Renesas / mbed-dsp-neon

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/StatisticsFunctions/arm_mean_f32.c@1:fdd22bb7aa52, 2012-11-28 (annotated)

Committer:
emilmont
Date:
Wed Nov 28 12:30:09 2012 +0000
Revision:
1:fdd22bb7aa52
Child:
2:da51fb522205
DSP library code

Who changed what in which revision?

UserRevisionLine numberNew contents of line
emilmont 1:fdd22bb7aa52 1 /* ----------------------------------------------------------------------
emilmont 1:fdd22bb7aa52 2 * Copyright (C) 2010 ARM Limited. All rights reserved.
emilmont 1:fdd22bb7aa52 3 *
emilmont 1:fdd22bb7aa52 4 * $Date: 15. February 2012
emilmont 1:fdd22bb7aa52 5 * $Revision: V1.1.0
emilmont 1:fdd22bb7aa52 6 *
emilmont 1:fdd22bb7aa52 7 * Project: CMSIS DSP Library
emilmont 1:fdd22bb7aa52 8 * Title: arm_mean_f32.c
emilmont 1:fdd22bb7aa52 9 *
emilmont 1:fdd22bb7aa52 10 * Description: Mean value of a floating-point vector.
emilmont 1:fdd22bb7aa52 11 *
emilmont 1:fdd22bb7aa52 12 * Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
emilmont 1:fdd22bb7aa52 13 *
emilmont 1:fdd22bb7aa52 14 * Version 1.1.0 2012/02/15
emilmont 1:fdd22bb7aa52 15 * Updated with more optimizations, bug fixes and minor API changes.
emilmont 1:fdd22bb7aa52 16 *
emilmont 1:fdd22bb7aa52 17 * Version 1.0.10 2011/7/15
emilmont 1:fdd22bb7aa52 18 * Big Endian support added and Merged M0 and M3/M4 Source code.
emilmont 1:fdd22bb7aa52 19 *
emilmont 1:fdd22bb7aa52 20 * Version 1.0.3 2010/11/29
emilmont 1:fdd22bb7aa52 21 * Re-organized the CMSIS folders and updated documentation.
emilmont 1:fdd22bb7aa52 22 *
emilmont 1:fdd22bb7aa52 23 * Version 1.0.2 2010/11/11
emilmont 1:fdd22bb7aa52 24 * Documentation updated.
emilmont 1:fdd22bb7aa52 25 *
emilmont 1:fdd22bb7aa52 26 * Version 1.0.1 2010/10/05
emilmont 1:fdd22bb7aa52 27 * Production release and review comments incorporated.
emilmont 1:fdd22bb7aa52 28 *
emilmont 1:fdd22bb7aa52 29 * Version 1.0.0 2010/09/20
emilmont 1:fdd22bb7aa52 30 * Production release and review comments incorporated.
emilmont 1:fdd22bb7aa52 31 * ---------------------------------------------------------------------------- */
emilmont 1:fdd22bb7aa52 32
emilmont 1:fdd22bb7aa52 33 #include "arm_math.h"
emilmont 1:fdd22bb7aa52 34
emilmont 1:fdd22bb7aa52 35 /**
emilmont 1:fdd22bb7aa52 36 * @ingroup groupStats
emilmont 1:fdd22bb7aa52 37 */
emilmont 1:fdd22bb7aa52 38
emilmont 1:fdd22bb7aa52 39 /**
emilmont 1:fdd22bb7aa52 40 * @defgroup mean Mean
emilmont 1:fdd22bb7aa52 41 *
emilmont 1:fdd22bb7aa52 42 * Calculates the mean of the input vector. Mean is defined as the average of the elements in the vector.
emilmont 1:fdd22bb7aa52 43 * The underlying algorithm is used:
emilmont 1:fdd22bb7aa52 44 *
emilmont 1:fdd22bb7aa52 45 * <pre>
emilmont 1:fdd22bb7aa52 46 * Result = (pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1]) / blockSize;
emilmont 1:fdd22bb7aa52 47 * </pre>
emilmont 1:fdd22bb7aa52 48 *
emilmont 1:fdd22bb7aa52 49 * There are separate functions for floating-point, Q31, Q15, and Q7 data types.
emilmont 1:fdd22bb7aa52 50 */
emilmont 1:fdd22bb7aa52 51
emilmont 1:fdd22bb7aa52 52 /**
emilmont 1:fdd22bb7aa52 53 * @addtogroup mean
emilmont 1:fdd22bb7aa52 54 * @{
emilmont 1:fdd22bb7aa52 55 */
emilmont 1:fdd22bb7aa52 56
emilmont 1:fdd22bb7aa52 57
emilmont 1:fdd22bb7aa52 58 /**
emilmont 1:fdd22bb7aa52 59 * @brief Mean value of a floating-point vector.
emilmont 1:fdd22bb7aa52 60 * @param[in] *pSrc points to the input vector
emilmont 1:fdd22bb7aa52 61 * @param[in] blockSize length of the input vector
emilmont 1:fdd22bb7aa52 62 * @param[out] *pResult mean value returned here
emilmont 1:fdd22bb7aa52 63 * @return none.
emilmont 1:fdd22bb7aa52 64 */
emilmont 1:fdd22bb7aa52 65
emilmont 1:fdd22bb7aa52 66
emilmont 1:fdd22bb7aa52 67 void arm_mean_f32(
emilmont 1:fdd22bb7aa52 68 float32_t * pSrc,
emilmont 1:fdd22bb7aa52 69 uint32_t blockSize,
emilmont 1:fdd22bb7aa52 70 float32_t * pResult)
emilmont 1:fdd22bb7aa52 71 {
emilmont 1:fdd22bb7aa52 72 float32_t sum = 0.0f; /* Temporary result storage */
emilmont 1:fdd22bb7aa52 73 uint32_t blkCnt; /* loop counter */
emilmont 1:fdd22bb7aa52 74
emilmont 1:fdd22bb7aa52 75 #ifndef ARM_MATH_CM0
emilmont 1:fdd22bb7aa52 76
emilmont 1:fdd22bb7aa52 77 /* Run the below code for Cortex-M4 and Cortex-M3 */
emilmont 1:fdd22bb7aa52 78 float32_t in1, in2, in3, in4;
emilmont 1:fdd22bb7aa52 79
emilmont 1:fdd22bb7aa52 80 /*loop Unrolling */
emilmont 1:fdd22bb7aa52 81 blkCnt = blockSize >> 2u;
emilmont 1:fdd22bb7aa52 82
emilmont 1:fdd22bb7aa52 83 /* First part of the processing with loop unrolling. Compute 4 outputs at a time.
emilmont 1:fdd22bb7aa52 84 ** a second loop below computes the remaining 1 to 3 samples. */
emilmont 1:fdd22bb7aa52 85 while(blkCnt > 0u)
emilmont 1:fdd22bb7aa52 86 {
emilmont 1:fdd22bb7aa52 87 /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
emilmont 1:fdd22bb7aa52 88 in1 = *pSrc++;
emilmont 1:fdd22bb7aa52 89 in2 = *pSrc++;
emilmont 1:fdd22bb7aa52 90 in3 = *pSrc++;
emilmont 1:fdd22bb7aa52 91 in4 = *pSrc++;
emilmont 1:fdd22bb7aa52 92
emilmont 1:fdd22bb7aa52 93 sum += in1;
emilmont 1:fdd22bb7aa52 94 sum += in2;
emilmont 1:fdd22bb7aa52 95 sum += in3;
emilmont 1:fdd22bb7aa52 96 sum += in4;
emilmont 1:fdd22bb7aa52 97
emilmont 1:fdd22bb7aa52 98 /* Decrement the loop counter */
emilmont 1:fdd22bb7aa52 99 blkCnt--;
emilmont 1:fdd22bb7aa52 100 }
emilmont 1:fdd22bb7aa52 101
emilmont 1:fdd22bb7aa52 102 /* If the blockSize is not a multiple of 4, compute any remaining output samples here.
emilmont 1:fdd22bb7aa52 103 ** No loop unrolling is used. */
emilmont 1:fdd22bb7aa52 104 blkCnt = blockSize % 0x4u;
emilmont 1:fdd22bb7aa52 105
emilmont 1:fdd22bb7aa52 106 #else
emilmont 1:fdd22bb7aa52 107
emilmont 1:fdd22bb7aa52 108 /* Run the below code for Cortex-M0 */
emilmont 1:fdd22bb7aa52 109
emilmont 1:fdd22bb7aa52 110 /* Loop over blockSize number of values */
emilmont 1:fdd22bb7aa52 111 blkCnt = blockSize;
emilmont 1:fdd22bb7aa52 112
emilmont 1:fdd22bb7aa52 113 #endif /* #ifndef ARM_MATH_CM0 */
emilmont 1:fdd22bb7aa52 114
emilmont 1:fdd22bb7aa52 115 while(blkCnt > 0u)
emilmont 1:fdd22bb7aa52 116 {
emilmont 1:fdd22bb7aa52 117 /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) */
emilmont 1:fdd22bb7aa52 118 sum += *pSrc++;
emilmont 1:fdd22bb7aa52 119
emilmont 1:fdd22bb7aa52 120 /* Decrement the loop counter */
emilmont 1:fdd22bb7aa52 121 blkCnt--;
emilmont 1:fdd22bb7aa52 122 }
emilmont 1:fdd22bb7aa52 123
emilmont 1:fdd22bb7aa52 124 /* C = (A[0] + A[1] + A[2] + ... + A[blockSize-1]) / blockSize */
emilmont 1:fdd22bb7aa52 125 /* Store the result to the destination */
emilmont 1:fdd22bb7aa52 126 *pResult = sum / (float32_t) blockSize;
emilmont 1:fdd22bb7aa52 127 }
emilmont 1:fdd22bb7aa52 128
emilmont 1:fdd22bb7aa52 129 /**
emilmont 1:fdd22bb7aa52 130 * @} end of mean group
emilmont 1:fdd22bb7aa52 131 */