Fork of mbed-dsp. CMSIS-DSP library of supporting NEON

Dependents:   mbed-os-example-cmsis_dsp_neon

Fork of mbed-dsp by mbed official

Information

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CMSIS-DSP of supporting NEON

What is this ?

A library for CMSIS-DSP of supporting NEON.
We supported the NEON to CMSIS-DSP Ver1.4.3(CMSIS V4.1) that ARM supplied, has achieved the processing speed improvement.
If you use the mbed-dsp library, you can use to replace this library.
CMSIS-DSP of supporting NEON is provied as a library.

Library Creation environment

CMSIS-DSP library of supporting NEON was created by the following environment.

  • Compiler
    ARMCC Version 5.03
  • Compile option switch[C Compiler]
   -DARM_MATH_MATRIX_CHECK -DARM_MATH_ROUNDING -O3 -Otime --cpu=Cortex-A9 --littleend --arm 
   --apcs=/interwork --no_unaligned_access --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp 
   --vectorize --asm
  • Compile option switch[Assembler]
   --cpreproc --cpu=Cortex-A9 --littleend --arm --apcs=/interwork --no_unaligned_access 
   --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp


Effects of NEON support

In the data which passes to each function, large size will be expected more effective than small size.
Also if the data is a multiple of 16, effect will be expected in every function in the CMSIS-DSP.


NEON対応CMSIS-DSP

概要

NEON対応したCMSIS-DSPのライブラリです。
ARM社提供のCMSIS-DSP Ver1.4.3(CMSIS V4.1)をターゲットにNEON対応を行ない、処理速度向上を実現しております。
mbed-dspライブラリを使用している場合は、本ライブラリに置き換えて使用することができます。
NEON対応したCMSIS-DSPはライブラリで提供します。

ライブラリ作成環境

NEON対応CMSIS-DSPライブラリは、以下の環境で作成しています。

  • コンパイラ
    ARMCC Version 5.03
  • コンパイルオプションスイッチ[C Compiler]
   -DARM_MATH_MATRIX_CHECK -DARM_MATH_ROUNDING -O3 -Otime --cpu=Cortex-A9 --littleend --arm 
   --apcs=/interwork --no_unaligned_access --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp 
   --vectorize --asm
  • コンパイルオプションスイッチ[Assembler]
   --cpreproc --cpu=Cortex-A9 --littleend --arm --apcs=/interwork --no_unaligned_access 
   --fpu=vfpv3_fp16 --fpmode=fast --apcs=/hardfp


NEON対応による効果について

CMSIS-DSP内の各関数へ渡すデータは、小さいサイズよりも大きいサイズの方が効果が見込めます。
また、16の倍数のデータであれば、CMSIS-DSP内のどの関数でも効果が見込めます。


cmsis_dsp/BasicMathFunctions/arm_dot_prod_q7.c

Committer:
emilmont
Date:
2012-11-28
Revision:
1:fdd22bb7aa52
Child:
2:da51fb522205

File content as of revision 1:fdd22bb7aa52:

/* ----------------------------------------------------------------------    
* Copyright (C) 2010 ARM Limited. All rights reserved.    
*    
* $Date:        15. February 2012  
* $Revision:     V1.1.0  
*    
* Project:         CMSIS DSP Library    
* Title:        arm_dot_prod_q7.c    
*    
* Description:    Q7 dot product.    
*    
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*  
* Version 1.1.0 2012/02/15 
*    Updated with more optimizations, bug fixes and minor API changes.  
*   
* 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 Q7 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.    
 *    
 * <b>Scaling and Overflow Behavior:</b>    
 * \par    
 * The intermediate multiplications are in 1.7 x 1.7 = 2.14 format and these    
 * results are added to an accumulator in 18.14 format.    
 * Nonsaturating additions are used and there is no danger of wrap around as long as    
 * the vectors are less than 2^18 elements long.    
 * The return result is in 18.14 format.    
 */

void arm_dot_prod_q7(
  q7_t * pSrcA,
  q7_t * pSrcB,
  uint32_t blockSize,
  q31_t * result)
{
  uint32_t blkCnt;                               /* loop counter */

  q31_t sum = 0;                                 /* Temporary variables to store output */

#ifndef ARM_MATH_CM0

/* Run the below code for Cortex-M4 and Cortex-M3 */

  q31_t input1, input2;                          /* Temporary variables to store input */
  q31_t inA1, inA2, inB1, inB2;                  /* Temporary variables to store input */



  /*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)
  {
    /* read 4 samples at a time from sourceA */
    input1 = *__SIMD32(pSrcA)++;
    /* read 4 samples at a time from sourceB */
    input2 = *__SIMD32(pSrcB)++;

    /* extract two q7_t samples to q15_t samples */
    inA1 = __SXTB16(__ROR(input1, 8));
    /* extract reminaing two samples */
    inA2 = __SXTB16(input1);
    /* extract two q7_t samples to q15_t samples */
    inB1 = __SXTB16(__ROR(input2, 8));
    /* extract reminaing two samples */
    inB2 = __SXTB16(input2);

    /* multiply and accumulate two samples at a time */
    sum = __SMLAD(inA1, inB1, sum);
    sum = __SMLAD(inA2, inB2, 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] */
    /* Dot product and then store the results in a temporary buffer. */
    sum = __SMLAD(*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] */
    /* Dot product and then store the results in a temporary buffer. */
    sum += (q31_t) ((q15_t) * pSrcA++ * *pSrcB++);

    /* Decrement the loop counter */
    blkCnt--;
  }

#endif /* #ifndef ARM_MATH_CM0 */


  /* Store the result in the destination buffer in 18.14 format */
  *result = sum;
}

/**    
 * @} end of dot_prod group    
 */