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_mult_f32.c

Committer:
mbed_official
Date:
2013-11-08
Revision:
3:7a284390b0ce
Parent:
2:da51fb522205

File content as of revision 3:7a284390b0ce:

/* ----------------------------------------------------------------------    
* Copyright (C) 2010-2013 ARM Limited. All rights reserved.    
*    
* $Date:        17. January 2013 
* $Revision: 	V1.4.1
*    
* Project: 	    CMSIS DSP Library    
* Title:	    arm_mat_mult_f32.c    
*    
* Description:  Floating-point matrix multiplication.    
*    
* 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 groupMatrix    
 */

/**    
 * @defgroup MatrixMult Matrix Multiplication    
 *    
 * Multiplies two matrices.    
 *    
 * \image html MatrixMultiplication.gif "Multiplication of two 3 x 3 matrices"    
    
 * Matrix multiplication is only defined if the number of columns of the    
 * first matrix equals the number of rows of the second matrix.    
 * Multiplying an <code>M x N</code> matrix with an <code>N x P</code> matrix results    
 * in an <code>M x P</code> matrix.    
 * When matrix size checking is enabled, the functions check: (1) that the inner dimensions of    
 * <code>pSrcA</code> and <code>pSrcB</code> are equal; and (2) that the size of the output    
 * matrix equals the outer dimensions of <code>pSrcA</code> and <code>pSrcB</code>.    
 */


/**    
 * @addtogroup MatrixMult    
 * @{    
 */

/**    
 * @brief Floating-point matrix multiplication.    
 * @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_mult_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 *pInA = pSrcA->pData;                /* input data matrix pointer A  */
  float32_t *pOut = pDst->pData;                 /* output data matrix pointer */
  float32_t *px;                                 /* Temporary output data matrix pointer */
  float32_t sum;                                 /* Accumulator */
  uint16_t numRowsA = pSrcA->numRows;            /* number of rows of input matrix A */
  uint16_t numColsB = pSrcB->numCols;            /* number of columns of input matrix B */
  uint16_t numColsA = pSrcA->numCols;            /* number of columns of input matrix A */

#ifndef ARM_MATH_CM0_FAMILY

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

  float32_t in1, in2, in3, in4;
  uint16_t col, i = 0u, j, row = numRowsA, colCnt;      /* loop counters */
  arm_status status;                             /* status of matrix multiplication */

#ifdef ARM_MATH_MATRIX_CHECK


  /* Check for matrix mismatch condition */
  if((pSrcA->numCols != pSrcB->numRows) ||
     (pSrcA->numRows != pDst->numRows) || (pSrcB->numCols != pDst->numCols))
  {

    /* Set status as ARM_MATH_SIZE_MISMATCH */
    status = ARM_MATH_SIZE_MISMATCH;
  }
  else
#endif /*      #ifdef ARM_MATH_MATRIX_CHECK    */

  {
    /* The following loop performs the dot-product of each row in pSrcA with each column in pSrcB */
    /* row loop */
    do
    {
      /* Output pointer is set to starting address of the row being processed */
      px = pOut + i;

      /* For every row wise process, the column loop counter is to be initiated */
      col = numColsB;

      /* For every row wise process, the pIn2 pointer is set    
       ** to the starting address of the pSrcB data */
      pIn2 = pSrcB->pData;

      j = 0u;

      /* column loop */
      do
      {
        /* Set the variable sum, that acts as accumulator, to zero */
        sum = 0.0f;

        /* Initiate the pointer pIn1 to point to the starting address of the column being processed */
        pIn1 = pInA;

        /* Apply loop unrolling and compute 4 MACs simultaneously. */
        colCnt = numColsA >> 2u;

        /* matrix multiplication        */
        while(colCnt > 0u)
        {
          /* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
          in3 = *pIn2;
          pIn2 += numColsB;
          in1 = pIn1[0];
          in2 = pIn1[1];
          sum += in1 * in3;
          in4 = *pIn2;
          pIn2 += numColsB;
          sum += in2 * in4;

          in3 = *pIn2;
          pIn2 += numColsB;
          in1 = pIn1[2];
          in2 = pIn1[3];
          sum += in1 * in3;
          in4 = *pIn2;
          pIn2 += numColsB;
          sum += in2 * in4;
          pIn1 += 4u;

          /* Decrement the loop count */
          colCnt--;
        }

        /* If the columns of pSrcA is not a multiple of 4, compute any remaining MACs here.    
         ** No loop unrolling is used. */
        colCnt = numColsA % 0x4u;

        while(colCnt > 0u)
        {
          /* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
          sum += *pIn1++ * (*pIn2);
          pIn2 += numColsB;

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

        /* Store the result in the destination buffer */
        *px++ = sum;

        /* Update the pointer pIn2 to point to the  starting address of the next column */
        j++;
        pIn2 = pSrcB->pData + j;

        /* Decrement the column loop counter */
        col--;

      } while(col > 0u);

#else

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

  float32_t *pInB = pSrcB->pData;                /* input data matrix pointer B */
  uint16_t col, i = 0u, row = numRowsA, colCnt;  /* loop counters */
  arm_status status;                             /* status of matrix multiplication */

#ifdef ARM_MATH_MATRIX_CHECK

  /* Check for matrix mismatch condition */
  if((pSrcA->numCols != pSrcB->numRows) ||
     (pSrcA->numRows != pDst->numRows) || (pSrcB->numCols != pDst->numCols))
  {

    /* Set status as ARM_MATH_SIZE_MISMATCH */
    status = ARM_MATH_SIZE_MISMATCH;
  }
  else
#endif /*      #ifdef ARM_MATH_MATRIX_CHECK    */

  {
    /* The following loop performs the dot-product of each row in pInA with each column in pInB */
    /* row loop */
    do
    {
      /* Output pointer is set to starting address of the row being processed */
      px = pOut + i;

      /* For every row wise process, the column loop counter is to be initiated */
      col = numColsB;

      /* For every row wise process, the pIn2 pointer is set     
       ** to the starting address of the pSrcB data */
      pIn2 = pSrcB->pData;

      /* column loop */
      do
      {
        /* Set the variable sum, that acts as accumulator, to zero */
        sum = 0.0f;

        /* Initialize the pointer pIn1 to point to the starting address of the row being processed */
        pIn1 = pInA;

        /* Matrix A columns number of MAC operations are to be performed */
        colCnt = numColsA;

        while(colCnt > 0u)
        {
          /* c(m,n) = a(1,1)*b(1,1) + a(1,2) * b(2,1) + .... + a(m,p)*b(p,n) */
          sum += *pIn1++ * (*pIn2);
          pIn2 += numColsB;

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

        /* Store the result in the destination buffer */
        *px++ = sum;

        /* Decrement the column loop counter */
        col--;

        /* Update the pointer pIn2 to point to the  starting address of the next column */
        pIn2 = pInB + (numColsB - col);

      } while(col > 0u);

#endif /* #ifndef ARM_MATH_CM0_FAMILY */

      /* Update the pointer pInA to point to the  starting address of the next row */
      i = i + numColsB;
      pInA = pInA + numColsA;

      /* Decrement the row loop counter */
      row--;

    } while(row > 0u);
    /* Set status as ARM_MATH_SUCCESS */
    status = ARM_MATH_SUCCESS;
  }

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

/**    
 * @} end of MatrixMult group    
 */