arm_conv_partial_q15.c

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/* ----------------------------------------------------------------------   
* Copyright (C) 2010-2014 ARM Limited. All rights reserved.   
*   
* $Date:        19. March 2015
* $Revision:    V.1.4.5
*   
* Project:      CMSIS DSP Library   
* Title:        arm_conv_partial_q15.c   
*   
* Description:  Partial convolution of Q15 sequences.  
*   
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
* 
* Redistribution and use in source and binary forms, with or without 
* modification, are permitted provided that the following conditions
* are met:
*   - Redistributions of source code must retain the above copyright
*     notice, this list of conditions and the following disclaimer.
*   - Redistributions in binary form must reproduce the above copyright
*     notice, this list of conditions and the following disclaimer in
*     the documentation and/or other materials provided with the 
*     distribution.
*   - Neither the name of ARM LIMITED nor the names of its contributors
*     may be used to endorse or promote products derived from this
*     software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.  
* -------------------------------------------------------------------- */

#include "arm_math.h"

arm_status arm_conv_partial_q15(
  q15_t * pSrcA,
  uint32_t srcALen,
  q15_t * pSrcB,
  uint32_t srcBLen,
  q15_t * pDst,
  uint32_t firstIndex,
  uint32_t numPoints)
{

#if (defined(ARM_MATH_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE)

  /* Run the below code for Cortex-M4 and Cortex-M3 */

  q15_t *pIn1;                                   /* inputA pointer               */
  q15_t *pIn2;                                   /* inputB pointer               */
  q15_t *pOut = pDst;                            /* output pointer               */
  q63_t sum, acc0, acc1, acc2, acc3;             /* Accumulator                  */
  q15_t *px;                                     /* Intermediate inputA pointer  */
  q15_t *py;                                     /* Intermediate inputB pointer  */
  q15_t *pSrc1, *pSrc2;                          /* Intermediate pointers        */
  q31_t x0, x1, x2, x3, c0;                      /* Temporary input variables */
  uint32_t j, k, count, check, blkCnt;
  int32_t blockSize1, blockSize2, blockSize3;    /* loop counter                 */
  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_MATH_ARGUMENT_ERROR */
    status = ARM_MATH_ARGUMENT_ERROR;
  }
  else
  {

    /* The algorithm implementation is based on the lengths of the inputs. */
    /* srcB is always made to slide across srcA. */
    /* So srcBLen is always considered as shorter or equal to srcALen */
    if(srcALen >= srcBLen)
    {
      /* Initialization of inputA pointer */
      pIn1 = pSrcA;

      /* Initialization of inputB pointer */
      pIn2 = pSrcB;
    }
    else
    {
      /* Initialization of inputA pointer */
      pIn1 = pSrcB;

      /* Initialization of inputB pointer */
      pIn2 = pSrcA;

      /* srcBLen is always considered as shorter or equal to srcALen */
      j = srcBLen;
      srcBLen = srcALen;
      srcALen = j;
    }

    /* Conditions to check which loopCounter holds   
     * the first and last indices of the output samples to be calculated. */
    check = firstIndex + numPoints;
    blockSize3 = ((int32_t)check > (int32_t)srcALen) ? (int32_t)check - (int32_t)srcALen : 0;
    blockSize3 = ((int32_t)firstIndex > (int32_t)srcALen - 1) ? blockSize3 - (int32_t)firstIndex + (int32_t)srcALen : blockSize3;
    blockSize1 = (((int32_t) srcBLen - 1) - (int32_t) firstIndex);
    blockSize1 = (blockSize1 > 0) ? ((check > (srcBLen - 1u)) ? blockSize1 :
                                     (int32_t) numPoints) : 0;
    blockSize2 = (int32_t) check - ((blockSize3 + blockSize1) +
                                    (int32_t) firstIndex);
    blockSize2 = (blockSize2 > 0) ? blockSize2 : 0;

    /* 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] */
    /* The function is internally   
     * divided into three stages according to the number of multiplications that has to be   
     * taken place between inputA samples and inputB samples. In the first stage of the   
     * algorithm, the multiplications increase by one for every iteration.   
     * In the second stage of the algorithm, srcBLen number of multiplications are done.   
     * In the third stage of the algorithm, the multiplications decrease by one   
     * for every iteration. */

    /* Set the output pointer to point to the firstIndex   
     * of the output sample to be calculated. */
    pOut = pDst + firstIndex;

    /* --------------------------   
     * Initializations of stage1   
     * -------------------------*/

    /* sum = x[0] * y[0]   
     * sum = x[0] * y[1] + x[1] * y[0]   
     * ....   
     * sum = x[0] * y[srcBlen - 1] + x[1] * y[srcBlen - 2] +...+ x[srcBLen - 1] * y[0]   
     */

    /* In this stage the MAC operations are increased by 1 for every iteration.   
       The count variable holds the number of MAC operations performed.   
       Since the partial convolution starts from firstIndex   
       Number of Macs to be performed is firstIndex + 1 */
    count = 1u + firstIndex;

    /* Working pointer of inputA */
    px = pIn1;

    /* Working pointer of inputB */
    pSrc2 = pIn2 + firstIndex;
    py = pSrc2;

    /* ------------------------   
     * Stage1 process   
     * ----------------------*/

    /* For loop unrolling by 4, this stage is divided into two. */
    /* First part of this stage computes the MAC operations less than 4 */
    /* Second part of this stage computes the MAC operations greater than or equal to 4 */

    /* The first part of the stage starts here */
    while((count < 4u) && (blockSize1 > 0))
    {
      /* Accumulator is made zero for every iteration */
      sum = 0;

      /* Loop over number of MAC operations between   
       * inputA samples and inputB samples */
      k = count;

      while(k > 0u)
      {
        /* Perform the multiply-accumulates */
        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 */
      py = ++pSrc2;
      px = pIn1;

      /* Increment the MAC count */
      count++;

      /* Decrement the loop counter */
      blockSize1--;
    }

    /* The second part of the stage starts here */
    /* The internal loop, over count, is unrolled by 4 */
    /* To, read the last two inputB samples using SIMD:   
     * y[srcBLen] and y[srcBLen-1] coefficients, py is decremented by 1 */
    py = py - 1;

    while(blockSize1 > 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)
      {
        /* Perform the multiply-accumulates */
        /* x[0], x[1] are multiplied with y[srcBLen - 1], y[srcBLen - 2] respectively */
        sum = __SMLALDX(*__SIMD32(px)++, *__SIMD32(py)--, sum);
        /* x[2], x[3] 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)
      {
        /* Perform the multiply-accumulates */
        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 */
      py = ++pSrc2 - 1u;
      px = pIn1;

      /* Increment the MAC count */
      count++;

      /* Decrement the loop counter */
      blockSize1--;
    }

    /* --------------------------   
     * Initializations of stage2   
     * ------------------------*/

    /* sum = x[0] * y[srcBLen-1] + x[1] * y[srcBLen-2] +...+ x[srcBLen-1] * y[0]   
     * sum = x[1] * y[srcBLen-1] + x[2] * y[srcBLen-2] +...+ x[srcBLen] * y[0]   
     * ....   
     * sum = x[srcALen-srcBLen-2] * y[srcBLen-1] + x[srcALen] * y[srcBLen-2] +...+ x[srcALen-1] * y[0]   
     */

    /* Working pointer of inputA */
    if((int32_t)firstIndex - (int32_t)srcBLen + 1 > 0)
    {
      px = pIn1 + firstIndex - srcBLen + 1;
    }
    else
    {
      px = pIn1;
    }

    /* Working pointer of inputB */
    pSrc2 = pIn2 + (srcBLen - 1u);
    py = pSrc2;

  /* count is the index by which the pointer pIn1 to be incremented */
  count = 0u;


  /* --------------------   
   * Stage2 process   
   * -------------------*/

  /* Stage2 depends on srcBLen as in this stage srcBLen number of MACS are performed.   
   * So, to loop unroll over blockSize2,   
   * srcBLen should be greater than or equal to 4 */
  if(srcBLen >= 4u)
  {
    /* Loop unroll over blockSize2, by 4 */
    blkCnt = blockSize2 >> 2u;

    while(blkCnt > 0u)
    {
      py = py - 1u;

      /* Set all accumulators to zero */
      acc0 = 0;
      acc1 = 0;
      acc2 = 0;
      acc3 = 0;


      /* read x[0], x[1] samples */
      x0 = *__SIMD32(px);
      /* read x[1], x[2] samples */
      x1 = _SIMD32_OFFSET(px+1);
      px+= 2u;


      /* 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. */
      do
      {
        /* Read the last two inputB samples using SIMD:   
         * y[srcBLen - 1] and y[srcBLen - 2] */
        c0 = *__SIMD32(py)--;

        /* acc0 +=  x[0] * y[srcBLen - 1] + x[1] * y[srcBLen - 2] */
        acc0 = __SMLALDX(x0, c0, acc0);

        /* acc1 +=  x[1] * y[srcBLen - 1] + x[2] * y[srcBLen - 2] */
        acc1 = __SMLALDX(x1, c0, acc1);

        /* Read x[2], x[3] */
        x2 = *__SIMD32(px);

        /* Read x[3], x[4] */
        x3 = _SIMD32_OFFSET(px+1);

        /* acc2 +=  x[2] * y[srcBLen - 1] + x[3] * y[srcBLen - 2] */
        acc2 = __SMLALDX(x2, c0, acc2);

        /* acc3 +=  x[3] * y[srcBLen - 1] + x[4] * y[srcBLen - 2] */
        acc3 = __SMLALDX(x3, c0, acc3);

        /* Read y[srcBLen - 3] and y[srcBLen - 4] */
        c0 = *__SIMD32(py)--;

        /* acc0 +=  x[2] * y[srcBLen - 3] + x[3] * y[srcBLen - 4] */
        acc0 = __SMLALDX(x2, c0, acc0);

        /* acc1 +=  x[3] * y[srcBLen - 3] + x[4] * y[srcBLen - 4] */
        acc1 = __SMLALDX(x3, c0, acc1);

        /* Read x[4], x[5] */
        x0 = _SIMD32_OFFSET(px+2);

        /* Read x[5], x[6] */
        x1 = _SIMD32_OFFSET(px+3);
        px += 4u;

        /* acc2 +=  x[4] * y[srcBLen - 3] + x[5] * y[srcBLen - 4] */
        acc2 = __SMLALDX(x0, c0, acc2);

        /* acc3 +=  x[5] * y[srcBLen - 3] + x[6] * y[srcBLen - 4] */
        acc3 = __SMLALDX(x1, c0, acc3);

      } while(--k);

      /* For the next MAC operations, SIMD is not used   
       * So, the 16 bit pointer if inputB, py is updated */

      /* If the srcBLen is not a multiple of 4, compute any remaining MACs here.   
       ** No loop unrolling is used. */
      k = srcBLen % 0x4u;

      if(k == 1u)
      {
        /* Read y[srcBLen - 5] */
        c0 = *(py+1);

#ifdef  ARM_MATH_BIG_ENDIAN

        c0 = c0 << 16u;

#else

        c0 = c0 & 0x0000FFFF;

#endif /*      #ifdef  ARM_MATH_BIG_ENDIAN     */

        /* Read x[7] */
        x3 = *__SIMD32(px);
        px++;

        /* Perform the multiply-accumulates */
        acc0 = __SMLALD(x0, c0, acc0);
        acc1 = __SMLALD(x1, c0, acc1);
        acc2 = __SMLALDX(x1, c0, acc2);
        acc3 = __SMLALDX(x3, c0, acc3);
      }

      if(k == 2u)
      {
        /* Read y[srcBLen - 5], y[srcBLen - 6] */
        c0 = _SIMD32_OFFSET(py);

        /* Read x[7], x[8] */
        x3 = *__SIMD32(px);

        /* Read x[9] */
        x2 = _SIMD32_OFFSET(px+1);
        px += 2u;

        /* Perform the multiply-accumulates */
        acc0 = __SMLALDX(x0, c0, acc0);
        acc1 = __SMLALDX(x1, c0, acc1);
        acc2 = __SMLALDX(x3, c0, acc2);
        acc3 = __SMLALDX(x2, c0, acc3);
      }

      if(k == 3u)
      {
        /* Read y[srcBLen - 5], y[srcBLen - 6] */
        c0 = _SIMD32_OFFSET(py);

        /* Read x[7], x[8] */
        x3 = *__SIMD32(px);

        /* Read x[9] */
        x2 = _SIMD32_OFFSET(px+1);

        /* Perform the multiply-accumulates */
        acc0 = __SMLALDX(x0, c0, acc0);
        acc1 = __SMLALDX(x1, c0, acc1);
        acc2 = __SMLALDX(x3, c0, acc2);
        acc3 = __SMLALDX(x2, c0, acc3);

        c0 = *(py-1);

#ifdef  ARM_MATH_BIG_ENDIAN

        c0 = c0 << 16u;
#else

        c0 = c0 & 0x0000FFFF;
#endif /*      #ifdef  ARM_MATH_BIG_ENDIAN     */

        /* Read x[10] */
        x3 =  _SIMD32_OFFSET(px+2);
        px += 3u;

        /* Perform the multiply-accumulates */
        acc0 = __SMLALDX(x1, c0, acc0);
        acc1 = __SMLALD(x2, c0, acc1);
        acc2 = __SMLALDX(x2, c0, acc2);
        acc3 = __SMLALDX(x3, c0, acc3);
      }


      /* Store the results in the accumulators in the destination buffer. */

#ifndef  ARM_MATH_BIG_ENDIAN

      *__SIMD32(pOut)++ =
        __PKHBT(__SSAT((acc0 >> 15), 16), __SSAT((acc1 >> 15), 16), 16);
      *__SIMD32(pOut)++ =
        __PKHBT(__SSAT((acc2 >> 15), 16), __SSAT((acc3 >> 15), 16), 16);

#else

      *__SIMD32(pOut)++ =
        __PKHBT(__SSAT((acc1 >> 15), 16), __SSAT((acc0 >> 15), 16), 16);
      *__SIMD32(pOut)++ =
        __PKHBT(__SSAT((acc3 >> 15), 16), __SSAT((acc2 >> 15), 16), 16);

#endif /*      #ifndef  ARM_MATH_BIG_ENDIAN    */

      /* Increment the pointer pIn1 index, count by 4 */
      count += 4u;

      /* Update the inputA and inputB pointers for next MAC calculation */
      px = pIn1 + count;
      py = pSrc2;

        /* Decrement the loop counter */
        blkCnt--;
      }

      /* If the blockSize2 is not a multiple of 4, compute any remaining output samples here.   
       ** No loop unrolling is used. */
      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--);
          sum += (q63_t) ((q31_t) * px++ * *py--);
          sum += (q63_t) ((q31_t) * px++ * *py--);
          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 */
        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 */
        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_CM4) || defined(ARM_MATH_CM3)) && !defined(UNALIGNED_SUPPORT_DISABLE)  */

}