/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_conv_partial_q15.c
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* Description: Partial convolution of Q15 sequences
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*
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* $Date: 27. January 2017
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* $Revision: V.1.5.1
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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) 2010-2017 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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* @addtogroup PartialConv
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* @{
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*/
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/**
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* @brief Partial convolution of Q15 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.
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* @param[in] firstIndex is the first output sample to start with.
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* @param[in] numPoints is the number of output points to be computed.
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* @return Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
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*
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* Refer to <code>arm_conv_partial_fast_q15()</code> for a faster but less precise version of this function for Cortex-M3 and Cortex-M4.
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*
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* \par
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* Refer the function <code>arm_conv_partial_opt_q15()</code> for a faster implementation of this function using scratch buffers.
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*
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*/
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arm_status arm_conv_partial_q15(
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q15_t * pSrcA,
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uint32_t srcALen,
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q15_t * pSrcB,
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uint32_t srcBLen,
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q15_t * pDst,
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uint32_t firstIndex,
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uint32_t numPoints)
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{
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#if (defined(ARM_MATH_CM7) || defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE)
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/* Run the below code for Cortex-M4 and Cortex-M3 */
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q15_t *pIn1; /* inputA pointer */
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q15_t *pIn2; /* inputB pointer */
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q15_t *pOut = pDst; /* output pointer */
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q63_t sum, acc0, acc1, acc2, acc3; /* Accumulator */
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q15_t *px; /* Intermediate inputA pointer */
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q15_t *py; /* Intermediate inputB pointer */
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q15_t *pSrc1, *pSrc2; /* Intermediate pointers */
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q31_t x0, x1, x2, x3, c0; /* Temporary input variables */
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uint32_t j, k, count, check, blkCnt;
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int32_t blockSize1, blockSize2, blockSize3; /* loop counter */
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arm_status status; /* status of Partial convolution */
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/* Check for range of output samples to be calculated */
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if ((firstIndex + numPoints) > ((srcALen + (srcBLen - 1U))))
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{
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/* Set status as ARM_MATH_ARGUMENT_ERROR */
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status = ARM_MATH_ARGUMENT_ERROR;
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}
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else
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{
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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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/* Conditions to check which loopCounter holds
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* the first and last indices of the output samples to be calculated. */
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check = firstIndex + numPoints;
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blockSize3 = ((int32_t)check > (int32_t)srcALen) ? (int32_t)check - (int32_t)srcALen : 0;
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blockSize3 = ((int32_t)firstIndex > (int32_t)srcALen - 1) ? blockSize3 - (int32_t)firstIndex + (int32_t)srcALen : blockSize3;
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blockSize1 = (((int32_t) srcBLen - 1) - (int32_t) firstIndex);
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blockSize1 = (blockSize1 > 0) ? ((check > (srcBLen - 1U)) ? blockSize1 :
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(int32_t) numPoints) : 0;
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blockSize2 = (int32_t) check - ((blockSize3 + blockSize1) +
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(int32_t) firstIndex);
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blockSize2 = (blockSize2 > 0) ? blockSize2 : 0;
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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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/* Set the output pointer to point to the firstIndex
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* of the output sample to be calculated. */
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pOut = pDst + firstIndex;
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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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Since the partial convolution starts from firstIndex
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Number of Macs to be performed is firstIndex + 1 */
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count = 1U + firstIndex;
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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 + firstIndex;
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py = pSrc2;
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/* ------------------------
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* Stage1 process
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* ----------------------*/
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/* For loop unrolling by 4, this stage is divided into two. */
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/* First part of this stage computes the MAC operations less than 4 */
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/* Second part of this stage computes the MAC operations greater than or equal to 4 */
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/* The first part of the stage starts here */
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while ((count < 4U) && (blockSize1 > 0))
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{
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/* Accumulator is made zero for every iteration */
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sum = 0;
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/* Loop over number of MAC operations between
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* inputA samples and inputB samples */
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k = count;
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while (k > 0U)
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{
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/* Perform the multiply-accumulates */
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sum = __SMLALD(*px++, *py--, sum);
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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++ = (q15_t) (__SSAT((sum >> 15), 16));
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/* Update the inputA and inputB pointers for next MAC calculation */
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py = ++pSrc2;
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px = pIn1;
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/* Increment the MAC count */
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count++;
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/* Decrement the loop counter */
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blockSize1--;
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}
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/* The second part of the stage starts here */
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/* The internal loop, over count, is unrolled by 4 */
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/* To, read the last two inputB samples using SIMD:
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* y[srcBLen] and y[srcBLen-1] coefficients, py is decremented by 1 */
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py = py - 1;
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while (blockSize1 > 0)
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{
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/* Accumulator is made zero for every iteration */
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sum = 0;
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/* Apply loop unrolling and compute 4 MACs simultaneously. */
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k = count >> 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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while (k > 0U)
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{
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/* Perform the multiply-accumulates */
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/* x[0], x[1] are multiplied with y[srcBLen - 1], y[srcBLen - 2] respectively */
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sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
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/* x[2], x[3] are multiplied with y[srcBLen - 3], y[srcBLen - 4] respectively */
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sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
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/* Decrement the loop counter */
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k--;
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}
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/* For the next MAC operations, the pointer py is used without SIMD
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* So, py is incremented by 1 */
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py = py + 1U;
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/* If the count 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 = count % 0x4U;
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while (k > 0U)
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{
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/* Perform the multiply-accumulates */
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sum = __SMLALD(*px++, *py--, sum);
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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++ = (q15_t) (__SSAT((sum >> 15), 16));
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/* Update the inputA and inputB pointers for next MAC calculation */
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py = ++pSrc2 - 1U;
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px = pIn1;
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/* Increment the MAC count */
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count++;
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/* Decrement the 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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if ((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
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{
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px = pIn1 + firstIndex - srcBLen + 1;
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}
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else
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{
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px = pIn1;
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}
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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 the 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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/* Loop unroll over blockSize2, by 4 */
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blkCnt = blockSize2 >> 2U;
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while (blkCnt > 0U)
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{
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py = py - 1U;
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/* Set all accumulators to zero */
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acc0 = 0;
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acc1 = 0;
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acc2 = 0;
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acc3 = 0;
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/* read x[0], x[1] samples */
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x0 = *__SIMD32(px);
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/* read x[1], x[2] samples */
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x1 = _SIMD32_OFFSET(px+1);
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px+= 2U;
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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 the last two inputB samples using SIMD:
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* y[srcBLen - 1] and y[srcBLen - 2] */
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c0 = *__SIMD32(py)--;
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/* acc0 += x[0] * y[srcBLen - 1] + x[1] * y[srcBLen - 2] */
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acc0 = __SMLALDX(x0, c0, acc0);
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/* acc1 += x[1] * y[srcBLen - 1] + x[2] * y[srcBLen - 2] */
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acc1 = __SMLALDX(x1, c0, acc1);
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/* Read x[2], x[3] */
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x2 = *__SIMD32(px);
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/* Read x[3], x[4] */
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x3 = _SIMD32_OFFSET(px+1);
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/* acc2 += x[2] * y[srcBLen - 1] + x[3] * y[srcBLen - 2] */
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acc2 = __SMLALDX(x2, c0, acc2);
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/* acc3 += x[3] * y[srcBLen - 1] + x[4] * y[srcBLen - 2] */
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acc3 = __SMLALDX(x3, c0, acc3);
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/* Read y[srcBLen - 3] and y[srcBLen - 4] */
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c0 = *__SIMD32(py)--;
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/* acc0 += x[2] * y[srcBLen - 3] + x[3] * y[srcBLen - 4] */
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acc0 = __SMLALDX(x2, c0, acc0);
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/* acc1 += x[3] * y[srcBLen - 3] + x[4] * y[srcBLen - 4] */
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acc1 = __SMLALDX(x3, c0, acc1);
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/* Read x[4], x[5] */
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x0 = _SIMD32_OFFSET(px+2);
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/* Read x[5], x[6] */
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x1 = _SIMD32_OFFSET(px+3);
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px += 4U;
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/* acc2 += x[4] * y[srcBLen - 3] + x[5] * y[srcBLen - 4] */
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acc2 = __SMLALDX(x0, c0, acc2);
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/* acc3 += x[5] * y[srcBLen - 3] + x[6] * y[srcBLen - 4] */
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acc3 = __SMLALDX(x1, c0, acc3);
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} while (--k);
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/* For the next MAC operations, SIMD is not used
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* So, the 16 bit pointer if inputB, py is updated */
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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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if (k == 1U)
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{
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/* Read y[srcBLen - 5] */
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c0 = *(py+1);
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#ifdef ARM_MATH_BIG_ENDIAN
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c0 = c0 << 16U;
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#else
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c0 = c0 & 0x0000FFFF;
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#endif /* #ifdef ARM_MATH_BIG_ENDIAN */
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/* Read x[7] */
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x3 = *__SIMD32(px);
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px++;
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/* Perform the multiply-accumulates */
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acc0 = __SMLALD(x0, c0, acc0);
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acc1 = __SMLALD(x1, c0, acc1);
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acc2 = __SMLALDX(x1, c0, acc2);
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acc3 = __SMLALDX(x3, c0, acc3);
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}
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if (k == 2U)
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{
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/* Read y[srcBLen - 5], y[srcBLen - 6] */
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c0 = _SIMD32_OFFSET(py);
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/* Read x[7], x[8] */
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x3 = *__SIMD32(px);
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/* Read x[9] */
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x2 = _SIMD32_OFFSET(px+1);
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px += 2U;
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/* Perform the multiply-accumulates */
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acc0 = __SMLALDX(x0, c0, acc0);
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acc1 = __SMLALDX(x1, c0, acc1);
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acc2 = __SMLALDX(x3, c0, acc2);
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acc3 = __SMLALDX(x2, c0, acc3);
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}
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if (k == 3U)
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{
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/* Read y[srcBLen - 5], y[srcBLen - 6] */
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c0 = _SIMD32_OFFSET(py);
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/* Read x[7], x[8] */
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x3 = *__SIMD32(px);
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/* Read x[9] */
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x2 = _SIMD32_OFFSET(px+1);
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/* Perform the multiply-accumulates */
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acc0 = __SMLALDX(x0, c0, acc0);
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acc1 = __SMLALDX(x1, c0, acc1);
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acc2 = __SMLALDX(x3, c0, acc2);
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acc3 = __SMLALDX(x2, c0, acc3);
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c0 = *(py-1);
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#ifdef ARM_MATH_BIG_ENDIAN
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c0 = c0 << 16U;
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#else
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c0 = c0 & 0x0000FFFF;
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#endif /* #ifdef ARM_MATH_BIG_ENDIAN */
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/* Read x[10] */
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x3 = _SIMD32_OFFSET(px+2);
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px += 3U;
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/* Perform the multiply-accumulates */
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acc0 = __SMLALDX(x1, c0, acc0);
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acc1 = __SMLALD(x2, c0, acc1);
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acc2 = __SMLALDX(x2, c0, acc2);
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acc3 = __SMLALDX(x3, c0, acc3);
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}
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/* Store the results in the accumulators in the destination buffer. */
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#ifndef ARM_MATH_BIG_ENDIAN
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*__SIMD32(pOut)++ =
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__PKHBT(__SSAT((acc0 >> 15), 16), __SSAT((acc1 >> 15), 16), 16);
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*__SIMD32(pOut)++ =
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__PKHBT(__SSAT((acc2 >> 15), 16), __SSAT((acc3 >> 15), 16), 16);
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#else
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*__SIMD32(pOut)++ =
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__PKHBT(__SSAT((acc1 >> 15), 16), __SSAT((acc0 >> 15), 16), 16);
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*__SIMD32(pOut)++ =
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__PKHBT(__SSAT((acc3 >> 15), 16), __SSAT((acc2 >> 15), 16), 16);
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#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
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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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if ((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
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{
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px = pIn1 + firstIndex - srcBLen + 1 + count;
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}
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else
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{
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px = pIn1 + count;
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}
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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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/* If the blockSize2 is not a multiple of 4, compute any remaining output samples here.
|
** No loop unrolling is used. */
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blkCnt = (uint32_t) blockSize2 % 0x4U;
|
|
while (blkCnt > 0U)
|
{
|
/* Accumulator is made zero for every iteration */
|
sum = 0;
|
|
/* Apply loop unrolling and compute 4 MACs simultaneously. */
|
k = srcBLen >> 2U;
|
|
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
|
** a second loop below computes MACs for the remaining 1 to 3 samples. */
|
while (k > 0U)
|
{
|
/* Perform the multiply-accumulates */
|
sum += (q63_t) ((q31_t) * px++ * *py--);
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sum += (q63_t) ((q31_t) * px++ * *py--);
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sum += (q63_t) ((q31_t) * px++ * *py--);
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sum += (q63_t) ((q31_t) * px++ * *py--);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
|
** No loop unrolling is used. */
|
k = srcBLen % 0x4U;
|
|
while (k > 0U)
|
{
|
/* Perform the multiply-accumulates */
|
sum += (q63_t) ((q31_t) * px++ * *py--);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* Store the result in the accumulator in the destination buffer. */
|
*pOut++ = (q15_t) (__SSAT(sum >> 15, 16));
|
|
/* Increment the pointer pIn1 index, count by 1 */
|
count++;
|
|
/* Update the inputA and inputB pointers for next MAC calculation */
|
if ((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
|
{
|
px = pIn1 + firstIndex - srcBLen + 1 + count;
|
}
|
else
|
{
|
px = pIn1 + count;
|
}
|
py = pSrc2;
|
|
/* Decrement the loop counter */
|
blkCnt--;
|
}
|
}
|
else
|
{
|
/* If the srcBLen is not a multiple of 4,
|
* the blockSize2 loop cannot be unrolled by 4 */
|
blkCnt = (uint32_t) blockSize2;
|
|
while (blkCnt > 0U)
|
{
|
/* Accumulator is made zero for every iteration */
|
sum = 0;
|
|
/* srcBLen number of MACS should be performed */
|
k = srcBLen;
|
|
while (k > 0U)
|
{
|
/* Perform the multiply-accumulate */
|
sum += (q63_t) ((q31_t) * px++ * *py--);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* Store the result in the accumulator in the destination buffer. */
|
*pOut++ = (q15_t) (__SSAT(sum >> 15, 16));
|
|
/* Increment the MAC count */
|
count++;
|
|
/* Update the inputA and inputB pointers for next MAC calculation */
|
if ((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
|
{
|
px = pIn1 + firstIndex - srcBLen + 1 + count;
|
}
|
else
|
{
|
px = pIn1 + count;
|
}
|
py = pSrc2;
|
|
/* Decrement the loop counter */
|
blkCnt--;
|
}
|
}
|
|
|
/* --------------------------
|
* Initializations of stage3
|
* -------------------------*/
|
|
/* sum += x[srcALen-srcBLen+1] * y[srcBLen-1] + x[srcALen-srcBLen+2] * y[srcBLen-2] +...+ x[srcALen-1] * y[1]
|
* sum += x[srcALen-srcBLen+2] * y[srcBLen-1] + x[srcALen-srcBLen+3] * y[srcBLen-2] +...+ x[srcALen-1] * y[2]
|
* ....
|
* sum += x[srcALen-2] * y[srcBLen-1] + x[srcALen-1] * y[srcBLen-2]
|
* sum += x[srcALen-1] * y[srcBLen-1]
|
*/
|
|
/* In this stage the MAC operations are decreased by 1 for every iteration.
|
The count variable holds the number of MAC operations performed */
|
count = srcBLen - 1U;
|
|
/* Working pointer of inputA */
|
pSrc1 = (pIn1 + srcALen) - (srcBLen - 1U);
|
px = pSrc1;
|
|
/* Working pointer of inputB */
|
pSrc2 = pIn2 + (srcBLen - 1U);
|
pIn2 = pSrc2 - 1U;
|
py = pIn2;
|
|
/* -------------------
|
* Stage3 process
|
* ------------------*/
|
|
/* For loop unrolling by 4, this stage is divided into two. */
|
/* First part of this stage computes the MAC operations greater than 4 */
|
/* Second part of this stage computes the MAC operations less than or equal to 4 */
|
|
/* The first part of the stage starts here */
|
j = count >> 2U;
|
|
while ((j > 0U) && (blockSize3 > 0))
|
{
|
/* Accumulator is made zero for every iteration */
|
sum = 0;
|
|
/* Apply loop unrolling and compute 4 MACs simultaneously. */
|
k = count >> 2U;
|
|
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
|
** a second loop below computes MACs for the remaining 1 to 3 samples. */
|
while (k > 0U)
|
{
|
/* x[srcALen - srcBLen + 1], x[srcALen - srcBLen + 2] are multiplied
|
* with y[srcBLen - 1], y[srcBLen - 2] respectively */
|
sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
|
/* x[srcALen - srcBLen + 3], x[srcALen - srcBLen + 4] are multiplied
|
* with y[srcBLen - 3], y[srcBLen - 4] respectively */
|
sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* For the next MAC operations, the pointer py is used without SIMD
|
* So, py is incremented by 1 */
|
py = py + 1U;
|
|
/* If the count is not a multiple of 4, compute any remaining MACs here.
|
** No loop unrolling is used. */
|
k = count % 0x4U;
|
|
while (k > 0U)
|
{
|
/* sum += x[srcALen - srcBLen + 5] * y[srcBLen - 5] */
|
sum = __SMLALD(*px++, *py--, sum);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* Store the result in the accumulator in the destination buffer. */
|
*pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
|
|
/* Update the inputA and inputB pointers for next MAC calculation */
|
px = ++pSrc1;
|
py = pIn2;
|
|
/* Decrement the MAC count */
|
count--;
|
|
/* Decrement the loop counter */
|
blockSize3--;
|
|
j--;
|
}
|
|
/* The second part of the stage starts here */
|
/* SIMD is not used for the next MAC operations,
|
* so pointer py is updated to read only one sample at a time */
|
py = py + 1U;
|
|
while (blockSize3 > 0)
|
{
|
/* Accumulator is made zero for every iteration */
|
sum = 0;
|
|
/* Apply loop unrolling and compute 4 MACs simultaneously. */
|
k = count;
|
|
while (k > 0U)
|
{
|
/* Perform the multiply-accumulates */
|
/* sum += x[srcALen-1] * y[srcBLen-1] */
|
sum = __SMLALD(*px++, *py--, sum);
|
|
/* Decrement the loop counter */
|
k--;
|
}
|
|
/* Store the result in the accumulator in the destination buffer. */
|
*pOut++ = (q15_t) (__SSAT((sum >> 15), 16));
|
|
/* Update the inputA and inputB pointers for next MAC calculation */
|
px = ++pSrc1;
|
py = pSrc2;
|
|
/* Decrement the MAC count */
|
count--;
|
|
/* Decrement the loop counter */
|
blockSize3--;
|
}
|
|
/* set status as ARM_MATH_SUCCESS */
|
status = ARM_MATH_SUCCESS;
|
}
|
|
/* Return to application */
|
return (status);
|
|
#else
|
|
/* Run the below code for Cortex-M0 */
|
|
q15_t *pIn1 = pSrcA; /* inputA pointer */
|
q15_t *pIn2 = pSrcB; /* inputB pointer */
|
q63_t sum; /* Accumulator */
|
uint32_t i, j; /* loop counters */
|
arm_status status; /* status of Partial convolution */
|
|
/* Check for range of output samples to be calculated */
|
if ((firstIndex + numPoints) > ((srcALen + (srcBLen - 1U))))
|
{
|
/* Set status as ARM_ARGUMENT_ERROR */
|
status = ARM_MATH_ARGUMENT_ERROR;
|
}
|
else
|
{
|
/* Loop to calculate convolution for output length number of values */
|
for (i = firstIndex; i <= (firstIndex + numPoints - 1); i++)
|
{
|
/* Initialize sum with zero to carry on MAC operations */
|
sum = 0;
|
|
/* Loop to perform MAC operations according to convolution equation */
|
for (j = 0; j <= i; j++)
|
{
|
/* Check the array limitations */
|
if (((i - j) < srcBLen) && (j < srcALen))
|
{
|
/* z[i] += x[i-j] * y[j] */
|
sum += ((q31_t) pIn1[j] * (pIn2[i - j]));
|
}
|
}
|
|
/* Store the output in the destination buffer */
|
pDst[i] = (q15_t) __SSAT((sum >> 15U), 16U);
|
}
|
/* set status as ARM_SUCCESS as there are no argument errors */
|
status = ARM_MATH_SUCCESS;
|
}
|
return (status);
|
|
#endif /* #if (defined(ARM_MATH_CM7) || defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE) */
|
|
}
|
|
/**
|
* @} end of PartialConv group
|
*/
|
