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。
cmsis_dsp/TransformFunctions/arm_rfft_f32.c
- Committer:
- emilmont
- Date:
- 2013-05-30
- Revision:
- 2:da51fb522205
- Parent:
- 1:fdd22bb7aa52
- Child:
- 3:7a284390b0ce
File content as of revision 2:da51fb522205:
/* ---------------------------------------------------------------------- * Copyright (C) 2010 ARM Limited. All rights reserved. * * $Date: 15. February 2012 * $Revision: V1.1.0 * * Project: CMSIS DSP Library * Title: arm_rfft_f32.c * * Description: RFFT & RIFFT Floating point process function * * 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 0.0.7 2010/06/10 * Misra-C changes done * -------------------------------------------------------------------- */ #include "arm_math.h" /** * @ingroup groupTransforms */ /** * @defgroup RFFT_RIFFT Real FFT Functions * * \par * Complex FFT/IFFT typically assumes complex input and output. However many applications use real valued data in time domain. * Real FFT/IFFT efficiently process real valued sequences with the advantage of requirement of low memory and with less complexity. * * \par * This set of functions implements Real Fast Fourier Transforms(RFFT) and Real Inverse Fast Fourier Transform(RIFFT) * for Q15, Q31, and floating-point data types. * * * \par Algorithm: * * <b>Real Fast Fourier Transform:</b> * \par * Real FFT of N-point is calculated using CFFT of N/2-point and Split RFFT process as shown below figure. * \par * \image html RFFT.gif "Real Fast Fourier Transform" * \par * The RFFT functions operate on blocks of input and output data and each call to the function processes * <code>fftLenR</code> samples through the transform. <code>pSrc</code> points to input array containing <code>fftLenR</code> values. * <code>pDst</code> points to output array containing <code>2*fftLenR</code> values. \n * Input for real FFT is in the order of * <pre>{real[0], real[1], real[2], real[3], ..}</pre> * Output for real FFT is complex and are in the order of * <pre>{real(0), imag(0), real(1), imag(1), ...}</pre> * * <b>Real Inverse Fast Fourier Transform:</b> * \par * Real IFFT of N-point is calculated using Split RIFFT process and CFFT of N/2-point as shown below figure. * \par * \image html RIFFT.gif "Real Inverse Fast Fourier Transform" * \par * The RIFFT functions operate on blocks of input and output data and each call to the function processes * <code>2*fftLenR</code> samples through the transform. <code>pSrc</code> points to input array containing <code>2*fftLenR</code> values. * <code>pDst</code> points to output array containing <code>fftLenR</code> values. \n * Input for real IFFT is complex and are in the order of * <pre>{real(0), imag(0), real(1), imag(1), ...}</pre> * Output for real IFFT is real and in the order of * <pre>{real[0], real[1], real[2], real[3], ..}</pre> * * \par Lengths supported by the transform: * \par * Real FFT/IFFT supports the lengths [128, 512, 2048], as it internally uses CFFT/CIFFT. * * \par Instance Structure * A separate instance structure must be defined for each Instance but the twiddle factors can be reused. * There are separate instance structure declarations for each of the 3 supported data types. * * \par Initialization Functions * There is also an associated initialization function for each data type. * The initialization function performs the following operations: * - Sets the values of the internal structure fields. * - Initializes twiddle factor tables. * - Initializes CFFT data structure fields. * \par * Use of the initialization function is optional. * However, if the initialization function is used, then the instance structure cannot be placed into a const data section. * To place an instance structure into a const data section, the instance structure must be manually initialized. * Manually initialize the instance structure as follows: * <pre> *arm_rfft_instance_f32 S = {fftLenReal, fftLenBy2, ifftFlagR, bitReverseFlagR, twidCoefRModifier, pTwiddleAReal, pTwiddleBReal, pCfft}; *arm_rfft_instance_q31 S = {fftLenReal, fftLenBy2, ifftFlagR, bitReverseFlagR, twidCoefRModifier, pTwiddleAReal, pTwiddleBReal, pCfft}; *arm_rfft_instance_q15 S = {fftLenReal, fftLenBy2, ifftFlagR, bitReverseFlagR, twidCoefRModifier, pTwiddleAReal, pTwiddleBReal, pCfft}; * </pre> * where <code>fftLenReal</code> length of RFFT/RIFFT; <code>fftLenBy2</code> length of CFFT/CIFFT. * <code>ifftFlagR</code> Flag for selection of RFFT or RIFFT(Set ifftFlagR to calculate RIFFT otherwise calculates RFFT); * <code>bitReverseFlagR</code> Flag for selection of output order(Set bitReverseFlagR to output in normal order otherwise output in bit reversed order); * <code>twidCoefRModifier</code> modifier for twiddle factor table which supports 128, 512, 2048 RFFT lengths with same table; * <code>pTwiddleAReal</code>points to A array of twiddle coefficients; <code>pTwiddleBReal</code>points to B array of twiddle coefficients; * <code>pCfft</code> points to the CFFT Instance structure. The CFFT structure also needs to be initialized, refer to arm_cfft_radix4_f32() for details regarding * static initialization of cfft structure. * * \par Fixed-Point Behavior * Care must be taken when using the fixed-point versions of the RFFT/RIFFT function. * Refer to the function specific documentation below for usage guidelines. */ /*-------------------------------------------------------------------- * Internal functions prototypes *--------------------------------------------------------------------*/ void arm_split_rfft_f32( float32_t * pSrc, uint32_t fftLen, float32_t * pATable, float32_t * pBTable, float32_t * pDst, uint32_t modifier); void arm_split_rifft_f32( float32_t * pSrc, uint32_t fftLen, float32_t * pATable, float32_t * pBTable, float32_t * pDst, uint32_t modifier); /** * @addtogroup RFFT_RIFFT * @{ */ /** * @brief Processing function for the floating-point RFFT/RIFFT. * @param[in] *S points to an instance of the floating-point RFFT/RIFFT structure. * @param[in] *pSrc points to the input buffer. * @param[out] *pDst points to the output buffer. * @return none. */ void arm_rfft_f32( const arm_rfft_instance_f32 * S, float32_t * pSrc, float32_t * pDst) { const arm_cfft_radix4_instance_f32 *S_CFFT = S->pCfft; /* Calculation of Real IFFT of input */ if(S->ifftFlagR == 1u) { /* Real IFFT core process */ arm_split_rifft_f32(pSrc, S->fftLenBy2, S->pTwiddleAReal, S->pTwiddleBReal, pDst, S->twidCoefRModifier); /* Complex radix-4 IFFT process */ arm_radix4_butterfly_inverse_f32(pDst, S_CFFT->fftLen, S_CFFT->pTwiddle, S_CFFT->twidCoefModifier, S_CFFT->onebyfftLen); /* Bit reversal process */ if(S->bitReverseFlagR == 1u) { arm_bitreversal_f32(pDst, S_CFFT->fftLen, S_CFFT->bitRevFactor, S_CFFT->pBitRevTable); } } else { /* Calculation of RFFT of input */ /* Complex radix-4 FFT process */ arm_radix4_butterfly_f32(pSrc, S_CFFT->fftLen, S_CFFT->pTwiddle, S_CFFT->twidCoefModifier); /* Bit reversal process */ if(S->bitReverseFlagR == 1u) { arm_bitreversal_f32(pSrc, S_CFFT->fftLen, S_CFFT->bitRevFactor, S_CFFT->pBitRevTable); } /* Real FFT core process */ arm_split_rfft_f32(pSrc, S->fftLenBy2, S->pTwiddleAReal, S->pTwiddleBReal, pDst, S->twidCoefRModifier); } } /** * @} end of RFFT_RIFFT group */ /** * @brief Core Real FFT process * @param[in] *pSrc points to the input buffer. * @param[in] fftLen length of FFT. * @param[in] *pATable points to the twiddle Coef A buffer. * @param[in] *pBTable points to the twiddle Coef B buffer. * @param[out] *pDst points to the output buffer. * @param[in] modifier twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. * @return none. */ void arm_split_rfft_f32( float32_t * pSrc, uint32_t fftLen, float32_t * pATable, float32_t * pBTable, float32_t * pDst, uint32_t modifier) { uint32_t i; /* Loop Counter */ float32_t outR, outI; /* Temporary variables for output */ float32_t *pCoefA, *pCoefB; /* Temporary pointers for twiddle factors */ float32_t CoefA1, CoefA2, CoefB1; /* Temporary variables for twiddle coefficients */ float32_t *pDst1 = &pDst[2], *pDst2 = &pDst[(4u * fftLen) - 1u]; /* temp pointers for output buffer */ float32_t *pSrc1 = &pSrc[2], *pSrc2 = &pSrc[(2u * fftLen) - 1u]; /* temp pointers for input buffer */ /* Init coefficient pointers */ pCoefA = &pATable[modifier * 2u]; pCoefB = &pBTable[modifier * 2u]; i = fftLen - 1u; while(i > 0u) { /* outR = (pSrc[2 * i] * pATable[2 * i] - pSrc[2 * i + 1] * pATable[2 * i + 1] + pSrc[2 * n - 2 * i] * pBTable[2 * i] + pSrc[2 * n - 2 * i + 1] * pBTable[2 * i + 1]); */ /* outI = (pIn[2 * i + 1] * pATable[2 * i] + pIn[2 * i] * pATable[2 * i + 1] + pIn[2 * n - 2 * i] * pBTable[2 * i + 1] - pIn[2 * n - 2 * i + 1] * pBTable[2 * i]); */ /* read pATable[2 * i] */ CoefA1 = *pCoefA++; /* pATable[2 * i + 1] */ CoefA2 = *pCoefA; /* pSrc[2 * i] * pATable[2 * i] */ outR = *pSrc1 * CoefA1; /* pSrc[2 * i] * CoefA2 */ outI = *pSrc1++ * CoefA2; /* (pSrc[2 * i + 1] + pSrc[2 * fftLen - 2 * i + 1]) * CoefA2 */ outR -= (*pSrc1 + *pSrc2) * CoefA2; /* pSrc[2 * i + 1] * CoefA1 */ outI += *pSrc1++ * CoefA1; CoefB1 = *pCoefB; /* pSrc[2 * fftLen - 2 * i + 1] * CoefB1 */ outI -= *pSrc2-- * CoefB1; /* pSrc[2 * fftLen - 2 * i] * CoefA2 */ outI -= *pSrc2 * CoefA2; /* pSrc[2 * fftLen - 2 * i] * CoefB1 */ outR += *pSrc2-- * CoefB1; /* write output */ *pDst1++ = outR; *pDst1++ = outI; /* write complex conjugate output */ *pDst2-- = -outI; *pDst2-- = outR; /* update coefficient pointer */ pCoefB = pCoefB + (modifier * 2u); pCoefA = pCoefA + ((modifier * 2u) - 1u); i--; } pDst[2u * fftLen] = pSrc[0] - pSrc[1]; pDst[(2u * fftLen) + 1u] = 0.0f; pDst[0] = pSrc[0] + pSrc[1]; pDst[1] = 0.0f; } /** * @brief Core Real IFFT process * @param[in] *pSrc points to the input buffer. * @param[in] fftLen length of FFT. * @param[in] *pATable points to the twiddle Coef A buffer. * @param[in] *pBTable points to the twiddle Coef B buffer. * @param[out] *pDst points to the output buffer. * @param[in] modifier twiddle coefficient modifier that supports different size FFTs with the same twiddle factor table. * @return none. */ void arm_split_rifft_f32( float32_t * pSrc, uint32_t fftLen, float32_t * pATable, float32_t * pBTable, float32_t * pDst, uint32_t modifier) { float32_t outR, outI; /* Temporary variables for output */ float32_t *pCoefA, *pCoefB; /* Temporary pointers for twiddle factors */ float32_t CoefA1, CoefA2, CoefB1; /* Temporary variables for twiddle coefficients */ float32_t *pSrc1 = &pSrc[0], *pSrc2 = &pSrc[(2u * fftLen) + 1u]; pCoefA = &pATable[0]; pCoefB = &pBTable[0]; while(fftLen > 0u) { /* outR = (pIn[2 * i] * pATable[2 * i] + pIn[2 * i + 1] * pATable[2 * i + 1] + pIn[2 * n - 2 * i] * pBTable[2 * i] - pIn[2 * n - 2 * i + 1] * pBTable[2 * i + 1]); outI = (pIn[2 * i + 1] * pATable[2 * i] - pIn[2 * i] * pATable[2 * i + 1] - pIn[2 * n - 2 * i] * pBTable[2 * i + 1] - pIn[2 * n - 2 * i + 1] * pBTable[2 * i]); */ CoefA1 = *pCoefA++; CoefA2 = *pCoefA; /* outR = (pSrc[2 * i] * CoefA1 */ outR = *pSrc1 * CoefA1; /* - pSrc[2 * i] * CoefA2 */ outI = -(*pSrc1++) * CoefA2; /* (pSrc[2 * i + 1] + pSrc[2 * fftLen - 2 * i + 1]) * CoefA2 */ outR += (*pSrc1 + *pSrc2) * CoefA2; /* pSrc[2 * i + 1] * CoefA1 */ outI += (*pSrc1++) * CoefA1; CoefB1 = *pCoefB; /* - pSrc[2 * fftLen - 2 * i + 1] * CoefB1 */ outI -= *pSrc2-- * CoefB1; /* pSrc[2 * fftLen - 2 * i] * CoefB1 */ outR += *pSrc2 * CoefB1; /* pSrc[2 * fftLen - 2 * i] * CoefA2 */ outI += *pSrc2-- * CoefA2; /* write output */ *pDst++ = outR; *pDst++ = outI; /* update coefficient pointer */ pCoefB = pCoefB + (modifier * 2u); pCoefA = pCoefA + ((modifier * 2u) - 1u); /* Decrement loop count */ fftLen--; } }