcA;
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/* Initialization of inputB pointer */
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pIn2 = pSrcB;
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}
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else
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{
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/* Initialization of inputA pointer */
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pIn1 = pSrcB;
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/* Initialization of inputB pointer */
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pIn2 = pSrcA;
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/* srcBLen is always considered as shorter or equal to srcALen */
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j = srcBLen;
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srcBLen = srcALen;
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srcALen = j;
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}
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/* conv(x,y) at n = x[n] * y[0] + x[n-1] * y[1] + x[n-2] * y[2] + ...+ x[n-N+1] * y[N -1] */
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/* The function is internally
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* divided into three stages according to the number of multiplications that has to be
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* taken place between inputA samples and inputB samples. In the first stage of the
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* algorithm, the multiplications increase by one for every iteration.
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* In the second stage of the algorithm, srcBLen number of multiplications are done.
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* In the third stage of the algorithm, the multiplications decrease by one
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* for every iteration. */
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/* The algorithm is implemented in three stages.
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The loop counters of each stage is initiated here. */
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blockSize1 = srcBLen - 1U;
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blockSize2 = srcALen - (srcBLen - 1U);
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blockSize3 = blockSize1;
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/* --------------------------
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* Initializations of stage1
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* -------------------------*/
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/* sum = x[0] * y[0]
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* sum = x[0] * y[1] + x[1] * y[0]
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* ....
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* sum = x[0] * y[srcBlen - 1] + x[1] * y[srcBlen - 2] +...+ x[srcBLen - 1] * y[0]
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*/
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/* In this stage the MAC operations are increased by 1 for every iteration.
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The count variable holds the number of MAC operations performed */
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count = 1U;
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/* Working pointer of inputA */
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px = pIn1;
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/* Working pointer of inputB */
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py = pIn2;
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/* ------------------------
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* Stage1 process
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* ----------------------*/
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/* The first stage starts here */
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while (blockSize1 > 0U)
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{
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/* Accumulator is made zero for every iteration */
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sum = 0.0f;
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#if defined (ARM_MATH_LOOPUNROLL)
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/* Loop unrolling: Compute 4 outputs at a time */
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k = count >> 2U;
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while (k > 0U)
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{
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/* x[0] * y[srcBLen - 1] */
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sum += *px++ * *py--;
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/* x[1] * y[srcBLen - 2] */
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sum += *px++ * *py--;
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/* x[2] * y[srcBLen - 3] */
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sum += *px++ * *py--;
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/* x[3] * y[srcBLen - 4] */
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sum += *px++ * *py--;
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/* Decrement loop counter */
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k--;
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}
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/* Loop unrolling: Compute remaining outputs */
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k = count % 0x4U;
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#else
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/* Initialize k with number of samples */
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k = count;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (k > 0U)
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{
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/* Perform the multiply-accumulate */
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sum += *px++ * *py--;
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/* Decrement loop counter */
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k--;
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}
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/* Store the result in the accumulator in the destination buffer. */
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*pOut++ = sum;
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/* Update the inputA and inputB pointers for next MAC calculation */
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py = pIn2 + count;
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px = pIn1;
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/* Increment MAC count */
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count++;
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/* Decrement loop counter */
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blockSize1--;
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}
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/* --------------------------
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* Initializations of stage2
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* ------------------------*/
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/* sum = x[0] * y[srcBLen-1] + x[1] * y[srcBLen-2] +...+ x[srcBLen-1] * y[0]
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* sum = x[1] * y[srcBLen-1] + x[2] * y[srcBLen-2] +...+ x[srcBLen] * y[0]
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* ....
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* sum = x[srcALen-srcBLen-2] * y[srcBLen-1] + x[srcALen] * y[srcBLen-2] +...+ x[srcALen-1] * y[0]
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*/
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/* Working pointer of inputA */
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px = pIn1;
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/* Working pointer of inputB */
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pSrc2 = pIn2 + (srcBLen - 1U);
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py = pSrc2;
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/* count is index by which the pointer pIn1 to be incremented */
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count = 0U;
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/* -------------------
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* Stage2 process
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* ------------------*/
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/* Stage2 depends on srcBLen as in this stage srcBLen number of MACS are performed.
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* So, to loop unroll over blockSize2,
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* srcBLen should be greater than or equal to 4 */
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if (srcBLen >= 4U)
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{
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#if defined (ARM_MATH_LOOPUNROLL)
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/* Loop unrolling: Compute 4 outputs at a time */
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blkCnt = blockSize2 >> 2U;
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while (blkCnt > 0U)
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{
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/* Set all accumulators to zero */
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acc0 = 0.0f;
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acc1 = 0.0f;
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acc2 = 0.0f;
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acc3 = 0.0f;
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/* read x[0], x[1], x[2] samples */
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x0 = *px++;
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x1 = *px++;
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x2 = *px++;
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/* Apply loop unrolling and compute 4 MACs simultaneously. */
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k = srcBLen >> 2U;
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/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
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** a second loop below computes MACs for the remaining 1 to 3 samples. */
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do
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{
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/* Read y[srcBLen - 1] sample */
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c0 = *py--;
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/* Read x[3] sample */
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x3 = *(px);
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/* Perform the multiply-accumulate */
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/* acc0 += x[0] * y[srcBLen - 1] */
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acc0 += x0 * c0;
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/* acc1 += x[1] * y[srcBLen - 1] */
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acc1 += x1 * c0;
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/* acc2 += x[2] * y[srcBLen - 1] */
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acc2 += x2 * c0;
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/* acc3 += x[3] * y[srcBLen - 1] */
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acc3 += x3 * c0;
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/* Read y[srcBLen - 2] sample */
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c0 = *py--;
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/* Read x[4] sample */
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x0 = *(px + 1U);
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/* Perform the multiply-accumulate */
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/* acc0 += x[1] * y[srcBLen - 2] */
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acc0 += x1 * c0;
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/* acc1 += x[2] * y[srcBLen - 2] */
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acc1 += x2 * c0;
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/* acc2 += x[3] * y[srcBLen - 2] */
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acc2 += x3 * c0;
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/* acc3 += x[4] * y[srcBLen - 2] */
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acc3 += x0 * c0;
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/* Read y[srcBLen - 3] sample */
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c0 = *py--;
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/* Read x[5] sample */
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x1 = *(px + 2U);
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/* Perform the multiply-accumulate */
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/* acc0 += x[2] * y[srcBLen - 3] */
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acc0 += x2 * c0;
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/* acc1 += x[3] * y[srcBLen - 2] */
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acc1 += x3 * c0;
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/* acc2 += x[4] * y[srcBLen - 2] */
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acc2 += x0 * c0;
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/* acc3 += x[5] * y[srcBLen - 2] */
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acc3 += x1 * c0;
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/* Read y[srcBLen - 4] sample */
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c0 = *py--;
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/* Read x[6] sample */
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x2 = *(px + 3U);
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px += 4U;
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/* Perform the multiply-accumulate */
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/* acc0 += x[3] * y[srcBLen - 4] */
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acc0 += x3 * c0;
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/* acc1 += x[4] * y[srcBLen - 4] */
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acc1 += x0 * c0;
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/* acc2 += x[5] * y[srcBLen - 4] */
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acc2 += x1 * c0;
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/* acc3 += x[6] * y[srcBLen - 4] */
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acc3 += x2 * c0;
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} while (--k);
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/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
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** No loop unrolling is used. */
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k = srcBLen % 0x4U;
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while (k > 0U)
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{
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/* Read y[srcBLen - 5] sample */
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c0 = *py--;
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/* Read x[7] sample */
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x3 = *px++;
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/* Perform the multiply-accumulate */
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/* acc0 += x[4] * y[srcBLen - 5] */
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acc0 += x0 * c0;
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/* acc1 += x[5] * y[srcBLen - 5] */
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acc1 += x1 * c0;
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/* acc2 += x[6] * y[srcBLen - 5] */
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acc2 += x2 * c0;
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/* acc3 += x[7] * y[srcBLen - 5] */
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acc3 += x3 * c0;
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/* Reuse the present samples for the next MAC */
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x0 = x1;
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x1 = x2;
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x2 = x3;
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/* Decrement the loop counter */
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k--;
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}
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/* Store the result in the accumulator in the destination buffer. */
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*pOut++ = acc0;
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*pOut++ = acc1;
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*pOut++ = acc2;
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*pOut++ = acc3;
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/* Increment the pointer pIn1 index, count by 4 */
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count += 4U;
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/* Update the inputA and inputB pointers for next MAC calculation */
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px = pIn1 + count;
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py = pSrc2;
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/* Decrement loop counter */
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blkCnt--;
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}
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/* Loop unrolling: Compute remaining outputs */
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blkCnt = blockSize2 % 0x4U;
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#else
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/* Initialize blkCnt with number of samples */
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blkCnt = blockSize2;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (blkCnt > 0U)
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{
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/* Accumulator is made zero for every iteration */
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sum = 0.0f;
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#if defined (ARM_MATH_LOOPUNROLL)
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/* Loop unrolling: Compute 4 outputs at a time */
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k = srcBLen >> 2U;
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while (k > 0U)
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{
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/* Perform the multiply-accumulate */
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sum += *px++ * *py--;
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sum += *px++ * *py--;
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sum += *px++ * *py--;
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sum += *px++ * *py--;
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/* Decrement loop counter */
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k--;
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}
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/* Loop unrolling: Compute remaining outputs */
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k = srcBLen % 0x4U;
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#else
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/* Initialize blkCnt with number of samples */
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k = srcBLen;
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#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
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while (k > 0U)
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{
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/* Perform the multiply-accumulate */
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sum += *px++ * *py--;
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/* Decrement the loop counter */
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k--;
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}
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/* Store the result in the accumulator in the destination buffer. */
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*pOut++ = sum;
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/* Increment the MAC count */
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count++;
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/* Update the inputA and inputB pointers for next MAC calculation */
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px = pIn1 + count;
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py = pSrc2;
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/* Decrement the loop counter */
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blkCnt--;
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}
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}
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else
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{
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/* If the srcBLen is not a multiple of 4,
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* the blockSize2 loop cannot be unrolled by 4 */
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blkCnt = blockSize2;
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while (blkCnt > 0U)
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{
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/* Accumulator is made zero for every iteration */
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sum = 0.0f;
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/* srcBLen number of MACS should be performed */
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k = srcBLen;
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while (k > 0U)
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{
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/* Perform the multiply-accumulate */
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sum += *px++ * *py--;
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/* Decrement the loop counter */
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k--;
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}
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/* Store the result in the accumulator in the destination buffer. */
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*pOut++ = sum;
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/* Increment the MAC count */
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count++;
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/* Update the inputA and inputB pointers for next MAC calculation */
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px = pIn1 + count;
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py = pSrc2;
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/* Decrement the loop counter */
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blkCnt--;
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}
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}
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/* --------------------------
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* Initializations of stage3
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* -------------------------*/
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/* sum += x[srcALen-srcBLen+1] * y[srcBLen-1] + x[srcALen-srcBLen+2] * y[srcBLen-2] +...+ x[srcALen-1] * y[1]
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* sum += x[srcALen-srcBLen+2] * y[srcBLen-1] + x[srcALen-srcBLen+3] * y[srcBLen-2] +...+ x[srcALen-1] * y[2]
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* ....
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|
* sum += x[srcALen-2] * y[srcBLen-1] + x[srcALen-1] * y[srcBLen-2]
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* sum += x[srcALen-1] * y[srcBLen-1]
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|
*/
|
|
|
|
/* In this stage the MAC operations are decreased by 1 for every iteration.
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|
The blockSize3 variable holds the number of MAC operations performed */
|
|
|
|
/* Working pointer of inputA */
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|
pSrc1 = pIn1 + (srcALen - (srcBLen - 1U));
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|
px = pSrc1;
|
|
|
|
/* Working pointer of inputB */
|
|
pSrc2 = pIn2 + (srcBLen - 1U);
|
|
py = pSrc2;
|
|
|
|
/* -------------------
|
|
* Stage3 process
|
|
* ------------------*/
|
|
|
|
while (blockSize3 > 0U)
|
|
{
|
|
/* Accumulator is made zero for every iteration */
|
|
sum = 0.0f;
|
|
|
|
#if defined (ARM_MATH_LOOPUNROLL)
|
|
|
|
/* Loop unrolling: Compute 4 outputs at a time */
|
|
k = blockSize3 >> 2U;
|
|
|
|
while (k > 0U)
|
|
{
|
|
/* Perform the multiply-accumulate */
|
|
/* sum += x[srcALen - srcBLen + 1] * y[srcBLen - 1] */
|
|
sum += *px++ * *py--;
|
|
|
|
/* sum += x[srcALen - srcBLen + 2] * y[srcBLen - 2] */
|
|
sum += *px++ * *py--;
|
|
|
|
/* sum += x[srcALen - srcBLen + 3] * y[srcBLen - 3] */
|
|
sum += *px++ * *py--;
|
|
|
|
/* sum += x[srcALen - srcBLen + 4] * y[srcBLen - 4] */
|
|
sum += *px++ * *py--;
|
|
|
|
/* Decrement loop counter */
|
|
k--;
|
|
}
|
|
|
|
/* Loop unrolling: Compute remaining outputs */
|
|
k = blockSize3 % 0x4U;
|
|
|
|
#else
|
|
|
|
/* Initialize blkCnt with number of samples */
|
|
k = blockSize3;
|
|
|
|
#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
|
|
|
|
while (k > 0U)
|
|
{
|
|
/* Perform the multiply-accumulate */
|
|
/* sum += x[srcALen-1] * y[srcBLen-1] */
|
|
sum += *px++ * *py--;
|
|
|
|
/* Decrement loop counter */
|
|
k--;
|
|
}
|
|
|
|
/* Store the result in the accumulator in the destination buffer. */
|
|
*pOut++ = sum;
|
|
|
|
/* Update the inputA and inputB pointers for next MAC calculation */
|
|
px = ++pSrc1;
|
|
py = pSrc2;
|
|
|
|
/* Decrement the loop counter */
|
|
blockSize3--;
|
|
}
|
|
|
|
#else
|
|
/* alternate version for CM0_FAMILY */
|
|
|
|
const float32_t *pIn1 = pSrcA; /* InputA pointer */
|
|
const float32_t *pIn2 = pSrcB; /* InputB pointer */
|
|
float32_t sum; /* Accumulator */
|
|
uint32_t i, j; /* Loop counters */
|
|
|
|
/* Loop to calculate convolution for output length number of times */
|
|
for (i = 0U; i < (srcALen + srcBLen - 1U); i++)
|
|
{
|
|
/* Initialize sum with zero to carry out MAC operations */
|
|
sum = 0.0f;
|
|
|
|
/* Loop to perform MAC operations according to convolution equation */
|
|
for (j = 0U; j <= i; j++)
|
|
{
|
|
/* Check the array limitations */
|
|
if (((i - j) < srcBLen) && (j < srcALen))
|
|
{
|
|
/* z[i] += x[i-j] * y[j] */
|
|
sum += ( pIn1[j] * pIn2[i - j]);
|
|
}
|
|
}
|
|
|
|
/* Store the output in the destination buffer */
|
|
pDst[i] = sum;
|
|
}
|
|
|
|
#endif /* #if !defined(ARM_MATH_CM0_FAMILY) */
|
|
|
|
}
|
|
|
|
/**
|
|
@} end of Conv group
|
|
*/
|