/* ----------------------------------------------------------------------    
* Copyright (C) 2010-2013 ARM Limited. All rights reserved.    
*    
* $Date:        17. January 2013 
* $Revision: 	V1.4.1
*    
* 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
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* 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,
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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    
 */