Fork of mbed-dsp. CMSIS-DSP library of supporting NEON
Dependents: mbed-os-example-cmsis_dsp_neon
Fork of mbed-dsp by
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。
Diff: cmsis_dsp/StatisticsFunctions/arm_std_f32.c
- Revision:
- 1:fdd22bb7aa52
- Child:
- 2:da51fb522205
diff -r 83d0537c7d84 -r fdd22bb7aa52 cmsis_dsp/StatisticsFunctions/arm_std_f32.c --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cmsis_dsp/StatisticsFunctions/arm_std_f32.c Wed Nov 28 12:30:09 2012 +0000 @@ -0,0 +1,188 @@ +/* ---------------------------------------------------------------------- +* Copyright (C) 2010 ARM Limited. All rights reserved. +* +* $Date: 15. February 2012 +* $Revision: V1.1.0 +* +* Project: CMSIS DSP Library +* Title: arm_std_f32.c +* +* Description: Standard deviation of the elements of a floating-point vector. +* +* 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. +* ---------------------------------------------------------------------------- */ + +#include "arm_math.h" + +/** + * @ingroup groupStats + */ + +/** + * @defgroup STD Standard deviation + * + * Calculates the standard deviation of the elements in the input vector. + * The underlying algorithm is used: + * + * <pre> + * Result = sqrt((sumOfSquares - sum<sup>2</sup> / blockSize) / (blockSize - 1)) + * + * where, sumOfSquares = pSrc[0] * pSrc[0] + pSrc[1] * pSrc[1] + ... + pSrc[blockSize-1] * pSrc[blockSize-1] + * + * sum = pSrc[0] + pSrc[1] + pSrc[2] + ... + pSrc[blockSize-1] + * </pre> + * + * There are separate functions for floating point, Q31, and Q15 data types. + */ + +/** + * @addtogroup STD + * @{ + */ + + +/** + * @brief Standard deviation of the elements of a floating-point vector. + * @param[in] *pSrc points to the input vector + * @param[in] blockSize length of the input vector + * @param[out] *pResult standard deviation value returned here + * @return none. + * + */ + + +void arm_std_f32( + float32_t * pSrc, + uint32_t blockSize, + float32_t * pResult) +{ + float32_t sum = 0.0f; /* Temporary result storage */ + float32_t sumOfSquares = 0.0f; /* Sum of squares */ + float32_t in; /* input value */ + uint32_t blkCnt; /* loop counter */ + +#ifndef ARM_MATH_CM0 + + /* Run the below code for Cortex-M4 and Cortex-M3 */ + + float32_t meanOfSquares, mean, squareOfMean; + + /*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) + { + /* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */ + /* Compute Sum of squares of the input samples + * and then store the result in a temporary variable, sum. */ + in = *pSrc++; + sum += in; + sumOfSquares += in * in; + in = *pSrc++; + sum += in; + sumOfSquares += in * in; + in = *pSrc++; + sum += in; + sumOfSquares += in * in; + in = *pSrc++; + sum += in; + sumOfSquares += in * in; + + /* 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] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */ + /* Compute Sum of squares of the input samples + * and then store the result in a temporary variable, sum. */ + in = *pSrc++; + sum += in; + sumOfSquares += in * in; + + /* Decrement the loop counter */ + blkCnt--; + } + + /* Compute Mean of squares of the input samples + * and then store the result in a temporary variable, meanOfSquares. */ + meanOfSquares = sumOfSquares / ((float32_t) blockSize - 1.0f); + + /* Compute mean of all input values */ + mean = sum / (float32_t) blockSize; + + /* Compute square of mean */ + squareOfMean = (mean * mean) * (((float32_t) blockSize) / + ((float32_t) blockSize - 1.0f)); + + /* Compute standard deviation and then store the result to the destination */ + arm_sqrt_f32((meanOfSquares - squareOfMean), pResult); + +#else + + /* Run the below code for Cortex-M0 */ + + float32_t squareOfSum; /* Square of Sum */ + float32_t var; /* Temporary varaince storage */ + + /* Loop over blockSize number of values */ + blkCnt = blockSize; + + while(blkCnt > 0u) + { + /* C = (A[0] * A[0] + A[1] * A[1] + ... + A[blockSize-1] * A[blockSize-1]) */ + /* Compute Sum of squares of the input samples + * and then store the result in a temporary variable, sumOfSquares. */ + in = *pSrc++; + sumOfSquares += in * in; + + /* C = (A[0] + A[1] + ... + A[blockSize-1]) */ + /* Compute Sum of the input samples + * and then store the result in a temporary variable, sum. */ + sum += in; + + /* Decrement the loop counter */ + blkCnt--; + } + + /* Compute the square of sum */ + squareOfSum = ((sum * sum) / (float32_t) blockSize); + + /* Compute the variance */ + var = ((sumOfSquares - squareOfSum) / (float32_t) (blockSize - 1.0f)); + + /* Compute standard deviation and then store the result to the destination */ + arm_sqrt_f32(var, pResult); + +#endif /* #ifndef ARM_MATH_CM0 */ + +} + +/** + * @} end of STD group + */