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authorrihab kouki <rihab.kouki@st.com>2020-07-28 11:24:49 +0100
committerrihab kouki <rihab.kouki@st.com>2020-07-28 11:24:49 +0100
commit96d6da4e252b06dcfdc041e7df23e86161c33007 (patch)
treea262f59bb1db7ec7819acae435f5049cbe5e2354 /DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c
parent9f95ff5b6ba01db09552b84a0ab79607060a2666 (diff)
downloadst-cmsis-core-lowfat-master.tar.gz
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Official ARM version: v5.6.0HEADmaster
Diffstat (limited to 'DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c')
-rw-r--r--DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c130
1 files changed, 85 insertions, 45 deletions
diff --git a/DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c b/DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c
index 0cd0afc..3eee3b9 100644
--- a/DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c
+++ b/DSP/Source/BasicMathFunctions/arm_dot_prod_f32.c
@@ -3,13 +3,13 @@
* Title: arm_dot_prod_f32.c
* Description: Floating-point dot product
*
- * $Date: 27. January 2017
- * $Revision: V.1.5.1
+ * $Date: 18. March 2019
+ * $Revision: V1.6.0
*
* Target Processor: Cortex-M cores
* -------------------------------------------------------------------- */
/*
- * Copyright (C) 2010-2017 ARM Limited or its affiliates. All rights reserved.
+ * Copyright (C) 2010-2019 ARM Limited or its affiliates. All rights reserved.
*
* SPDX-License-Identifier: Apache-2.0
*
@@ -29,95 +29,135 @@
#include "arm_math.h"
/**
- * @ingroup groupMath
+ @ingroup groupMath
*/
/**
- * @defgroup dot_prod Vector Dot Product
- *
- * Computes the dot product of two vectors.
- * The vectors are multiplied element-by-element and then summed.
- *
- * <pre>
- * sum = pSrcA[0]*pSrcB[0] + pSrcA[1]*pSrcB[1] + ... + pSrcA[blockSize-1]*pSrcB[blockSize-1]
- * </pre>
- *
- * There are separate functions for floating-point, Q7, Q15, and Q31 data types.
+ @defgroup BasicDotProd Vector Dot Product
+
+ Computes the dot product of two vectors.
+ The vectors are multiplied element-by-element and then summed.
+
+ <pre>
+ sum = pSrcA[0]*pSrcB[0] + pSrcA[1]*pSrcB[1] + ... + pSrcA[blockSize-1]*pSrcB[blockSize-1]
+ </pre>
+
+ There are separate functions for floating-point, Q7, Q15, and Q31 data types.
*/
/**
- * @addtogroup dot_prod
- * @{
+ @addtogroup BasicDotProd
+ @{
*/
/**
- * @brief Dot product of floating-point 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.
+ @brief Dot product of floating-point 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
*/
-
void arm_dot_prod_f32(
- float32_t * pSrcA,
- float32_t * pSrcB,
- uint32_t blockSize,
- float32_t * result)
+ const float32_t * pSrcA,
+ const float32_t * pSrcB,
+ uint32_t blockSize,
+ float32_t * result)
{
- float32_t sum = 0.0f; /* Temporary result storage */
- uint32_t blkCnt; /* loop counter */
+ uint32_t blkCnt; /* Loop counter */
+ float32_t sum = 0.0f; /* Temporary return variable */
+
+#if defined(ARM_MATH_NEON)
+ float32x4_t vec1;
+ float32x4_t vec2;
+ float32x4_t res;
+ float32x4_t accum = vdupq_n_f32(0);
+
+ /* Compute 4 outputs at a time */
+ blkCnt = blockSize >> 2U;
+
+ vec1 = vld1q_f32(pSrcA);
+ vec2 = vld1q_f32(pSrcB);
+
+ 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. */
+
+ accum = vmlaq_f32(accum, vec1, vec2);
+
+ /* Increment pointers */
+ pSrcA += 4;
+ pSrcB += 4;
+
+ vec1 = vld1q_f32(pSrcA);
+ vec2 = vld1q_f32(pSrcB);
+
+ /* Decrement the loop counter */
+ blkCnt--;
+ }
+
+#if __aarch64__
+ sum = vpadds_f32(vpadd_f32(vget_low_f32(accum), vget_high_f32(accum)));
+#else
+ sum = (vpadd_f32(vget_low_f32(accum), vget_high_f32(accum)))[0] + (vpadd_f32(vget_low_f32(accum), vget_high_f32(accum)))[1];
+#endif
+ /* Tail */
+ blkCnt = blockSize & 0x3;
-#if defined (ARM_MATH_DSP)
+#else
+#if defined (ARM_MATH_LOOPUNROLL)
-/* Run the below code for Cortex-M4 and Cortex-M3 */
- /*loop Unrolling */
+ /* Loop unrolling: Compute 4 outputs at a time */
blkCnt = blockSize >> 2U;
- /* First part of the processing with loop unrolling. Compute 4 outputs at a time.
+ /* 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 */
+
+ /* Calculate dot product and store result in a temporary buffer. */
sum += (*pSrcA++) * (*pSrcB++);
+
sum += (*pSrcA++) * (*pSrcB++);
+
sum += (*pSrcA++) * (*pSrcB++);
+
sum += (*pSrcA++) * (*pSrcB++);
- /* Decrement the loop counter */
+ /* Decrement loop counter */
blkCnt--;
}
- /* If the blockSize is not a multiple of 4, compute any remaining output samples here.
- ** No loop unrolling is used. */
+ /* Loop unrolling: Compute remaining outputs */
blkCnt = blockSize % 0x4U;
#else
- /* Run the below code for Cortex-M0 */
-
/* Initialize blkCnt with number of samples */
blkCnt = blockSize;
-#endif /* #if defined (ARM_MATH_DSP) */
-
+#endif /* #if defined (ARM_MATH_LOOPUNROLL) */
+#endif /* #if defined(ARM_MATH_NEON) */
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. */
+
+ /* Calculate dot product and store result in a temporary buffer. */
sum += (*pSrcA++) * (*pSrcB++);
- /* Decrement the loop counter */
+ /* Decrement loop counter */
blkCnt--;
}
- /* Store the result back in the destination buffer */
+
+ /* Store result in destination buffer */
*result = sum;
}
/**
- * @} end of dot_prod group
+ @} end of BasicDotProd group
*/