Renesas
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
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/MatrixFunctions/arm_mat_inverse_f32.c
- Revision:
- 2:da51fb522205
- Parent:
- 1:fdd22bb7aa52
- Child:
- 3:7a284390b0ce
--- a/cmsis_dsp/MatrixFunctions/arm_mat_inverse_f32.c Wed Nov 28 12:30:09 2012 +0000
+++ b/cmsis_dsp/MatrixFunctions/arm_mat_inverse_f32.c Thu May 30 17:10:11 2013 +0100
@@ -2,12 +2,12 @@
* Copyright (C) 2010 ARM Limited. All rights reserved.
*
* $Date: 15. February 2012
-* $Revision: V1.1.0
+* $Revision: V1.1.0
*
-* Project: CMSIS DSP Library
-* Title: arm_mat_inverse_f32.c
+* Project: CMSIS DSP Library
+* Title: arm_mat_inverse_f32.c
*
-* Description: Floating-point matrix inverse.
+* Description: Floating-point matrix inverse.
*
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*
@@ -67,7 +67,7 @@
* @brief Floating-point matrix inverse.
* @param[in] *pSrc points to input matrix structure
* @param[out] *pDst points to output matrix structure
- * @return The function returns
+ * @return The function returns
* <code>ARM_MATH_SIZE_MISMATCH</code> if the input matrix is not square or if the size
* of the output matrix does not match the size of the input matrix.
* If the input matrix is found to be singular (non-invertible), then the function returns
@@ -110,39 +110,39 @@
{
/*--------------------------------------------------------------------------------------------------------------
- * Matrix Inverse can be solved using elementary row operations.
- *
- * Gauss-Jordan Method:
- *
- * 1. First combine the identity matrix and the input matrix separated by a bar to form an
- * augmented matrix as follows:
- * _ _ _ _
- * | a11 a12 | 1 0 | | X11 X12 |
- * | | | = | |
- * |_ a21 a22 | 0 1 _| |_ X21 X21 _|
- *
- * 2. In our implementation, pDst Matrix is used as identity matrix.
- *
- * 3. Begin with the first row. Let i = 1.
- *
- * 4. Check to see if the pivot for row i is zero.
- * The pivot is the element of the main diagonal that is on the current row.
- * For instance, if working with row i, then the pivot element is aii.
- * If the pivot is zero, exchange that row with a row below it that does not
- * contain a zero in column i. If this is not possible, then an inverse
- * to that matrix does not exist.
- *
- * 5. Divide every element of row i by the pivot.
- *
- * 6. For every row below and row i, replace that row with the sum of that row and
- * a multiple of row i so that each new element in column i below row i is zero.
- *
- * 7. Move to the next row and column and repeat steps 2 through 5 until you have zeros
- * for every element below and above the main diagonal.
- *
- * 8. Now an identical matrix is formed to the left of the bar(input matrix, pSrc).
- * Therefore, the matrix to the right of the bar is our solution(pDst matrix, pDst).
- *----------------------------------------------------------------------------------------------------------------*/
+ * Matrix Inverse can be solved using elementary row operations.
+ *
+ * Gauss-Jordan Method:
+ *
+ * 1. First combine the identity matrix and the input matrix separated by a bar to form an
+ * augmented matrix as follows:
+ * _ _ _ _
+ * | a11 a12 | 1 0 | | X11 X12 |
+ * | | | = | |
+ * |_ a21 a22 | 0 1 _| |_ X21 X21 _|
+ *
+ * 2. In our implementation, pDst Matrix is used as identity matrix.
+ *
+ * 3. Begin with the first row. Let i = 1.
+ *
+ * 4. Check to see if the pivot for row i is zero.
+ * The pivot is the element of the main diagonal that is on the current row.
+ * For instance, if working with row i, then the pivot element is aii.
+ * If the pivot is zero, exchange that row with a row below it that does not
+ * contain a zero in column i. If this is not possible, then an inverse
+ * to that matrix does not exist.
+ *
+ * 5. Divide every element of row i by the pivot.
+ *
+ * 6. For every row below and row i, replace that row with the sum of that row and
+ * a multiple of row i so that each new element in column i below row i is zero.
+ *
+ * 7. Move to the next row and column and repeat steps 2 through 5 until you have zeros
+ * for every element below and above the main diagonal.
+ *
+ * 8. Now an identical matrix is formed to the left of the bar(input matrix, pSrc).
+ * Therefore, the matrix to the right of the bar is our solution(pDst matrix, pDst).
+ *----------------------------------------------------------------------------------------------------------------*/
/* Working pointer for destination matrix */
pInT2 = pOut;
@@ -421,39 +421,39 @@
{
/*--------------------------------------------------------------------------------------------------------------
- * Matrix Inverse can be solved using elementary row operations.
- *
- * Gauss-Jordan Method:
- *
- * 1. First combine the identity matrix and the input matrix separated by a bar to form an
- * augmented matrix as follows:
- * _ _ _ _ _ _ _ _
- * | | a11 a12 | | | 1 0 | | | X11 X12 |
- * | | | | | | | = | |
- * |_ |_ a21 a22 _| | |_0 1 _| _| |_ X21 X21 _|
- *
- * 2. In our implementation, pDst Matrix is used as identity matrix.
- *
- * 3. Begin with the first row. Let i = 1.
- *
- * 4. Check to see if the pivot for row i is zero.
- * The pivot is the element of the main diagonal that is on the current row.
- * For instance, if working with row i, then the pivot element is aii.
- * If the pivot is zero, exchange that row with a row below it that does not
- * contain a zero in column i. If this is not possible, then an inverse
- * to that matrix does not exist.
- *
- * 5. Divide every element of row i by the pivot.
- *
- * 6. For every row below and row i, replace that row with the sum of that row and
- * a multiple of row i so that each new element in column i below row i is zero.
- *
- * 7. Move to the next row and column and repeat steps 2 through 5 until you have zeros
- * for every element below and above the main diagonal.
- *
- * 8. Now an identical matrix is formed to the left of the bar(input matrix, src).
- * Therefore, the matrix to the right of the bar is our solution(dst matrix, dst).
- *----------------------------------------------------------------------------------------------------------------*/
+ * Matrix Inverse can be solved using elementary row operations.
+ *
+ * Gauss-Jordan Method:
+ *
+ * 1. First combine the identity matrix and the input matrix separated by a bar to form an
+ * augmented matrix as follows:
+ * _ _ _ _ _ _ _ _
+ * | | a11 a12 | | | 1 0 | | | X11 X12 |
+ * | | | | | | | = | |
+ * |_ |_ a21 a22 _| | |_0 1 _| _| |_ X21 X21 _|
+ *
+ * 2. In our implementation, pDst Matrix is used as identity matrix.
+ *
+ * 3. Begin with the first row. Let i = 1.
+ *
+ * 4. Check to see if the pivot for row i is zero.
+ * The pivot is the element of the main diagonal that is on the current row.
+ * For instance, if working with row i, then the pivot element is aii.
+ * If the pivot is zero, exchange that row with a row below it that does not
+ * contain a zero in column i. If this is not possible, then an inverse
+ * to that matrix does not exist.
+ *
+ * 5. Divide every element of row i by the pivot.
+ *
+ * 6. For every row below and row i, replace that row with the sum of that row and
+ * a multiple of row i so that each new element in column i below row i is zero.
+ *
+ * 7. Move to the next row and column and repeat steps 2 through 5 until you have zeros
+ * for every element below and above the main diagonal.
+ *
+ * 8. Now an identical matrix is formed to the left of the bar(input matrix, src).
+ * Therefore, the matrix to the right of the bar is our solution(dst matrix, dst).
+ *----------------------------------------------------------------------------------------------------------------*/
/* Working pointer for destination matrix */
pInT2 = pOut;