/* ---------------------------------------------------------------------- * 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. * * Scaling and Overflow Behavior: * \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 */