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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_mat_mult_fast_q31.c    

*    

* Description:   Q31 matrix multiplication (fast variant).    

*    

* Target Processor: Cortex-M4/Cortex-M3

*  

* 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

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* -------------------------------------------------------------------- */

#include "arm_math.h"

/**    

 * @ingroup groupMatrix    

 */

/**    

 * @addtogroup MatrixMult    

 * @{    

 */

/**    

 * @brief Q31 matrix multiplication (fast variant) for Cortex-M3 and Cortex-M4    

 * @param[in]       *pSrcA points to the first input matrix structure    

 * @param[in]       *pSrcB points to the second input matrix structure    

 * @param[out]      *pDst points to output matrix structure    

 * @return              The function returns either    

 * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.    

 *    

 * @details    

 * <b>Scaling and Overflow Behavior:</b>    

 *    

 * \par    

 * The difference between the function arm_mat_mult_q31() and this fast variant is that    

 * the fast variant use a 32-bit rather than a 64-bit accumulator.    

 * The result of each 1.31 x 1.31 multiplication is truncated to    

 * 2.30 format. These intermediate results are accumulated in a 32-bit register in 2.30    

 * format. Finally, the accumulator is saturated and converted to a 1.31 result.    

 *    

 * \par    

 * The fast version has the same overflow behavior as the standard version but provides    

 * less precision since it discards the low 32 bits of each multiplication result.    

 * In order to avoid overflows completely the input signals must be scaled down.    

 * Scale down one of the input matrices by log2(numColsA) bits to    

 * avoid overflows, as a total of numColsA additions are computed internally for each    

 * output element.    

 *    

 * \par    

 * See <code>arm_mat_mult_q31()</code> for a slower implementation of this function    

 * which uses 64-bit accumulation to provide higher precision.    

 */

arm_status arm_mat_mult_fast_q31(

  const arm_matrix_instance_q31 * pSrcA,

  const arm_matrix_instance_q31 * pSrcB,

  arm_matrix_instance_q31 * pDst)

{

  q31_t *pIn1 = pSrcA->pData;                    /* input data matrix pointer A */

  q31_t *pIn2 = pSrcB->pData;                    /* input data matrix pointer B */

  q31_t *pInA = pSrcA->pData;                    /* input data matrix pointer A */

//  q31_t *pSrcB = pSrcB->pData;                    /* input data matrix pointer B */    

  q31_t *pOut = pDst->pData;                     /* output data matrix pointer */

  q31_t *px;                                     /* Temporary output data matrix pointer */

  q31_t sum;                                     /* Accumulator */

  uint16_t numRowsA = pSrcA->numRows;            /* number of rows of input matrix A    */

  uint16_t numColsB = pSrcB->numCols;            /* number of columns of input matrix B */

  uint16_t numColsA = pSrcA->numCols;            /* number of columns of input matrix A */

  uint16_t col, i = 0u, j, row = numRowsA, colCnt;      /* loop counters */

  arm_status status;                             /* status of matrix multiplication */

  q31_t inA1, inA2, inA3, inA4, inB1, inB2, inB3, inB4;

#ifdef ARM_MATH_MATRIX_CHECK

  /* Check for matrix mismatch condition */

  if((pSrcA->numCols != pSrcB->numRows) ||

     (pSrcA->numRows != pDst->numRows) || (pSrcB->numCols != pDst->numCols))

  {

    /* Set status as ARM_MATH_SIZE_MISMATCH */

    status = ARM_MATH_SIZE_MISMATCH;

  }

  else

#endif /*      #ifdef ARM_MATH_MATRIX_CHECK    */

  {

    /* The following loop performs the dot-product of each row in pSrcA with each column in pSrcB */

    /* row loop */

    do

    {

      /* Output pointer is set to starting address of the row being processed */

      px = pOut + i;

      /* For every row wise process, the column loop counter is to be initiated */

      col = numColsB;

      /* For every row wise process, the pIn2 pointer is set    

       ** to the starting address of the pSrcB data */

      pIn2 = pSrcB->pData;

      j = 0u;

      /* column loop */

      do

      {

        /* Set the variable sum, that acts as accumulator, to zero */

        sum = 0;

        /* Initiate the pointer pIn1 to point to the starting address of pInA */

        pIn1 = pInA;

        /* Apply loop unrolling and compute 4 MACs simultaneously. */

        colCnt = numColsA >> 2;

        /* matrix multiplication */

        while(colCnt > 0u)

        {

          /* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */

          /* Perform the multiply-accumulates */

          inB1 = *pIn2;

          pIn2 += numColsB;

          inA1 = pIn1[0];

          inA2 = pIn1[1];

          inB2 = *pIn2;

          pIn2 += numColsB;

          inB3 = *pIn2;

          pIn2 += numColsB;

          sum = (q31_t) ((((q63_t) sum << 32) + ((q63_t) inA1 * inB1)) >> 32);

          sum = (q31_t) ((((q63_t) sum << 32) + ((q63_t) inA2 * inB2)) >> 32);

          inA3 = pIn1[2];

          inA4 = pIn1[3];

          inB4 = *pIn2;

          pIn2 += numColsB;

          sum = (q31_t) ((((q63_t) sum << 32) + ((q63_t) inA3 * inB3)) >> 32);

          sum = (q31_t) ((((q63_t) sum << 32) + ((q63_t) inA4 * inB4)) >> 32);

          pIn1 += 4u;

          /* Decrement the loop counter */

          colCnt--;

        }

        /* If the columns of pSrcA is not a multiple of 4, compute any remaining output samples here.    

         ** No loop unrolling is used. */

        colCnt = numColsA % 0x4u;

        while(colCnt > 0u)

        {

          /* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */

          /* Perform the multiply-accumulates */

          sum = (q31_t) ((((q63_t) sum << 32) +

                          ((q63_t) * pIn1++ * (*pIn2))) >> 32);

          pIn2 += numColsB;

          /* Decrement the loop counter */

          colCnt--;

        }

        /* Convert the result from 2.30 to 1.31 format and store in destination buffer */

        *px++ = sum << 1;

        /* Update the pointer pIn2 to point to the  starting address of the next column */

        j++;

        pIn2 = pSrcB->pData + j;

        /* Decrement the column loop counter */

        col--;

      } while(col > 0u);

      /* Update the pointer pInA to point to the  starting address of the next row */

      i = i + numColsB;

      pInA = pInA + numColsA;

      /* Decrement the row loop counter */

      row--;

    } while(row > 0u);

    /* set status as ARM_MATH_SUCCESS */

    status = ARM_MATH_SUCCESS;

  }

  /* Return to application */

  return (status);

}

/**    

 * @} end of MatrixMult group    

 */