arm_mat_qr_f32.c 20 KB

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  1. /* ----------------------------------------------------------------------
  2. * Project: CMSIS DSP Library
  3. * Title: arm_mat_qr_f32.c
  4. * Description: Floating-point matrix QR decomposition.
  5. *
  6. * $Date: 15 June 2022
  7. * $Revision: V1.11.0
  8. *
  9. * Target Processor: Cortex-M and Cortex-A cores
  10. * -------------------------------------------------------------------- */
  11. /*
  12. * Copyright (C) 2010-2022 ARM Limited or its affiliates. All rights reserved.
  13. *
  14. * SPDX-License-Identifier: Apache-2.0
  15. *
  16. * Licensed under the Apache License, Version 2.0 (the License); you may
  17. * not use this file except in compliance with the License.
  18. * You may obtain a copy of the License at
  19. *
  20. * www.apache.org/licenses/LICENSE-2.0
  21. *
  22. * Unless required by applicable law or agreed to in writing, software
  23. * distributed under the License is distributed on an AS IS BASIS, WITHOUT
  24. * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  25. * See the License for the specific language governing permissions and
  26. * limitations under the License.
  27. */
  28. #include "dsp/matrix_functions.h"
  29. #include "dsp/matrix_utils.h"
  30. #if !defined(ARM_MATH_AUTOVECTORIZE)
  31. #if defined(ARM_MATH_MVEF)
  32. #include "arm_helium_utils.h"
  33. #endif
  34. #endif
  35. /**
  36. @ingroup groupMatrix
  37. */
  38. /**
  39. @defgroup MatrixQR QR decomposition of a Matrix
  40. Computes the QR decomposition of a matrix M using Householder algorithm.
  41. \f[
  42. M = Q R
  43. \f]
  44. where Q is an orthogonal matrix and R is upper triangular.
  45. No pivoting strategy is used.
  46. The returned value for R is using a format a bit similar
  47. to LAPACK : it is not just containing the matrix R but
  48. also the Householder reflectors.
  49. The function is also returning a vector \f$\tau\f$
  50. that is containing the scaling factor for the reflectors.
  51. Returned value R has the structure:
  52. \f[
  53. \begin{pmatrix}
  54. r_{11} & r_{12} & \dots & r_{1n} \\
  55. v_{12} & r_{22} & \dots & r_{2n} \\
  56. v_{13} & v_{22} & \dots & r_{3n} \\
  57. \vdots & \vdots & \ddots & \vdots \\
  58. v_{1m} & v_{2(m-1)} & \dots & r_{mn} \\
  59. \end{pmatrix}
  60. \f]
  61. where
  62. \f[
  63. v_1 =
  64. \begin{pmatrix}
  65. 1 \\
  66. v_{12} \\
  67. \vdots \\
  68. v_{1m} \\
  69. \end{pmatrix}
  70. \f]
  71. is the first householder reflector.
  72. The Householder Matrix is given by \f$H_1\f$
  73. \f[
  74. H_1 = I - \tau_1 v_1 v_1^T
  75. \f]
  76. The Matrix Q is the product of the Householder matrices:
  77. \f[
  78. Q = H_1 H_2 \dots H_n
  79. \f]
  80. The computation of the matrix Q by this function is
  81. optional.
  82. And the matrix R, would be the returned value R without the
  83. householder reflectors:
  84. \f[
  85. \begin{pmatrix}
  86. r_{11} & r_{12} & \dots & r_{1n} \\
  87. 0 & r_{22} & \dots & r_{2n} \\
  88. 0 & 0 & \dots & r_{3n} \\
  89. \vdots & \vdots & \ddots & \vdots \\
  90. 0 & 0 & \dots & r_{mn} \\
  91. \end{pmatrix}
  92. \f]
  93. */
  94. /**
  95. @addtogroup MatrixQR
  96. @{
  97. */
  98. /**
  99. @brief QR decomposition of a m x n floating point matrix with m >= n.
  100. @param[in] pSrc points to input matrix structure. The source matrix is modified by the function.
  101. @param[in] threshold norm2 threshold.
  102. @param[out] pOutR points to output R matrix structure of dimension m x n
  103. @param[out] pOutQ points to output Q matrix structure of dimension m x m (can be NULL)
  104. @param[out] pOutTau points to Householder scaling factors of dimension n
  105. @param[inout] pTmpA points to a temporary vector of dimension m.
  106. @param[inout] pTmpB points to a temporary vector of dimension m.
  107. @return execution status
  108. - \ref ARM_MATH_SUCCESS : Operation successful
  109. - \ref ARM_MATH_SIZE_MISMATCH : Matrix size check failed
  110. @par pOutQ is optional:
  111. pOutQ can be a NULL pointer.
  112. In this case, the argument will be ignored
  113. and the output Q matrix won't be computed.
  114. @par Norm2 threshold
  115. For the meaning of this argument please
  116. refer to the \ref MatrixHouseholder documentation
  117. */
  118. #if !defined(ARM_MATH_AUTOVECTORIZE)
  119. #if defined(ARM_MATH_MVEF)
  120. arm_status arm_mat_qr_f32(
  121. const arm_matrix_instance_f32 * pSrc,
  122. const float32_t threshold,
  123. arm_matrix_instance_f32 * pOutR,
  124. arm_matrix_instance_f32 * pOutQ,
  125. float32_t * pOutTau,
  126. float32_t *pTmpA,
  127. float32_t *pTmpB
  128. )
  129. {
  130. int32_t col=0;
  131. int32_t nb,pos;
  132. float32_t *pa,*pc;
  133. float32_t beta;
  134. float32_t *pv;
  135. float32_t *pdst;
  136. float32_t *p;
  137. if (pSrc->numRows < pSrc->numCols)
  138. {
  139. return(ARM_MATH_SIZE_MISMATCH);
  140. }
  141. memcpy(pOutR->pData,pSrc->pData,pSrc->numCols * pSrc->numRows*sizeof(float32_t));
  142. pOutR->numCols = pSrc->numCols;
  143. pOutR->numRows = pSrc->numRows;
  144. p = pOutR->pData;
  145. pc = pOutTau;
  146. for(col=0 ; col < pSrc->numCols; col++)
  147. {
  148. int32_t j,k,blkCnt,blkCnt2;
  149. float32_t *pa0,*pa1,*pa2,*pa3,*ptemp;
  150. float32_t temp;
  151. float32x4_t v1,v2,vtemp;
  152. COPY_COL_F32(pOutR,col,col,pTmpA);
  153. beta = arm_householder_f32(pTmpA,threshold,pSrc->numRows - col,pTmpA);
  154. *pc++ = beta;
  155. pdst = pTmpB;
  156. /* v.T A(col:,col:) -> tmpb */
  157. pv = pTmpA;
  158. pa = p;
  159. temp = *pv;
  160. blkCnt = (pSrc->numCols-col) >> 2;
  161. while (blkCnt > 0)
  162. {
  163. v1 = vld1q_f32(pa);
  164. v2 = vmulq_n_f32(v1,temp);
  165. vst1q_f32(pdst,v2);
  166. pa += 4;
  167. pdst += 4;
  168. blkCnt--;
  169. }
  170. blkCnt = (pSrc->numCols-col) & 3;
  171. if (blkCnt > 0)
  172. {
  173. mve_pred16_t p0 = vctp32q(blkCnt);
  174. v1 = vld1q_f32(pa);
  175. v2 = vmulq_n_f32(v1,temp);
  176. vst1q_p_f32(pdst,v2,p0);
  177. pa += blkCnt;
  178. }
  179. pa += col;
  180. pv++;
  181. pdst = pTmpB;
  182. pa0 = pa;
  183. pa1 = pa0 + pSrc->numCols;
  184. pa2 = pa1 + pSrc->numCols;
  185. pa3 = pa2 + pSrc->numCols;
  186. /* Unrolled loop */
  187. blkCnt = (pSrc->numRows-col - 1) >> 2;
  188. k=1;
  189. while(blkCnt > 0)
  190. {
  191. vtemp=vld1q_f32(pv);
  192. blkCnt2 = (pSrc->numCols-col) >> 2;
  193. while (blkCnt2 > 0)
  194. {
  195. v1 = vld1q_f32(pdst);
  196. v2 = vld1q_f32(pa0);
  197. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,0));
  198. v2 = vld1q_f32(pa1);
  199. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,1));
  200. v2 = vld1q_f32(pa2);
  201. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,2));
  202. v2 = vld1q_f32(pa3);
  203. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,3));
  204. vst1q_f32(pdst,v1);
  205. pdst += 4;
  206. pa0 += 4;
  207. pa1 += 4;
  208. pa2 += 4;
  209. pa3 += 4;
  210. blkCnt2--;
  211. }
  212. blkCnt2 = (pSrc->numCols-col) & 3;
  213. if (blkCnt2 > 0)
  214. {
  215. mve_pred16_t p0 = vctp32q(blkCnt2);
  216. v1 = vld1q_f32(pdst);
  217. v2 = vld1q_f32(pa0);
  218. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,0));
  219. v2 = vld1q_f32(pa1);
  220. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,1));
  221. v2 = vld1q_f32(pa2);
  222. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,2));
  223. v2 = vld1q_f32(pa3);
  224. v1 = vfmaq_n_f32(v1,v2,vgetq_lane(vtemp,3));
  225. vst1q_p_f32(pdst,v1,p0);
  226. pa0 += blkCnt2;
  227. pa1 += blkCnt2;
  228. pa2 += blkCnt2;
  229. pa3 += blkCnt2;
  230. }
  231. pa0 += col + 3*pSrc->numCols;
  232. pa1 += col + 3*pSrc->numCols;
  233. pa2 += col + 3*pSrc->numCols;
  234. pa3 += col + 3*pSrc->numCols;
  235. pv += 4;
  236. pdst = pTmpB;
  237. k += 4;
  238. blkCnt--;
  239. }
  240. pa = pa0;
  241. for(;k<pSrc->numRows-col; k++)
  242. {
  243. temp = *pv;
  244. blkCnt2 = (pSrc->numCols-col) >> 2;
  245. while (blkCnt2 > 0)
  246. {
  247. v1 = vld1q_f32(pa);
  248. v2 = vld1q_f32(pdst);
  249. v2 = vfmaq_n_f32(v2,v1,temp);
  250. vst1q_f32(pdst,v2);
  251. pa += 4;
  252. pdst += 4;
  253. blkCnt2--;
  254. }
  255. blkCnt2 = (pSrc->numCols-col) & 3;
  256. if (blkCnt2 > 0)
  257. {
  258. mve_pred16_t p0 = vctp32q(blkCnt2);
  259. v1 = vld1q_f32(pa);
  260. v2 = vld1q_f32(pdst);
  261. v2 = vfmaq_n_f32(v2,v1,temp);
  262. vst1q_p_f32(pdst,v2,p0);
  263. pa += blkCnt2;
  264. }
  265. pa += col;
  266. pv++;
  267. pdst = pTmpB;
  268. }
  269. /* A(col:,col:) - beta v tmpb */
  270. pa = p;
  271. for(j=0;j<pSrc->numRows-col; j++)
  272. {
  273. float32_t f = -beta * pTmpA[j];
  274. ptemp = pTmpB;
  275. blkCnt2 = (pSrc->numCols-col) >> 2;
  276. while (blkCnt2 > 0)
  277. {
  278. v1 = vld1q_f32(pa);
  279. v2 = vld1q_f32(ptemp);
  280. v1 = vfmaq_n_f32(v1,v2,f);
  281. vst1q_f32(pa,v1);
  282. pa += 4;
  283. ptemp += 4;
  284. blkCnt2--;
  285. }
  286. blkCnt2 = (pSrc->numCols-col) & 3;
  287. if (blkCnt2 > 0)
  288. {
  289. mve_pred16_t p0 = vctp32q(blkCnt2);
  290. v1 = vld1q_f32(pa);
  291. v2 = vld1q_f32(ptemp);
  292. v1 = vfmaq_n_f32(v1,v2,f);
  293. vst1q_p_f32(pa,v1,p0);
  294. pa += blkCnt2;
  295. }
  296. pa += col;
  297. }
  298. /* Copy Householder reflectors into R matrix */
  299. pa = p + pOutR->numCols;
  300. for(k=0;k<pSrc->numRows-col-1; k++)
  301. {
  302. *pa = pTmpA[k+1];
  303. pa += pOutR->numCols;
  304. }
  305. p += 1 + pOutR->numCols;
  306. }
  307. /* Generate Q if requested by user matrix */
  308. if (pOutQ != NULL)
  309. {
  310. /* Initialize Q matrix to identity */
  311. memset(pOutQ->pData,0,sizeof(float32_t)*pOutQ->numRows*pOutQ->numRows);
  312. pa = pOutQ->pData;
  313. for(col=0 ; col < pOutQ->numCols; col++)
  314. {
  315. *pa = 1.0f;
  316. pa += pOutQ->numCols+1;
  317. }
  318. nb = pOutQ->numRows - pOutQ->numCols + 1;
  319. pc = pOutTau + pOutQ->numCols - 1;
  320. for(col=0 ; col < pOutQ->numCols; col++)
  321. {
  322. int32_t j,k, blkCnt, blkCnt2;
  323. float32_t *pa0,*pa1,*pa2,*pa3,*ptemp;
  324. float32_t temp;
  325. float32x4_t v1,v2,vtemp;
  326. pos = pSrc->numRows - nb;
  327. p = pOutQ->pData + pos + pOutQ->numCols*pos ;
  328. COPY_COL_F32(pOutR,pos,pos,pTmpA);
  329. pTmpA[0] = 1.0f;
  330. pdst = pTmpB;
  331. /* v.T A(col:,col:) -> tmpb */
  332. pv = pTmpA;
  333. pa = p;
  334. temp = *pv;
  335. blkCnt2 = (pOutQ->numRows-pos) >> 2;
  336. while (blkCnt2 > 0)
  337. {
  338. v1 = vld1q_f32(pa);
  339. v1 = vmulq_n_f32(v1, temp);
  340. vst1q_f32(pdst,v1);
  341. pa += 4;
  342. pdst += 4;
  343. blkCnt2--;
  344. }
  345. blkCnt2 = (pOutQ->numRows-pos) & 3;
  346. if (blkCnt2 > 0)
  347. {
  348. mve_pred16_t p0 = vctp32q(blkCnt2);
  349. v1 = vld1q_f32(pa);
  350. v1 = vmulq_n_f32(v1, temp);
  351. vst1q_p_f32(pdst,v1,p0);
  352. pa += blkCnt2;
  353. }
  354. pa += pos;
  355. pv++;
  356. pdst = pTmpB;
  357. pa0 = pa;
  358. pa1 = pa0 + pOutQ->numRows;
  359. pa2 = pa1 + pOutQ->numRows;
  360. pa3 = pa2 + pOutQ->numRows;
  361. /* Unrolled loop */
  362. blkCnt = (pOutQ->numRows-pos - 1) >> 2;
  363. k=1;
  364. while(blkCnt > 0)
  365. {
  366. vtemp = vld1q_f32(pv);
  367. blkCnt2 = (pOutQ->numRows-pos) >> 2;
  368. while (blkCnt2 > 0)
  369. {
  370. v1 = vld1q_f32(pdst);
  371. v2 = vld1q_f32(pa0);
  372. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,0));
  373. v2 = vld1q_f32(pa1);
  374. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,1));
  375. v2 = vld1q_f32(pa2);
  376. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,2));
  377. v2 = vld1q_f32(pa3);
  378. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,3));
  379. vst1q_f32(pdst,v1);
  380. pa0 += 4;
  381. pa1 += 4;
  382. pa2 += 4;
  383. pa3 += 4;
  384. pdst += 4;
  385. blkCnt2--;
  386. }
  387. blkCnt2 = (pOutQ->numRows-pos) & 3;
  388. if (blkCnt2 > 0)
  389. {
  390. mve_pred16_t p0 = vctp32q(blkCnt2);
  391. v1 = vld1q_f32(pdst);
  392. v2 = vld1q_f32(pa0);
  393. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,0));
  394. v2 = vld1q_f32(pa1);
  395. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,1));
  396. v2 = vld1q_f32(pa2);
  397. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,2));
  398. v2 = vld1q_f32(pa3);
  399. v1 = vfmaq_n_f32(v1, v2, vgetq_lane(vtemp,3));
  400. vst1q_p_f32(pdst,v1,p0);
  401. pa0 += blkCnt2;
  402. pa1 += blkCnt2;
  403. pa2 += blkCnt2;
  404. pa3 += blkCnt2;
  405. }
  406. pa0 += pos + 3*pOutQ->numRows;
  407. pa1 += pos + 3*pOutQ->numRows;
  408. pa2 += pos + 3*pOutQ->numRows;
  409. pa3 += pos + 3*pOutQ->numRows;
  410. pv += 4;
  411. pdst = pTmpB;
  412. k += 4;
  413. blkCnt--;
  414. }
  415. pa = pa0;
  416. for(;k<pOutQ->numRows-pos; k++)
  417. {
  418. temp = *pv;
  419. blkCnt2 = (pOutQ->numRows-pos) >> 2;
  420. while (blkCnt2 > 0)
  421. {
  422. v1 = vld1q_f32(pdst);
  423. v2 = vld1q_f32(pa);
  424. v1 = vfmaq_n_f32(v1, v2, temp);
  425. vst1q_f32(pdst,v1);
  426. pdst += 4;
  427. pa += 4;
  428. blkCnt2--;
  429. }
  430. blkCnt2 = (pOutQ->numRows-pos) & 3;
  431. if (blkCnt2 > 0)
  432. {
  433. mve_pred16_t p0 = vctp32q(blkCnt2);
  434. v1 = vld1q_f32(pdst);
  435. v2 = vld1q_f32(pa);
  436. v1 = vfmaq_n_f32(v1, v2, temp);
  437. vst1q_p_f32(pdst,v1,p0);
  438. pa += blkCnt2;
  439. }
  440. pa += pos;
  441. pv++;
  442. pdst = pTmpB;
  443. }
  444. pa = p;
  445. beta = *pc--;
  446. for(j=0;j<pOutQ->numRows-pos; j++)
  447. {
  448. float32_t f = -beta * pTmpA[j];
  449. ptemp = pTmpB;
  450. blkCnt2 = (pOutQ->numCols-pos) >> 2;
  451. while (blkCnt2 > 0)
  452. {
  453. v1 = vld1q_f32(pa);
  454. v2 = vld1q_f32(ptemp);
  455. v1 = vfmaq_n_f32(v1,v2,f);
  456. vst1q_f32(pa,v1);
  457. pa += 4;
  458. ptemp += 4;
  459. blkCnt2--;
  460. }
  461. blkCnt2 = (pOutQ->numCols-pos) & 3;
  462. if (blkCnt2 > 0)
  463. {
  464. mve_pred16_t p0 = vctp32q(blkCnt2);
  465. v1 = vld1q_f32(pa);
  466. v2 = vld1q_f32(ptemp);
  467. v1 = vfmaq_n_f32(v1,v2,f);
  468. vst1q_p_f32(pa,v1,p0);
  469. pa += blkCnt2;
  470. }
  471. pa += pos;
  472. }
  473. nb++;
  474. }
  475. }
  476. arm_status status = ARM_MATH_SUCCESS;
  477. /* Return to application */
  478. return (status);
  479. }
  480. #endif /*#if !defined(ARM_MATH_MVEF)*/
  481. #endif /*#if !defined(ARM_MATH_AUTOVECTORIZE)*/
  482. #if (!defined(ARM_MATH_MVEF)) || defined(ARM_MATH_AUTOVECTORIZE)
  483. arm_status arm_mat_qr_f32(
  484. const arm_matrix_instance_f32 * pSrc,
  485. const float32_t threshold,
  486. arm_matrix_instance_f32 * pOutR,
  487. arm_matrix_instance_f32 * pOutQ,
  488. float32_t * pOutTau,
  489. float32_t *pTmpA,
  490. float32_t *pTmpB
  491. )
  492. {
  493. int32_t col=0;
  494. int32_t nb,pos;
  495. float32_t *pa,*pc;
  496. float32_t beta;
  497. float32_t *pv;
  498. float32_t *pdst;
  499. float32_t *p;
  500. if (pSrc->numRows < pSrc->numCols)
  501. {
  502. return(ARM_MATH_SIZE_MISMATCH);
  503. }
  504. memcpy(pOutR->pData,pSrc->pData,pSrc->numCols * pSrc->numRows*sizeof(float32_t));
  505. pOutR->numCols = pSrc->numCols;
  506. pOutR->numRows = pSrc->numRows;
  507. p = pOutR->pData;
  508. pc = pOutTau;
  509. for(col=0 ; col < pSrc->numCols; col++)
  510. {
  511. int32_t i,j,k,blkCnt;
  512. float32_t *pa0,*pa1,*pa2,*pa3;
  513. COPY_COL_F32(pOutR,col,col,pTmpA);
  514. beta = arm_householder_f32(pTmpA,threshold,pSrc->numRows - col,pTmpA);
  515. *pc++ = beta;
  516. pdst = pTmpB;
  517. /* v.T A(col:,col:) -> tmpb */
  518. pv = pTmpA;
  519. pa = p;
  520. for(j=0;j<pSrc->numCols-col; j++)
  521. {
  522. *pdst++ = *pv * *pa++;
  523. }
  524. pa += col;
  525. pv++;
  526. pdst = pTmpB;
  527. pa0 = pa;
  528. pa1 = pa0 + pSrc->numCols;
  529. pa2 = pa1 + pSrc->numCols;
  530. pa3 = pa2 + pSrc->numCols;
  531. /* Unrolled loop */
  532. blkCnt = (pSrc->numRows-col - 1) >> 2;
  533. k=1;
  534. while(blkCnt > 0)
  535. {
  536. float32_t sum;
  537. for(j=0;j<pSrc->numCols-col; j++)
  538. {
  539. sum = *pdst;
  540. sum += pv[0] * *pa0++;
  541. sum += pv[1] * *pa1++;
  542. sum += pv[2] * *pa2++;
  543. sum += pv[3] * *pa3++;
  544. *pdst++ = sum;
  545. }
  546. pa0 += col + 3*pSrc->numCols;
  547. pa1 += col + 3*pSrc->numCols;
  548. pa2 += col + 3*pSrc->numCols;
  549. pa3 += col + 3*pSrc->numCols;
  550. pv += 4;
  551. pdst = pTmpB;
  552. k += 4;
  553. blkCnt--;
  554. }
  555. pa = pa0;
  556. for(;k<pSrc->numRows-col; k++)
  557. {
  558. for(j=0;j<pSrc->numCols-col; j++)
  559. {
  560. *pdst++ += *pv * *pa++;
  561. }
  562. pa += col;
  563. pv++;
  564. pdst = pTmpB;
  565. }
  566. /* A(col:,col:) - beta v tmpb */
  567. pa = p;
  568. for(j=0;j<pSrc->numRows-col; j++)
  569. {
  570. float32_t f = beta * pTmpA[j];
  571. for(i=0;i<pSrc->numCols-col; i++)
  572. {
  573. *pa = *pa - f * pTmpB[i] ;
  574. pa++;
  575. }
  576. pa += col;
  577. }
  578. /* Copy Householder reflectors into R matrix */
  579. pa = p + pOutR->numCols;
  580. for(k=0;k<pSrc->numRows-col-1; k++)
  581. {
  582. *pa = pTmpA[k+1];
  583. pa += pOutR->numCols;
  584. }
  585. p += 1 + pOutR->numCols;
  586. }
  587. /* Generate Q if requested by user matrix */
  588. if (pOutQ != NULL)
  589. {
  590. /* Initialize Q matrix to identity */
  591. memset(pOutQ->pData,0,sizeof(float32_t)*pOutQ->numRows*pOutQ->numRows);
  592. pa = pOutQ->pData;
  593. for(col=0 ; col < pOutQ->numCols; col++)
  594. {
  595. *pa = 1.0f;
  596. pa += pOutQ->numCols+1;
  597. }
  598. nb = pOutQ->numRows - pOutQ->numCols + 1;
  599. pc = pOutTau + pOutQ->numCols - 1;
  600. for(col=0 ; col < pOutQ->numCols; col++)
  601. {
  602. int32_t i,j,k, blkCnt;
  603. float32_t *pa0,*pa1,*pa2,*pa3;
  604. pos = pSrc->numRows - nb;
  605. p = pOutQ->pData + pos + pOutQ->numCols*pos ;
  606. COPY_COL_F32(pOutR,pos,pos,pTmpA);
  607. pTmpA[0] = 1.0f;
  608. pdst = pTmpB;
  609. /* v.T A(col:,col:) -> tmpb */
  610. pv = pTmpA;
  611. pa = p;
  612. for(j=0;j<pOutQ->numRows-pos; j++)
  613. {
  614. *pdst++ = *pv * *pa++;
  615. }
  616. pa += pos;
  617. pv++;
  618. pdst = pTmpB;
  619. pa0 = pa;
  620. pa1 = pa0 + pOutQ->numRows;
  621. pa2 = pa1 + pOutQ->numRows;
  622. pa3 = pa2 + pOutQ->numRows;
  623. /* Unrolled loop */
  624. blkCnt = (pOutQ->numRows-pos - 1) >> 2;
  625. k=1;
  626. while(blkCnt > 0)
  627. {
  628. float32_t sum;
  629. for(j=0;j<pOutQ->numRows-pos; j++)
  630. {
  631. sum = *pdst;
  632. sum += pv[0] * *pa0++;
  633. sum += pv[1] * *pa1++;
  634. sum += pv[2] * *pa2++;
  635. sum += pv[3] * *pa3++;
  636. *pdst++ = sum;
  637. }
  638. pa0 += pos + 3*pOutQ->numRows;
  639. pa1 += pos + 3*pOutQ->numRows;
  640. pa2 += pos + 3*pOutQ->numRows;
  641. pa3 += pos + 3*pOutQ->numRows;
  642. pv += 4;
  643. pdst = pTmpB;
  644. k += 4;
  645. blkCnt--;
  646. }
  647. pa = pa0;
  648. for(;k<pOutQ->numRows-pos; k++)
  649. {
  650. for(j=0;j<pOutQ->numRows-pos; j++)
  651. {
  652. *pdst++ += *pv * *pa++;
  653. }
  654. pa += pos;
  655. pv++;
  656. pdst = pTmpB;
  657. }
  658. pa = p;
  659. beta = *pc--;
  660. for(j=0;j<pOutQ->numRows-pos; j++)
  661. {
  662. float32_t f = beta * pTmpA[j];
  663. for(i=0;i<pOutQ->numCols-pos; i++)
  664. {
  665. *pa = *pa - f * pTmpB[i] ;
  666. pa++;
  667. }
  668. pa += pos;
  669. }
  670. nb++;
  671. }
  672. }
  673. arm_status status = ARM_MATH_SUCCESS;
  674. /* Return to application */
  675. return (status);
  676. }
  677. #endif /* end of test for Helium or Neon availability */
  678. /**
  679. @} end of MatrixQR group
  680. */