/* ----------------------------------------------------------------------------
* Copyright (C) 2010-2013 ARM Limited. All rights reserved.
*
* $Date: 17. January 2013
* $Revision: V1.4.1
*
* Project: CMSIS DSP Library
* Title: arm_conv_partial_f32.c
*
* Description: Partial convolution of floating-point sequences.
*
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*
* 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
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* 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,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
* -------------------------------------------------------------------------- */
#include "arm_math.h"
/**
* @ingroup groupFilters
*/
/**
* @defgroup PartialConv Partial Convolution
*
* Partial Convolution is equivalent to Convolution except that a subset of the output samples is generated.
* Each function has two additional arguments.
* firstIndex specifies the starting index of the subset of output samples.
* numPoints is the number of output samples to compute.
* The function computes the output in the range
* [firstIndex, ..., firstIndex+numPoints-1].
* The output array pDst contains numPoints values.
*
* The allowable range of output indices is [0 srcALen+srcBLen-2].
* If the requested subset does not fall in this range then the functions return ARM_MATH_ARGUMENT_ERROR.
* Otherwise the functions return ARM_MATH_SUCCESS.
* \note Refer arm_conv_f32() for details on fixed point behavior.
*
*
* Fast Versions
*
* \par
* Fast versions are supported for Q31 and Q15 of partial convolution. Cycles for Fast versions are less compared to Q31 and Q15 of partial conv and the design requires
* the input signals should be scaled down to avoid intermediate overflows.
*
*
* Opt Versions
*
* \par
* Opt versions are supported for Q15 and Q7. Design uses internal scratch buffer for getting good optimisation.
* These versions are optimised in cycles and consumes more memory(Scratch memory) compared to Q15 and Q7 versions of partial convolution
*/
/**
* @addtogroup PartialConv
* @{
*/
/**
* @brief Partial convolution of floating-point sequences.
* @param[in] *pSrcA points to the first input sequence.
* @param[in] srcALen length of the first input sequence.
* @param[in] *pSrcB points to the second input sequence.
* @param[in] srcBLen length of the second input sequence.
* @param[out] *pDst points to the location where the output result is written.
* @param[in] firstIndex is the first output sample to start with.
* @param[in] numPoints is the number of output points to be computed.
* @return Returns either ARM_MATH_SUCCESS if the function completed correctly or ARM_MATH_ARGUMENT_ERROR if the requested subset is not in the range [0 srcALen+srcBLen-2].
*/
arm_status arm_conv_partial_f32(
float32_t * pSrcA,
uint32_t srcALen,
float32_t * pSrcB,
uint32_t srcBLen,
float32_t * pDst,
uint32_t firstIndex,
uint32_t numPoints)
{
#ifndef ARM_MATH_CM0_FAMILY
/* Run the below code for Cortex-M4 and Cortex-M3 */
float32_t *pIn1 = pSrcA; /* inputA pointer */
float32_t *pIn2 = pSrcB; /* inputB pointer */
float32_t *pOut = pDst; /* output pointer */
float32_t *px; /* Intermediate inputA pointer */
float32_t *py; /* Intermediate inputB pointer */
float32_t *pSrc1, *pSrc2; /* Intermediate pointers */
float32_t sum, acc0, acc1, acc2, acc3; /* Accumulator */
float32_t x0, x1, x2, x3, c0; /* Temporary variables to hold state and coefficient values */
uint32_t j, k, count = 0u, blkCnt, check;
int32_t blockSize1, blockSize2, blockSize3; /* loop counters */
arm_status status; /* status of Partial convolution */
/* Check for range of output samples to be calculated */
if((firstIndex + numPoints) > ((srcALen + (srcBLen - 1u))))
{
/* Set status as ARM_MATH_ARGUMENT_ERROR */
status = ARM_MATH_ARGUMENT_ERROR;
}
else
{
/* The algorithm implementation is based on the lengths of the inputs. */
/* srcB is always made to slide across srcA. */
/* So srcBLen is always considered as shorter or equal to srcALen */
if(srcALen >= srcBLen)
{
/* Initialization of inputA pointer */
pIn1 = pSrcA;
/* Initialization of inputB pointer */
pIn2 = pSrcB;
}
else
{
/* Initialization of inputA pointer */
pIn1 = pSrcB;
/* Initialization of inputB pointer */
pIn2 = pSrcA;
/* srcBLen is always considered as shorter or equal to srcALen */
j = srcBLen;
srcBLen = srcALen;
srcALen = j;
}
/* Conditions to check which loopCounter holds
* the first and last indices of the output samples to be calculated. */
check = firstIndex + numPoints;
blockSize3 = (int32_t) check - (int32_t) srcALen;
blockSize3 = (blockSize3 > 0) ? blockSize3 : 0;
blockSize1 = ((int32_t) srcBLen - 1) - (int32_t) firstIndex;
blockSize1 = (blockSize1 > 0) ? ((check > (srcBLen - 1u)) ? blockSize1 :
(int32_t) numPoints) : 0;
blockSize2 = ((int32_t) check - blockSize3) -
(blockSize1 + (int32_t) firstIndex);
blockSize2 = (blockSize2 > 0) ? blockSize2 : 0;
/* conv(x,y) at n = x[n] * y[0] + x[n-1] * y[1] + x[n-2] * y[2] + ...+ x[n-N+1] * y[N -1] */
/* The function is internally
* divided into three stages according to the number of multiplications that has to be
* taken place between inputA samples and inputB samples. In the first stage of the
* algorithm, the multiplications increase by one for every iteration.
* In the second stage of the algorithm, srcBLen number of multiplications are done.
* In the third stage of the algorithm, the multiplications decrease by one
* for every iteration. */
/* Set the output pointer to point to the firstIndex
* of the output sample to be calculated. */
pOut = pDst + firstIndex;
/* --------------------------
* Initializations of stage1
* -------------------------*/
/* sum = x[0] * y[0]
* sum = x[0] * y[1] + x[1] * y[0]
* ....
* sum = x[0] * y[srcBlen - 1] + x[1] * y[srcBlen - 2] +...+ x[srcBLen - 1] * y[0]
*/
/* In this stage the MAC operations are increased by 1 for every iteration.
The count variable holds the number of MAC operations performed.
Since the partial convolution starts from from firstIndex
Number of Macs to be performed is firstIndex + 1 */
count = 1u + firstIndex;
/* Working pointer of inputA */
px = pIn1;
/* Working pointer of inputB */
pSrc1 = pIn2 + firstIndex;
py = pSrc1;
/* ------------------------
* Stage1 process
* ----------------------*/
/* The first stage starts here */
while(blockSize1 > 0)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = count >> 2u;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
while(k > 0u)
{
/* x[0] * y[srcBLen - 1] */
sum += *px++ * *py--;
/* x[1] * y[srcBLen - 2] */
sum += *px++ * *py--;
/* x[2] * y[srcBLen - 3] */
sum += *px++ * *py--;
/* x[3] * y[srcBLen - 4] */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* If the count is not a multiple of 4, compute any remaining MACs here.
** No loop unrolling is used. */
k = count % 0x4u;
while(k > 0u)
{
/* Perform the multiply-accumulates */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = sum;
/* Update the inputA and inputB pointers for next MAC calculation */
py = ++pSrc1;
px = pIn1;
/* Increment the MAC count */
count++;
/* Decrement the loop counter */
blockSize1--;
}
/* --------------------------
* Initializations of stage2
* ------------------------*/
/* sum = x[0] * y[srcBLen-1] + x[1] * y[srcBLen-2] +...+ x[srcBLen-1] * y[0]
* sum = x[1] * y[srcBLen-1] + x[2] * y[srcBLen-2] +...+ x[srcBLen] * y[0]
* ....
* sum = x[srcALen-srcBLen-2] * y[srcBLen-1] + x[srcALen] * y[srcBLen-2] +...+ x[srcALen-1] * y[0]
*/
/* Working pointer of inputA */
px = pIn1;
/* Working pointer of inputB */
pSrc2 = pIn2 + (srcBLen - 1u);
py = pSrc2;
/* count is index by which the pointer pIn1 to be incremented */
count = 0u;
/* -------------------
* Stage2 process
* ------------------*/
/* Stage2 depends on srcBLen as in this stage srcBLen number of MACS are performed.
* So, to loop unroll over blockSize2,
* srcBLen should be greater than or equal to 4 */
if(srcBLen >= 4u)
{
/* Loop unroll over blockSize2, by 4 */
blkCnt = ((uint32_t) blockSize2 >> 2u);
while(blkCnt > 0u)
{
/* Set all accumulators to zero */
acc0 = 0.0f;
acc1 = 0.0f;
acc2 = 0.0f;
acc3 = 0.0f;
/* read x[0], x[1], x[2] samples */
x0 = *(px++);
x1 = *(px++);
x2 = *(px++);
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = srcBLen >> 2u;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
do
{
/* Read y[srcBLen - 1] sample */
c0 = *(py--);
/* Read x[3] sample */
x3 = *(px++);
/* Perform the multiply-accumulate */
/* acc0 += x[0] * y[srcBLen - 1] */
acc0 += x0 * c0;
/* acc1 += x[1] * y[srcBLen - 1] */
acc1 += x1 * c0;
/* acc2 += x[2] * y[srcBLen - 1] */
acc2 += x2 * c0;
/* acc3 += x[3] * y[srcBLen - 1] */
acc3 += x3 * c0;
/* Read y[srcBLen - 2] sample */
c0 = *(py--);
/* Read x[4] sample */
x0 = *(px++);
/* Perform the multiply-accumulate */
/* acc0 += x[1] * y[srcBLen - 2] */
acc0 += x1 * c0;
/* acc1 += x[2] * y[srcBLen - 2] */
acc1 += x2 * c0;
/* acc2 += x[3] * y[srcBLen - 2] */
acc2 += x3 * c0;
/* acc3 += x[4] * y[srcBLen - 2] */
acc3 += x0 * c0;
/* Read y[srcBLen - 3] sample */
c0 = *(py--);
/* Read x[5] sample */
x1 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[2] * y[srcBLen - 3] */
acc0 += x2 * c0;
/* acc1 += x[3] * y[srcBLen - 2] */
acc1 += x3 * c0;
/* acc2 += x[4] * y[srcBLen - 2] */
acc2 += x0 * c0;
/* acc3 += x[5] * y[srcBLen - 2] */
acc3 += x1 * c0;
/* Read y[srcBLen - 4] sample */
c0 = *(py--);
/* Read x[6] sample */
x2 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[3] * y[srcBLen - 4] */
acc0 += x3 * c0;
/* acc1 += x[4] * y[srcBLen - 4] */
acc1 += x0 * c0;
/* acc2 += x[5] * y[srcBLen - 4] */
acc2 += x1 * c0;
/* acc3 += x[6] * y[srcBLen - 4] */
acc3 += x2 * c0;
} while(--k);
/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
** No loop unrolling is used. */
k = srcBLen % 0x4u;
while(k > 0u)
{
/* Read y[srcBLen - 5] sample */
c0 = *(py--);
/* Read x[7] sample */
x3 = *(px++);
/* Perform the multiply-accumulates */
/* acc0 += x[4] * y[srcBLen - 5] */
acc0 += x0 * c0;
/* acc1 += x[5] * y[srcBLen - 5] */
acc1 += x1 * c0;
/* acc2 += x[6] * y[srcBLen - 5] */
acc2 += x2 * c0;
/* acc3 += x[7] * y[srcBLen - 5] */
acc3 += x3 * c0;
/* Reuse the present samples for the next MAC */
x0 = x1;
x1 = x2;
x2 = x3;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = acc0;
*pOut++ = acc1;
*pOut++ = acc2;
*pOut++ = acc3;
/* Increment the pointer pIn1 index, count by 1 */
count += 4u;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pSrc2;
/* Decrement the loop counter */
blkCnt--;
}
/* If the blockSize2 is not a multiple of 4, compute any remaining output samples here.
** No loop unrolling is used. */
blkCnt = (uint32_t) blockSize2 % 0x4u;
while(blkCnt > 0u)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = srcBLen >> 2u;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
while(k > 0u)
{
/* Perform the multiply-accumulates */
sum += *px++ * *py--;
sum += *px++ * *py--;
sum += *px++ * *py--;
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* If the srcBLen is not a multiple of 4, compute any remaining MACs here.
** No loop unrolling is used. */
k = srcBLen % 0x4u;
while(k > 0u)
{
/* Perform the multiply-accumulate */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = sum;
/* Increment the MAC count */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pSrc2;
/* Decrement the loop counter */
blkCnt--;
}
}
else
{
/* If the srcBLen is not a multiple of 4,
* the blockSize2 loop cannot be unrolled by 4 */
blkCnt = (uint32_t) blockSize2;
while(blkCnt > 0u)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* srcBLen number of MACS should be performed */
k = srcBLen;
while(k > 0u)
{
/* Perform the multiply-accumulate */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = sum;
/* Increment the MAC count */
count++;
/* Update the inputA and inputB pointers for next MAC calculation */
px = pIn1 + count;
py = pSrc2;
/* Decrement the loop counter */
blkCnt--;
}
}
/* --------------------------
* Initializations of stage3
* -------------------------*/
/* sum += x[srcALen-srcBLen+1] * y[srcBLen-1] + x[srcALen-srcBLen+2] * y[srcBLen-2] +...+ x[srcALen-1] * y[1]
* sum += x[srcALen-srcBLen+2] * y[srcBLen-1] + x[srcALen-srcBLen+3] * y[srcBLen-2] +...+ x[srcALen-1] * y[2]
* ....
* sum += x[srcALen-2] * y[srcBLen-1] + x[srcALen-1] * y[srcBLen-2]
* sum += x[srcALen-1] * y[srcBLen-1]
*/
/* In this stage the MAC operations are decreased by 1 for every iteration.
The count variable holds the number of MAC operations performed */
count = srcBLen - 1u;
/* Working pointer of inputA */
pSrc1 = (pIn1 + srcALen) - (srcBLen - 1u);
px = pSrc1;
/* Working pointer of inputB */
pSrc2 = pIn2 + (srcBLen - 1u);
py = pSrc2;
while(blockSize3 > 0)
{
/* Accumulator is made zero for every iteration */
sum = 0.0f;
/* Apply loop unrolling and compute 4 MACs simultaneously. */
k = count >> 2u;
/* First part of the processing with loop unrolling. Compute 4 MACs at a time.
** a second loop below computes MACs for the remaining 1 to 3 samples. */
while(k > 0u)
{
/* sum += x[srcALen - srcBLen + 1] * y[srcBLen - 1] */
sum += *px++ * *py--;
/* sum += x[srcALen - srcBLen + 2] * y[srcBLen - 2] */
sum += *px++ * *py--;
/* sum += x[srcALen - srcBLen + 3] * y[srcBLen - 3] */
sum += *px++ * *py--;
/* sum += x[srcALen - srcBLen + 4] * y[srcBLen - 4] */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* If the count is not a multiple of 4, compute any remaining MACs here.
** No loop unrolling is used. */
k = count % 0x4u;
while(k > 0u)
{
/* Perform the multiply-accumulates */
/* sum += x[srcALen-1] * y[srcBLen-1] */
sum += *px++ * *py--;
/* Decrement the loop counter */
k--;
}
/* Store the result in the accumulator in the destination buffer. */
*pOut++ = sum;
/* Update the inputA and inputB pointers for next MAC calculation */
px = ++pSrc1;
py = pSrc2;
/* Decrement the MAC count */
count--;
/* Decrement the loop counter */
blockSize3--;
}
/* set status as ARM_MATH_SUCCESS */
status = ARM_MATH_SUCCESS;
}
/* Return to application */
return (status);
#else
/* Run the below code for Cortex-M0 */
float32_t *pIn1 = pSrcA; /* inputA pointer */
float32_t *pIn2 = pSrcB; /* inputB pointer */
float32_t sum; /* Accumulator */
uint32_t i, j; /* loop counters */
arm_status status; /* status of Partial convolution */
/* Check for range of output samples to be calculated */
if((firstIndex + numPoints) > ((srcALen + (srcBLen - 1u))))
{
/* Set status as ARM_ARGUMENT_ERROR */
status = ARM_MATH_ARGUMENT_ERROR;
}
else
{
/* Loop to calculate convolution for output length number of values */
for (i = firstIndex; i <= (firstIndex + numPoints - 1); i++)
{
/* Initialize sum with zero to carry on MAC operations */
sum = 0.0f;
/* Loop to perform MAC operations according to convolution equation */
for (j = 0u; j <= i; j++)
{
/* Check the array limitations for inputs */
if((((i - j) < srcBLen) && (j < srcALen)))
{
/* z[i] += x[i-j] * y[j] */
sum += pIn1[j] * pIn2[i - j];
}
}
/* Store the output in the destination buffer */
pDst[i] = sum;
}
/* set status as ARM_SUCCESS as there are no argument errors */
status = ARM_MATH_SUCCESS;
}
return (status);
#endif /* #ifndef ARM_MATH_CM0_FAMILY */
}
/**
* @} end of PartialConv group
*/