/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_mat_mult_fast_q15.c
* Description: Q15 matrix multiplication (fast variant)
*
* $Date: 27. January 2017
* $Revision: V.1.5.1
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
* Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the License); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an AS IS BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#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 */
uint32_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;
q31_t sum2, sum3, sum4;
q15_t *pInA2, *pInB2, *px2;
uint32_t j = 0;
#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;
#ifndef UNALIGNED_SUPPORT_DISABLE
/* Process two rows from matrix A at a time and output two rows at a time */
row = row >> 1;
px2 = px + numColsB;
#endif
/* The following loop performs the dot-product of each row in pSrcA with each column in pSrcB */
/* row loop */
while (row > 0U)
{
/* 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;
#ifndef UNALIGNED_SUPPORT_DISABLE
/* Process two (transposed) columns from matrix B at a time */
col = col >> 1;
j = 0;
#endif
/* column loop */
while (col > 0U)
{
/* Set the variable sum, that acts as accumulator, to zero */
sum = 0;
/* Initiate the pointer pInA to point to the starting address of the column being processed */
pInA = pSrcA->pData + i;
#ifndef UNALIGNED_SUPPORT_DISABLE
sum2 = 0;
sum3 = 0;
sum4 = 0;
pInB = pSrcBT + j;
pInA2 = pInA + numColsA;
pInB2 = pInB + numRowsB;
/* Read in two elements at once - alows dual MAC instruction */
colCnt = numColsA >> 1;
#else
colCnt = numColsA >> 2;
#endif
/* 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(pInA2)++;
inB2 = *__SIMD32(pInB2)++;
sum = __SMLAD(inA1, inB1, sum);
sum2 = __SMLAD(inA1, inB2, sum2);
sum3 = __SMLAD(inA2, inB1, sum3);
sum4 = __SMLAD(inA2, inB2, sum4);
#else
inA1 = *pInA;
inB1 = *pInB;
sum += inA1 * inB1;
inA2 = pInA[1];
inB2 = pInB[1];
sum += inA2 * inB2;
inA1 = pInA[2];
inB1 = pInB[2];
sum += inA1 * inB1;
inA2 = pInA[3];
inB2 = pInB[3];
sum += inA2 * inB2;
pInA += 4;
pInB += 4;
#endif /* #ifndef UNALIGNED_SUPPORT_DISABLE */
/* Decrement the loop counter */
colCnt--;
}
/* process odd column samples */
#ifndef UNALIGNED_SUPPORT_DISABLE
if (numColsA & 1U) {
inA1 = *pInA++;
inB1 = *pInB++;
inA2 = *pInA2++;
inB2 = *pInB2++;
sum += inA1 * inB1;
sum2 += inA1 * inB2;
sum3 += inA2 * inB1;
sum4 += inA2 * inB2;
}
#else
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--;
}
#endif
/* Saturate and store the result in the destination buffer */
*px++ = (q15_t) (sum >> 15);
#ifndef UNALIGNED_SUPPORT_DISABLE
*px++ = (q15_t) (sum2 >> 15);
*px2++ = (q15_t) (sum3 >> 15);
*px2++ = (q15_t) (sum4 >> 15);
j += numRowsB * 2;
#endif
/* Decrement the column loop counter */
col--;
}
i = i + numColsA;
#ifndef UNALIGNED_SUPPORT_DISABLE
i = i + numColsA;
px = px2 + (numColsB & 1U);
px2 = px + numColsB;
#endif
/* Decrement the row loop counter */
row--;
}
/* Compute any remaining odd row/column below */
#ifndef UNALIGNED_SUPPORT_DISABLE
/* Compute remaining output column */
if (numColsB & 1U) {
/* Avoid redundant computation of last element */
row = numRowsA & (~0x1);
/* Point to remaining unfilled column in output matrix */
px = pDst->pData+numColsB-1;
pInA = pSrcA->pData;
/* row loop */
while (row > 0)
{
/* point to last column in matrix B */
pInB = pSrcBT + numRowsB*(numColsB-1);
/* Set the variable sum, that acts as accumulator, to zero */
sum = 0;
/* Compute 4 columns at once */
colCnt = numColsA >> 2;
/* matrix multiplication */
while (colCnt > 0U)
{
inA1 = *__SIMD32(pInA)++;
inA2 = *__SIMD32(pInA)++;
inB1 = *__SIMD32(pInB)++;
inB2 = *__SIMD32(pInB)++;
sum = __SMLAD(inA1, inB1, sum);
sum = __SMLAD(inA2, inB2, sum);
/* Decrement the loop counter */
colCnt--;
}
colCnt = numColsA & 3U;
while (colCnt > 0U) {
sum += (q31_t) (*pInA++) * (*pInB++);
colCnt--;
}
/* Store the result in the destination buffer */
*px = (q15_t) (sum >> 15);
px += numColsB;
/* Decrement the row loop counter */
row--;
}
}
/* Compute remaining output row */
if (numRowsA & 1U) {
/* point to last row in output matrix */
px = pDst->pData+(numColsB)*(numRowsA-1);
pInB = pSrcBT;
col = numColsB;
i = 0U;
/* col loop */
while (col > 0)
{
/* point to last row in matrix A */
pInA = pSrcA->pData + (numRowsA-1)*numColsA;
/* Set the variable sum, that acts as accumulator, to zero */
sum = 0;
/* Compute 4 columns at once */
colCnt = numColsA >> 2;
/* matrix multiplication */
while (colCnt > 0U)
{
inA1 = *__SIMD32(pInA)++;
inA2 = *__SIMD32(pInA)++;
inB1 = *__SIMD32(pInB)++;
inB2 = *__SIMD32(pInB)++;
sum = __SMLAD(inA1, inB1, sum);
sum = __SMLAD(inA2, inB2, sum);
/* Decrement the loop counter */
colCnt--;
}
colCnt = numColsA & 3U;
while (colCnt > 0U) {
sum += (q31_t) (*pInA++) * (*pInB++);
colCnt--;
}
/* Store the result in the destination buffer */
*px++ = (q15_t) (sum >> 15);
/* Decrement the col loop counter */
col--;
}
}
#endif /* #ifndef UNALIGNED_SUPPORT_DISABLE */
/* set status as ARM_MATH_SUCCESS */
status = ARM_MATH_SUCCESS;
}
/* Return to application */
return (status);
}
/**
* @} end of MatrixMult group
*/