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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_q15.c    

*    

* Description:   Q15 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

* 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

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* POSSIBILITY OF SUCH DAMAGE.    

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

#include "arm_math.h"

/**    

 * @ingroup groupMatrix    

 */

/**    

 * @addtogroup MatrixMult    

 * @{    

 */

/**    

 * @brief Q15 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    

 * @param[in]           *pState points to the array for storing intermediate results    

 * @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_q15() and this fast variant is that    

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

 * The result of each 1.15 x 1.15 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 1.15 result.        

 *        

 * \par        

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

 * less precision since it discards the low 16 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_q15()</code> for a slower implementation of this function    

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

 */

arm_status arm_mat_mult_fast_q15(

  const arm_matrix_instance_q15 * pSrcA,

  const arm_matrix_instance_q15 * pSrcB,

  arm_matrix_instance_q15 * pDst,

  q15_t * pState)

{

  q31_t sum;                                     /* accumulator */

  q15_t *pSrcBT = pState;                        /* input data matrix pointer for transpose */

  q15_t *pInA = pSrcA->pData;                    /* input data matrix pointer A of Q15 type */

  q15_t *pInB = pSrcB->pData;                    /* input data matrix pointer B of Q15 type */

  q15_t *px;                                     /* Temporary output data matrix pointer */

  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 numRowsB = pSrcB->numRows;            /* number of rows of input matrix A    */

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

  arm_status status;                             /* status of matrix multiplication */

#ifndef UNALIGNED_SUPPORT_DISABLE

  q31_t in;                                      /* Temporary variable to hold the input value */

  q31_t inA1, inA2, inB1, inB2;

#else

  q15_t in;                                      /* Temporary variable to hold the input value */

  q15_t inA1, inA2, inB1, inB2;

#endif  /*      #ifndef UNALIGNED_SUPPORT_DISABLE       */

#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

  {

    /* Matrix transpose */

    do

    {

      /* Apply loop unrolling and exchange the columns with row elements */

      col = numColsB >> 2;

      /* The pointer px is set to starting address of the column being processed */

      px = pSrcBT + i;

      /* First part of the processing with loop unrolling.  Compute 4 outputs at a time.        

       ** a second loop below computes the remaining 1 to 3 samples. */

      while(col > 0u)

      {

#ifndef UNALIGNED_SUPPORT_DISABLE

        /* Read two elements from the row */

        in = *__SIMD32(pInB)++;

        /* Unpack and store one element in the destination */

#ifndef ARM_MATH_BIG_ENDIAN

        *px = (q15_t) in;

#else

        *px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);

#endif /*    #ifndef ARM_MATH_BIG_ENDIAN    */

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Unpack and store the second element in the destination */

#ifndef ARM_MATH_BIG_ENDIAN

        *px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);

#else

        *px = (q15_t) in;

#endif /*    #ifndef ARM_MATH_BIG_ENDIAN    */

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Read two elements from the row */

        in = *__SIMD32(pInB)++;

        /* Unpack and store one element in the destination */

#ifndef ARM_MATH_BIG_ENDIAN

        *px = (q15_t) in;

#else

        *px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);

#endif /*    #ifndef ARM_MATH_BIG_ENDIAN    */

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Unpack and store the second element in the destination */

#ifndef ARM_MATH_BIG_ENDIAN

        *px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);

#else

        *px = (q15_t) in;

#endif /*    #ifndef ARM_MATH_BIG_ENDIAN    */

#else

        /* Read one element from the row */

        in = *pInB++;

        /* Store one element in the destination */

        *px = in;

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Read one element from the row */

        in = *pInB++;

        /* Store one element in the destination */

        *px = in;

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Read one element from the row */

        in = *pInB++;

        /* Store one element in the destination */

        *px = in;

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Read one element from the row */

        in = *pInB++;

        /* Store one element in the destination */

        *px = in;

#endif  /*      #ifndef UNALIGNED_SUPPORT_DISABLE       */

                /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Decrement the column loop counter */

        col--;

      }

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

       ** No loop unrolling is used. */

      col = numColsB % 0x4u;

      while(col > 0u)

      {

        /* Read and store the input element in the destination */

        *px = *pInB++;

        /* Update the pointer px to point to the next row of the transposed matrix */

        px += numRowsB;

        /* Decrement the column loop counter */

        col--;

      }

      i++;

      /* Decrement the row loop counter */

      row--;

    } while(row > 0u);

    /* Reset the variables for the usage in the following multiplication process */

    row = numRowsA;

    i = 0u;

    px = pDst->pData;

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

    /* row loop */

    do

    {

      /* 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 transposed pSrcB data */

      pInB = pSrcBT;

      /* column loop */

      do

      {

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

        sum = 0;

        /* Apply loop unrolling and compute 2 MACs simultaneously. */

        colCnt = numColsA >> 2;

        /* Initiate the pointer pIn1 to point to the starting address of the column being processed */

        pInA = pSrcA->pData + i;

        /* 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) */

#ifndef UNALIGNED_SUPPORT_DISABLE

          inA1 = *__SIMD32(pInA)++;

          inB1 = *__SIMD32(pInB)++;

          inA2 = *__SIMD32(pInA)++;

          inB2 = *__SIMD32(pInB)++;

          sum = __SMLAD(inA1, inB1, sum);

          sum = __SMLAD(inA2, inB2, sum);

#else

          inA1 = *pInA++;

          inB1 = *pInB++;

          inA2 = *pInA++;

          sum += inA1 * inB1;

          inB2 = *pInB++;

          inA1 = *pInA++;

          inB1 = *pInB++;

          sum += inA2 * inB2;

          inA2 = *pInA++;

          inB2 = *pInB++;

          sum += inA1 * inB1;

          sum += inA2 * inB2;

#endif  /*      #ifndef UNALIGNED_SUPPORT_DISABLE       */

          /* Decrement the loop counter */

          colCnt--;

        }

        /* process odd column samples */

        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) */

          sum += (q31_t) (*pInA++) * (*pInB++);

          colCnt--;

        }

        /* Saturate and store the result in the destination buffer */

        *px = (q15_t) (sum >> 15);

        px++;

        /* Decrement the column loop counter */

        col--;

      } while(col > 0u);

      i = i + 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        

 */