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

Japanese version is available in lower part of this page.
このページの後半に日本語版が用意されています.

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/MatrixFunctions/arm_mat_sub_q15.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_mat_sub_q15.c    
*    
* Description:    Q15 Matrix subtraction    
*    
* 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 0.0.5  2010/04/26     
*    incorporated review comments and updated with latest CMSIS layer    
*    
* Version 0.0.3  2010/03/10     
*    Initial version    
* -------------------------------------------------------------------- */

#include "arm_math.h"

/**    
 * @ingroup groupMatrix    
 */

/**    
 * @addtogroup MatrixSub    
 * @{    
 */

/**    
 * @brief Q15 matrix subtraction.    
 * @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    
 * @return             The function returns either    
 * <code>ARM_MATH_SIZE_MISMATCH</code> or <code>ARM_MATH_SUCCESS</code> based on the outcome of size checking.    
 *    
 * <b>Scaling and Overflow Behavior:</b>    
 * \par    
 * The function uses saturating arithmetic.    
 * Results outside of the allowable Q15 range [0x8000 0x7FFF] will be saturated.    
 */

arm_status arm_mat_sub_q15(
  const arm_matrix_instance_q15 * pSrcA,
  const arm_matrix_instance_q15 * pSrcB,
  arm_matrix_instance_q15 * pDst)
{
  q15_t *pInA = pSrcA->pData;                    /* input data matrix pointer A */
  q15_t *pInB = pSrcB->pData;                    /* input data matrix pointer B */
  q15_t *pOut = pDst->pData;                     /* output data matrix pointer */
  uint32_t numSamples;                           /* total number of elements in the matrix */
  uint32_t blkCnt;                               /* loop counters  */
  arm_status status;                             /* status of matrix subtraction  */


#ifdef ARM_MATH_MATRIX_CHECK


  /* Check for matrix mismatch condition */
  if((pSrcA->numRows != pSrcB->numRows) ||
     (pSrcA->numCols != pSrcB->numCols) ||
     (pSrcA->numRows != pDst->numRows) || (pSrcA->numCols != pDst->numCols))
  {
    /* Set status as ARM_MATH_SIZE_MISMATCH */
    status = ARM_MATH_SIZE_MISMATCH;
  }
  else
#endif /*    #ifdef ARM_MATH_MATRIX_CHECK    */

  {
    /* Total number of samples in the input matrix */
    numSamples = (uint32_t) pSrcA->numRows * pSrcA->numCols;

#ifndef ARM_MATH_CM0

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

    /* Apply loop unrolling */
    blkCnt = numSamples >> 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)
    {
      /* C(m,n) = A(m,n) - B(m,n) */
      /* Subtract, Saturate and then store the results in the destination buffer. */
      *__SIMD32(pOut)++ = __QSUB16(*__SIMD32(pInA)++, *__SIMD32(pInB)++);
      *__SIMD32(pOut)++ = __QSUB16(*__SIMD32(pInA)++, *__SIMD32(pInB)++);

      /* 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 = numSamples % 0x4u;

    while(blkCnt > 0u)
    {
      /* C(m,n) = A(m,n) - B(m,n) */
      /* Subtract and then store the results in the destination buffer. */
      *pOut++ = (q15_t) __QSUB16(*pInA++, *pInB++);

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

#else

    /* Run the below code for Cortex-M0 */

    /* Initialize blkCnt with number of samples */
    blkCnt = numSamples;

    while(blkCnt > 0u)
    {
      /* C(m,n) = A(m,n) - B(m,n) */
      /* Subtract and then store the results in the destination buffer. */
      *pOut++ = (q15_t) __SSAT(((q31_t) * pInA++ - *pInB++), 16);

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

#endif /* #ifndef ARM_MATH_CM0 */

    /* Set status as ARM_MATH_SUCCESS */
    status = ARM_MATH_SUCCESS;
  }

  /* Return to application */
  return (status);
}

/**    
 * @} end of MatrixSub group    
 */