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/MatrixFunctions/arm_mat_add_f32.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_add_f32.c    
*    
* Description:    Floating-point matrix addition    
*    
* 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        
 */

/**        
 * @defgroup MatrixAdd Matrix Addition        
 *        
 * Adds two matrices.        
 * \image html MatrixAddition.gif "Addition of two 3 x 3 matrices"        
 *        
 * The functions check to make sure that        
 * <code>pSrcA</code>, <code>pSrcB</code>, and <code>pDst</code> have the same        
 * number of rows and columns.        
 */

/**        
 * @addtogroup MatrixAdd        
 * @{        
 */


/**        
 * @brief Floating-point matrix addition.        
 * @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.        
 */

arm_status arm_mat_add_f32(
  const arm_matrix_instance_f32 * pSrcA,
  const arm_matrix_instance_f32 * pSrcB,
  arm_matrix_instance_f32 * pDst)
{
  float32_t *pIn1 = pSrcA->pData;                /* input data matrix pointer A  */
  float32_t *pIn2 = pSrcB->pData;                /* input data matrix pointer B  */
  float32_t *pOut = pDst->pData;                 /* output data matrix pointer   */

#ifndef ARM_MATH_CM0

  float32_t inA1, inA2, inB1, inB2, out1, out2;  /* temporary variables */

#endif //      #ifndef ARM_MATH_CM0

  uint32_t numSamples;                           /* total number of elements in the matrix  */
  uint32_t blkCnt;                               /* loop counters */
  arm_status status;                             /* status of matrix addition */

#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
  {

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

#ifndef ARM_MATH_CM0

    /* 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) */
      /* Add and then store the results in the destination buffer. */
      /* Read values from source A */
      inA1 = pIn1[0];

      /* Read values from source B */
      inB1 = pIn2[0];

      /* Read values from source A */
      inA2 = pIn1[1];

      /* out = sourceA + sourceB */
      out1 = inA1 + inB1;

      /* Read values from source B */
      inB2 = pIn2[1];

      /* Read values from source A */
      inA1 = pIn1[2];

      /* out = sourceA + sourceB */
      out2 = inA2 + inB2;

      /* Read values from source B */
      inB1 = pIn2[2];

      /* Store result in destination */
      pOut[0] = out1;
      pOut[1] = out2;

      /* Read values from source A */
      inA2 = pIn1[3];

      /* Read values from source B */
      inB2 = pIn2[3];

      /* out = sourceA + sourceB */
      out1 = inA1 + inB1;

      /* out = sourceA + sourceB */
      out2 = inA2 + inB2;

      /* Store result in destination */
      pOut[2] = out1;

      /* Store result in destination */
      pOut[3] = out2;


      /* update pointers to process next sampels */
      pIn1 += 4u;
      pIn2 += 4u;
      pOut += 4u;
      /* Decrement the loop counter */
      blkCnt--;
    }

    /* If the numSamples is not a multiple of 4, compute any remaining output samples here.    
     ** No loop unrolling is used. */
    blkCnt = numSamples % 0x4u;

#else

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

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

#endif /* #ifndef ARM_MATH_CM0 */

    while(blkCnt > 0u)
    {
      /* C(m,n) = A(m,n) + B(m,n) */
      /* Add and then store the results in the destination buffer. */
      *pOut++ = (*pIn1++) + (*pIn2++);

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

    /* set status as ARM_MATH_SUCCESS */
    status = ARM_MATH_SUCCESS;

  }

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

/**        
 * @} end of MatrixAdd group        
 */