k60-keil

K60-Keil版本（下载安装MDK4.23）

/* ----------------------------------------------------------------------   
* Copyright (C) 2010 ARM Limited. All rights reserved.   
*   
* $Date:        15. July 2011  
* $Revision: 	V1.0.10  
*   
* Project: 	    CMSIS DSP Library   
* Title:		arm_dot_prod_q15.c   
*   
* Description:	Q15 dot product.   
*   
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*  
* Version 1.0.10 2011/7/15 
*    Big Endian support added and Merged M0 and M3/M4 Source code.  
*   
* Version 1.0.3 2010/11/29  
*    Re-organized the CMSIS folders and updated documentation.   
*    
* Version 1.0.2 2010/11/11   
*    Documentation updated.    
*   
* Version 1.0.1 2010/10/05    
*    Production release and review comments incorporated.   
*   
* Version 1.0.0 2010/09/20    
*    Production release and review comments incorporated.   
*   
* Version 0.0.7  2010/06/10    
*    Misra-C changes done   
* -------------------------------------------------------------------- */

#include "arm_math.h"

/**   
 * @ingroup groupMath   
 */

/**   
 * @addtogroup dot_prod   
 * @{   
 */

/**   
 * @brief Dot product of Q15 vectors.   
 * @param[in]       *pSrcA points to the first input vector   
 * @param[in]       *pSrcB points to the second input vector   
 * @param[in]       blockSize number of samples in each vector   
 * @param[out]      *result output result returned here   
 * @return none.   
 *   
 * <b>Scaling and Overflow Behavior:</b>   
 * \par   
 * The intermediate multiplications are in 1.15 x 1.15 = 2.30 format and these   
 * results are added to a 64-bit accumulator in 34.30 format.   
 * Nonsaturating additions are used and given that there are 33 guard bits in the accumulator   
 * there is no risk of overflow.   
 * The return result is in 34.30 format.   
 */

void arm_dot_prod_q15(
  q15_t * pSrcA,
  q15_t * pSrcB,
  uint32_t blockSize,
  q63_t * result)
{
  q63_t sum = 0;                                 /* Temporary result storage */
  uint32_t blkCnt;                               /* loop counter */

#ifndef ARM_MATH_CM0

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


  /*loop Unrolling */
  blkCnt = blockSize >> 2u;

  /* 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(blkCnt > 0u)
  {
    /* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
    /* Calculate dot product and then store the result in a temporary buffer. */
    sum = __SMLALD(*__SIMD32(pSrcA)++, *__SIMD32(pSrcB)++, sum);
    sum = __SMLALD(*__SIMD32(pSrcA)++, *__SIMD32(pSrcB)++, sum);

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

  /* If the blockSize is not a multiple of 4, compute any remaining output samples here.   
   ** No loop unrolling is used. */
  blkCnt = blockSize % 0x4u;

  while(blkCnt > 0u)
  {
    /* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
    /* Calculate dot product and then store the results in a temporary buffer. */
    sum = __SMLALD(*pSrcA++, *pSrcB++, sum);

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


#else

  /* Run the below code for Cortex-M0 */

  /* Initialize blkCnt with number of samples */
  blkCnt = blockSize;

  while(blkCnt > 0u)
  {
    /* C = A[0]* B[0] + A[1]* B[1] + A[2]* B[2] + .....+ A[blockSize-1]* B[blockSize-1] */
    /* Calculate dot product and then store the results in a temporary buffer. */
    sum += (q63_t) ((q31_t) * pSrcA++ * *pSrcB++);

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

#endif /* #ifndef ARM_MATH_CM0 */

  /* Store the result in the destination buffer in 34.30 format */
  *result = sum;

}

/**   
 * @} end of dot_prod group   
 */