Fork of mbed-dsp. CMSIS-DSP library of supporting NEON
Dependents: mbed-os-example-cmsis_dsp_neon
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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。
Diff: cmsis_dsp/StatisticsFunctions/arm_var_q15.c
- Revision:
- 1:fdd22bb7aa52
- Child:
- 2:da51fb522205
diff -r 83d0537c7d84 -r fdd22bb7aa52 cmsis_dsp/StatisticsFunctions/arm_var_q15.c --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/cmsis_dsp/StatisticsFunctions/arm_var_q15.c Wed Nov 28 12:30:09 2012 +0000 @@ -0,0 +1,180 @@ +/* ---------------------------------------------------------------------- +* Copyright (C) 2010 ARM Limited. All rights reserved. +* +* $Date: 15. February 2012 +* $Revision: V1.1.0 +* +* Project: CMSIS DSP Library +* Title: arm_var_q15.c +* +* Description: Variance of an array of Q15 type. +* +* 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 + */ + +/** + * @addtogroup variance + * @{ + */ + +/** + * @brief Variance of the elements of a Q15 vector. + * @param[in] *pSrc points to the input vector + * @param[in] blockSize length of the input vector + * @param[out] *pResult variance value returned here + * @return none. + * + * @details + * <b>Scaling and Overflow Behavior:</b> + * + * \par + * The function is implemented using a 64-bit internal accumulator. + * The input is represented in 1.15 format. + * Intermediate multiplication yields a 2.30 format, and this + * result is added without saturation to a 64-bit accumulator in 34.30 format. + * With 33 guard bits in the accumulator, there is no risk of overflow, and the + * full precision of the intermediate multiplication is preserved. + * Finally, the 34.30 result is truncated to 34.15 format by discarding the lower + * 15 bits, and then saturated to yield a result in 1.15 format. + * + */ + + +void arm_var_q15( + q15_t * pSrc, + uint32_t blockSize, + q31_t * pResult) +{ + q31_t sum = 0; /* Accumulator */ + q31_t meanOfSquares, squareOfMean; /* Mean of square and square of mean */ + q15_t mean; /* mean */ + uint32_t blkCnt; /* loop counter */ + q15_t t; /* Temporary variable */ + q63_t sumOfSquares = 0; /* Accumulator */ + +#ifndef ARM_MATH_CM0 + + /* Run the below code for Cortex-M4 and Cortex-M3 */ + + q31_t in; /* Input variable */ + q15_t in1; /* Temporary variable */ + + /*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 = *__SIMD32(pSrc)++; + sum += ((in << 16) >> 16); + sum += (in >> 16); + sumOfSquares = __SMLALD(in, in, sumOfSquares); + in = *__SIMD32(pSrc)++; + sum += ((in << 16) >> 16); + sum += (in >> 16); + sumOfSquares = __SMLALD(in, in, sumOfSquares); + + /* 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. */ + in1 = *pSrc++; + sum += in1; + sumOfSquares = __SMLALD(in1, in1, sumOfSquares); + + /* Decrement the loop counter */ + blkCnt--; + } + + /* Compute Mean of squares of the input samples + * and then store the result in a temporary variable, meanOfSquares. */ + t = (q15_t) ((1.0f / (float32_t) (blockSize - 1u)) * 16384); + sumOfSquares = __SSAT((sumOfSquares >> 15u), 16u); + + meanOfSquares = (q31_t) ((sumOfSquares * t) >> 14u); + +#else + + /* Run the below code for Cortex-M0 */ + + q15_t in; /* Temporary variable */ + /* 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[2] + ... + A[blockSize-1]) */ + /* Compute sum of all input values and then store the result in a temporary variable, sum. */ + sum += in; + + /* Decrement the loop counter */ + blkCnt--; + } + + /* Compute Mean of squares of the input samples + * and then store the result in a temporary variable, meanOfSquares. */ + t = (q15_t) ((1.0f / (float32_t) (blockSize - 1u)) * 16384); + sumOfSquares = __SSAT((sumOfSquares >> 15u), 16u); + meanOfSquares = (q31_t) ((sumOfSquares * t) >> 14u); + +#endif /* #ifndef ARM_MATH_CM0 */ + + /* Compute mean of all input values */ + t = (q15_t) ((1.0f / (float32_t) (blockSize * (blockSize - 1u))) * 32768); + mean = __SSAT(sum, 16u); + + /* Compute square of mean */ + squareOfMean = ((q31_t) mean * mean) >> 15; + squareOfMean = (q31_t) (((q63_t) squareOfMean * t) >> 15); + + /* Compute variance and then store the result to the destination */ + *pResult = (meanOfSquares - squareOfMean); + +} + +/** + * @} end of variance group + */