/* ----------------------------------------------------------------------
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* Copyright (C) 2010-2014 ARM Limited. All rights reserved.
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*
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* $Date: 19. March 2015
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* $Revision: V.1.4.5
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*
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* Project: CMSIS DSP Library
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* Title: arm_mat_mult_fast_q15.c
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*
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* Description: Q15 matrix multiplication (fast variant)
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*
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* Target Processor: Cortex-M4/Cortex-M3
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* - Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* - Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* - Neither the name of ARM LIMITED nor the names of its contributors
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* may be used to endorse or promote products derived from this
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* software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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* -------------------------------------------------------------------- */
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#include "arm_math.h"
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/**
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* @ingroup groupMatrix
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*/
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/**
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* @addtogroup MatrixMult
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* @{
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*/
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/**
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* @brief Q15 matrix multiplication (fast variant) for Cortex-M3 and Cortex-M4
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* @param[in] *pSrcA points to the first input matrix structure
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* @param[in] *pSrcB points to the second input matrix structure
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* @param[out] *pDst points to output matrix structure
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* @param[in] *pState points to the array for storing intermediate results
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* @return The function returns either
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* <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.
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*
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* @details
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* <b>Scaling and Overflow Behavior:</b>
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*
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* \par
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* The difference between the function arm_mat_mult_q15() and this fast variant is that
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* the fast variant use a 32-bit rather than a 64-bit accumulator.
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* The result of each 1.15 x 1.15 multiplication is truncated to
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* 2.30 format. These intermediate results are accumulated in a 32-bit register in 2.30
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* format. Finally, the accumulator is saturated and converted to a 1.15 result.
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*
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* \par
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* The fast version has the same overflow behavior as the standard version but provides
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* less precision since it discards the low 16 bits of each multiplication result.
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* In order to avoid overflows completely the input signals must be scaled down.
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* Scale down one of the input matrices by log2(numColsA) bits to
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* avoid overflows, as a total of numColsA additions are computed internally for each
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* output element.
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*
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* \par
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* See <code>arm_mat_mult_q15()</code> for a slower implementation of this function
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* which uses 64-bit accumulation to provide higher precision.
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*/
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arm_status arm_mat_mult_fast_q15(
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const arm_matrix_instance_q15 * pSrcA,
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const arm_matrix_instance_q15 * pSrcB,
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arm_matrix_instance_q15 * pDst,
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q15_t * pState)
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{
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q31_t sum; /* accumulator */
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q15_t *pSrcBT = pState; /* input data matrix pointer for transpose */
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q15_t *pInA = pSrcA->pData; /* input data matrix pointer A of Q15 type */
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q15_t *pInB = pSrcB->pData; /* input data matrix pointer B of Q15 type */
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q15_t *px; /* Temporary output data matrix pointer */
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uint16_t numRowsA = pSrcA->numRows; /* number of rows of input matrix A */
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uint16_t numColsB = pSrcB->numCols; /* number of columns of input matrix B */
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uint16_t numColsA = pSrcA->numCols; /* number of columns of input matrix A */
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uint16_t numRowsB = pSrcB->numRows; /* number of rows of input matrix A */
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uint16_t col, i = 0u, row = numRowsB, colCnt; /* loop counters */
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arm_status status; /* status of matrix multiplication */
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#ifndef UNALIGNED_SUPPORT_DISABLE
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q31_t in; /* Temporary variable to hold the input value */
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q31_t inA1, inA2, inB1, inB2;
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#else
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q15_t in; /* Temporary variable to hold the input value */
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q15_t inA1, inA2, inB1, inB2;
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#endif /* #ifndef UNALIGNED_SUPPORT_DISABLE */
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#ifdef ARM_MATH_MATRIX_CHECK
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/* Check for matrix mismatch condition */
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if((pSrcA->numCols != pSrcB->numRows) ||
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(pSrcA->numRows != pDst->numRows) || (pSrcB->numCols != pDst->numCols))
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{
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/* Set status as ARM_MATH_SIZE_MISMATCH */
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status = ARM_MATH_SIZE_MISMATCH;
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}
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else
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#endif
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{
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/* Matrix transpose */
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do
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{
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/* Apply loop unrolling and exchange the columns with row elements */
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col = numColsB >> 2;
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/* The pointer px is set to starting address of the column being processed */
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px = pSrcBT + i;
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/* First part of the processing with loop unrolling. Compute 4 outputs at a time.
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** a second loop below computes the remaining 1 to 3 samples. */
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while(col > 0u)
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{
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#ifndef UNALIGNED_SUPPORT_DISABLE
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/* Read two elements from the row */
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in = *__SIMD32(pInB)++;
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/* Unpack and store one element in the destination */
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#ifndef ARM_MATH_BIG_ENDIAN
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*px = (q15_t) in;
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#else
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*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
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#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Unpack and store the second element in the destination */
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#ifndef ARM_MATH_BIG_ENDIAN
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*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
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#else
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*px = (q15_t) in;
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#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Read two elements from the row */
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in = *__SIMD32(pInB)++;
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/* Unpack and store one element in the destination */
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#ifndef ARM_MATH_BIG_ENDIAN
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*px = (q15_t) in;
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#else
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*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
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#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Unpack and store the second element in the destination */
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#ifndef ARM_MATH_BIG_ENDIAN
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*px = (q15_t) ((in & (q31_t) 0xffff0000) >> 16);
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#else
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*px = (q15_t) in;
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#endif /* #ifndef ARM_MATH_BIG_ENDIAN */
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#else
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/* Read one element from the row */
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in = *pInB++;
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/* Store one element in the destination */
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*px = in;
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Read one element from the row */
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in = *pInB++;
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/* Store one element in the destination */
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*px = in;
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Read one element from the row */
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in = *pInB++;
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/* Store one element in the destination */
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*px = in;
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Read one element from the row */
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in = *pInB++;
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/* Store one element in the destination */
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*px = in;
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#endif /* #ifndef UNALIGNED_SUPPORT_DISABLE */
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Decrement the column loop counter */
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col--;
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}
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/* If the columns of pSrcB is not a multiple of 4, compute any remaining output samples here.
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** No loop unrolling is used. */
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col = numColsB % 0x4u;
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while(col > 0u)
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{
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/* Read and store the input element in the destination */
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*px = *pInB++;
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/* Update the pointer px to point to the next row of the transposed matrix */
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px += numRowsB;
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/* Decrement the column loop counter */
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col--;
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}
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i++;
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/* Decrement the row loop counter */
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row--;
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} while(row > 0u);
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/* Reset the variables for the usage in the following multiplication process */
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row = numRowsA;
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i = 0u;
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px = pDst->pData;
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/* The following loop performs the dot-product of each row in pSrcA with each column in pSrcB */
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/* row loop */
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do
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{
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/* For every row wise process, the column loop counter is to be initiated */
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col = numColsB;
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/* For every row wise process, the pIn2 pointer is set
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** to the starting address of the transposed pSrcB data */
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pInB = pSrcBT;
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/* column loop */
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do
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{
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/* Set the variable sum, that acts as accumulator, to zero */
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sum = 0;
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/* Apply loop unrolling and compute 2 MACs simultaneously. */
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colCnt = numColsA >> 2;
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/* Initiate the pointer pIn1 to point to the starting address of the column being processed */
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pInA = pSrcA->pData + i;
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/* matrix multiplication */
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while(colCnt > 0u)
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{
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/* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
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#ifndef UNALIGNED_SUPPORT_DISABLE
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inA1 = *__SIMD32(pInA)++;
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inB1 = *__SIMD32(pInB)++;
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inA2 = *__SIMD32(pInA)++;
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inB2 = *__SIMD32(pInB)++;
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sum = __SMLAD(inA1, inB1, sum);
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sum = __SMLAD(inA2, inB2, sum);
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#else
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inA1 = *pInA++;
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inB1 = *pInB++;
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inA2 = *pInA++;
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sum += inA1 * inB1;
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inB2 = *pInB++;
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inA1 = *pInA++;
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inB1 = *pInB++;
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sum += inA2 * inB2;
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inA2 = *pInA++;
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inB2 = *pInB++;
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sum += inA1 * inB1;
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sum += inA2 * inB2;
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#endif /* #ifndef UNALIGNED_SUPPORT_DISABLE */
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/* Decrement the loop counter */
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colCnt--;
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}
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/* process odd column samples */
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colCnt = numColsA % 0x4u;
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while(colCnt > 0u)
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{
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/* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
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sum += (q31_t) (*pInA++) * (*pInB++);
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colCnt--;
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}
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/* Saturate and store the result in the destination buffer */
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*px = (q15_t) (sum >> 15);
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px++;
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/* Decrement the column loop counter */
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col--;
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} while(col > 0u);
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i = i + numColsA;
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/* Decrement the row loop counter */
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row--;
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} while(row > 0u);
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/* set status as ARM_MATH_SUCCESS */
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status = ARM_MATH_SUCCESS;
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}
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/* Return to application */
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return (status);
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}
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/**
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* @} end of MatrixMult group
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*/
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