ssdomn.f 11 KB

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  1. *DECK SSDOMN
  2. SUBROUTINE SSDOMN (N, B, X, NELT, IA, JA, A, ISYM, NSAVE, ITOL,
  3. + TOL, ITMAX, ITER, ERR, IERR, IUNIT, RWORK, LENW, IWORK, LENIW)
  4. C***BEGIN PROLOGUE SSDOMN
  5. C***PURPOSE Diagonally Scaled Orthomin Sparse Iterative Ax=b Solver.
  6. C Routine to solve a general linear system Ax = b using
  7. C the Orthomin method with diagonal scaling.
  8. C***LIBRARY SLATEC (SLAP)
  9. C***CATEGORY D2A4, D2B4
  10. C***TYPE SINGLE PRECISION (SSDOMN-S, DSDOMN-D)
  11. C***KEYWORDS ITERATIVE PRECONDITION, NON-SYMMETRIC LINEAR SYSTEM SOLVE,
  12. C SLAP, SPARSE
  13. C***AUTHOR Greenbaum, Anne, (Courant Institute)
  14. C Seager, Mark K., (LLNL)
  15. C Lawrence Livermore National Laboratory
  16. C PO BOX 808, L-60
  17. C Livermore, CA 94550 (510) 423-3141
  18. C seager@llnl.gov
  19. C***DESCRIPTION
  20. C
  21. C *Usage:
  22. C INTEGER N, NELT, IA(NELT), JA(NELT), ISYM, NSAVE, ITOL, ITMAX
  23. C INTEGER ITER, IERR, IUNIT, LENW, IWORK(10), LENIW
  24. C REAL B(N), X(N), A(NELT), TOL, ERR
  25. C REAL RWORK(7*N+3*N*NSAVE+NSAVE)
  26. C
  27. C CALL SSDOMN(N, B, X, NELT, IA, JA, A, ISYM, NSAVE, ITOL, TOL,
  28. C $ ITMAX, ITER, ERR, IERR, IUNIT, RWORK, LENW, IWORK, LENIW )
  29. C
  30. C *Arguments:
  31. C N :IN Integer.
  32. C Order of the Matrix.
  33. C B :IN Real B(N).
  34. C Right-hand side vector.
  35. C X :INOUT Real X(N).
  36. C On input X is your initial guess for solution vector.
  37. C On output X is the final approximate solution.
  38. C NELT :IN Integer.
  39. C Number of Non-Zeros stored in A.
  40. C IA :IN Integer IA(NELT).
  41. C JA :IN Integer JA(NELT).
  42. C A :IN Real A(NELT).
  43. C These arrays should hold the matrix A in either the SLAP
  44. C Triad format or the SLAP Column format. See "Description",
  45. C below. If the SLAP Triad format is chosen, it is changed
  46. C internally to the SLAP Column format.
  47. C ISYM :IN Integer.
  48. C Flag to indicate symmetric storage format.
  49. C If ISYM=0, all non-zero entries of the matrix are stored.
  50. C If ISYM=1, the matrix is symmetric, and only the upper
  51. C or lower triangle of the matrix is stored.
  52. C NSAVE :IN Integer.
  53. C Number of direction vectors to save and orthogonalize against.
  54. C ITOL :IN Integer.
  55. C Flag to indicate type of convergence criterion.
  56. C If ITOL=1, iteration stops when the 2-norm of the residual
  57. C divided by the 2-norm of the right-hand side is less than TOL.
  58. C If ITOL=2, iteration stops when the 2-norm of M-inv times the
  59. C residual divided by the 2-norm of M-inv times the right hand
  60. C side is less than TOL, where M-inv is the inverse of the
  61. C diagonal of A.
  62. C ITOL=11 is often useful for checking and comparing different
  63. C routines. For this case, the user must supply the "exact"
  64. C solution or a very accurate approximation (one with an error
  65. C much less than TOL) through a common block,
  66. C COMMON /SSLBLK/ SOLN( )
  67. C If ITOL=11, iteration stops when the 2-norm of the difference
  68. C between the iterative approximation and the user-supplied
  69. C solution divided by the 2-norm of the user-supplied solution
  70. C is less than TOL.
  71. C TOL :INOUT Real.
  72. C Convergence criterion, as described above. (Reset if IERR=4.)
  73. C ITMAX :IN Integer.
  74. C Maximum number of iterations.
  75. C ITER :OUT Integer.
  76. C Number of iterations required to reach convergence, or
  77. C ITMAX+1 if convergence criterion could not be achieved in
  78. C ITMAX iterations.
  79. C ERR :OUT Real.
  80. C Error estimate of error in final approximate solution, as
  81. C defined by ITOL.
  82. C IERR :OUT Integer.
  83. C Return error flag.
  84. C IERR = 0 => All went well.
  85. C IERR = 1 => Insufficient space allocated for WORK or IWORK.
  86. C IERR = 2 => Method failed to converge in ITMAX steps.
  87. C IERR = 3 => Error in user input.
  88. C Check input values of N, ITOL.
  89. C IERR = 4 => User error tolerance set too tight.
  90. C Reset to 500*R1MACH(3). Iteration proceeded.
  91. C IERR = 5 => Preconditioning matrix, M, is not positive
  92. C definite. (r,z) < 0.
  93. C IERR = 6 => Breakdown of method detected.
  94. C (p,Ap) < epsilon**2.
  95. C IUNIT :IN Integer.
  96. C Unit number on which to write the error at each iteration,
  97. C if this is desired for monitoring convergence. If unit
  98. C number is 0, no writing will occur.
  99. C RWORK :WORK Real RWORK(LENW).
  100. C Real array used for workspace.
  101. C LENW :IN Integer.
  102. C Length of the real workspace, RWORK.
  103. C LENW >= 7*N+NSAVE*(3*N+1).
  104. C IWORK :WORK Integer IWORK(LENIW).
  105. C Used to hold pointers into the RWORK array.
  106. C LENIW :IN Integer.
  107. C Length of the integer workspace, IWORK. LENIW >= 10.
  108. C
  109. C *Description:
  110. C This routine is simply a driver for the SOMN routine. It
  111. C calls the SSDS routine to set up the preconditioning and
  112. C then calls SOMN with the appropriate MATVEC and MSOLVE
  113. C routines.
  114. C
  115. C The Sparse Linear Algebra Package (SLAP) utilizes two matrix
  116. C data structures: 1) the SLAP Triad format or 2) the SLAP
  117. C Column format. The user can hand this routine either of the
  118. C of these data structures and SLAP will figure out which on
  119. C is being used and act accordingly.
  120. C
  121. C =================== S L A P Triad format ===================
  122. C
  123. C In this format only the non-zeros are stored. They may
  124. C appear in *ANY* order. The user supplies three arrays of
  125. C length NELT, where NELT is the number of non-zeros in the
  126. C matrix: (IA(NELT), JA(NELT), A(NELT)). For each non-zero
  127. C the user puts the row and column index of that matrix
  128. C element in the IA and JA arrays. The value of the non-zero
  129. C matrix element is placed in the corresponding location of
  130. C the A array. This is an extremely easy data structure to
  131. C generate. On the other hand it is not too efficient on
  132. C vector computers for the iterative solution of linear
  133. C systems. Hence, SLAP changes this input data structure to
  134. C the SLAP Column format for the iteration (but does not
  135. C change it back).
  136. C
  137. C Here is an example of the SLAP Triad storage format for a
  138. C 5x5 Matrix. Recall that the entries may appear in any order.
  139. C
  140. C 5x5 Matrix SLAP Triad format for 5x5 matrix on left.
  141. C 1 2 3 4 5 6 7 8 9 10 11
  142. C |11 12 0 0 15| A: 51 12 11 33 15 53 55 22 35 44 21
  143. C |21 22 0 0 0| IA: 5 1 1 3 1 5 5 2 3 4 2
  144. C | 0 0 33 0 35| JA: 1 2 1 3 5 3 5 2 5 4 1
  145. C | 0 0 0 44 0|
  146. C |51 0 53 0 55|
  147. C
  148. C =================== S L A P Column format ==================
  149. C
  150. C In this format the non-zeros are stored counting down
  151. C columns (except for the diagonal entry, which must appear
  152. C first in each "column") and are stored in the real array A.
  153. C In other words, for each column in the matrix put the
  154. C diagonal entry in A. Then put in the other non-zero
  155. C elements going down the column (except the diagonal) in
  156. C order. The IA array holds the row index for each non-zero.
  157. C The JA array holds the offsets into the IA, A arrays for the
  158. C beginning of each column. That is, IA(JA(ICOL)),
  159. C A(JA(ICOL)) points to the beginning of the ICOL-th column in
  160. C IA and A. IA(JA(ICOL+1)-1), A(JA(ICOL+1)-1) points to the
  161. C end of the ICOL-th column. Note that we always have JA(N+1)
  162. C = NELT+1, where N is the number of columns in the matrix and
  163. C NELT is the number of non-zeros in the matrix.
  164. C
  165. C Here is an example of the SLAP Column storage format for a
  166. C 5x5 Matrix (in the A and IA arrays '|' denotes the end of a
  167. C column):
  168. C
  169. C 5x5 Matrix SLAP Column format for 5x5 matrix on left.
  170. C 1 2 3 4 5 6 7 8 9 10 11
  171. C |11 12 0 0 15| A: 11 21 51 | 22 12 | 33 53 | 44 | 55 15 35
  172. C |21 22 0 0 0| IA: 1 2 5 | 2 1 | 3 5 | 4 | 5 1 3
  173. C | 0 0 33 0 35| JA: 1 4 6 8 9 12
  174. C | 0 0 0 44 0|
  175. C |51 0 53 0 55|
  176. C
  177. C *Side Effects:
  178. C The SLAP Triad format (IA, JA, A) is modified internally to
  179. C be the SLAP Column format. See above.
  180. C
  181. C *Cautions:
  182. C This routine will attempt to write to the Fortran logical output
  183. C unit IUNIT, if IUNIT .ne. 0. Thus, the user must make sure that
  184. C this logical unit is attached to a file or terminal before calling
  185. C this routine with a non-zero value for IUNIT. This routine does
  186. C not check for the validity of a non-zero IUNIT unit number.
  187. C
  188. C***SEE ALSO SOMN, SSLUOM
  189. C***REFERENCES (NONE)
  190. C***ROUTINES CALLED SCHKW, SOMN, SS2Y, SSDI, SSDS, SSMV
  191. C***REVISION HISTORY (YYMMDD)
  192. C 871119 DATE WRITTEN
  193. C 881213 Previous REVISION DATE
  194. C 890915 Made changes requested at July 1989 CML Meeting. (MKS)
  195. C 890921 Removed TeX from comments. (FNF)
  196. C 890922 Numerous changes to prologue to make closer to SLATEC
  197. C standard. (FNF)
  198. C 890929 Numerous changes to reduce SP/DP differences. (FNF)
  199. C 910411 Prologue converted to Version 4.0 format. (BAB)
  200. C 920407 COMMON BLOCK renamed SSLBLK. (WRB)
  201. C 920511 Added complete declaration section. (WRB)
  202. C 921113 Corrected C***CATEGORY line. (FNF)
  203. C***END PROLOGUE SSDOMN
  204. C .. Parameters ..
  205. INTEGER LOCRB, LOCIB
  206. PARAMETER (LOCRB=1, LOCIB=11)
  207. C .. Scalar Arguments ..
  208. REAL ERR, TOL
  209. INTEGER IERR, ISYM, ITER, ITMAX, ITOL, IUNIT, LENIW, LENW, N,
  210. + NELT, NSAVE
  211. C .. Array Arguments ..
  212. REAL A(N), B(N), RWORK(LENW), X(N)
  213. INTEGER IA(NELT), IWORK(LENIW), JA(NELT)
  214. C .. Local Scalars ..
  215. INTEGER LOCAP, LOCCSA, LOCDIN, LOCDZ, LOCEMA, LOCIW, LOCP, LOCR,
  216. + LOCW, LOCZ
  217. C .. External Subroutines ..
  218. EXTERNAL SCHKW, SOMN, SS2Y, SSDI, SSDS, SSMV
  219. C***FIRST EXECUTABLE STATEMENT SSDOMN
  220. C
  221. IERR = 0
  222. IF( N.LT.1 .OR. NELT.LT.1 ) THEN
  223. IERR = 3
  224. RETURN
  225. ENDIF
  226. C
  227. C Change the SLAP input matrix IA, JA, A to SLAP-Column format.
  228. CALL SS2Y( N, NELT, IA, JA, A, ISYM )
  229. C
  230. C Set up the workspace.
  231. LOCIW = LOCIB
  232. C
  233. LOCDIN = LOCRB
  234. LOCR = LOCDIN + N
  235. LOCZ = LOCR + N
  236. LOCP = LOCZ + N
  237. LOCAP = LOCP + N*(NSAVE+1)
  238. LOCEMA = LOCAP + N*(NSAVE+1)
  239. LOCDZ = LOCEMA + N*(NSAVE+1)
  240. LOCCSA = LOCDZ + N
  241. LOCW = LOCCSA + NSAVE
  242. C
  243. C Check the workspace allocations.
  244. CALL SCHKW( 'SSDOMN', LOCIW, LENIW, LOCW, LENW, IERR, ITER, ERR )
  245. IF( IERR.NE.0 ) RETURN
  246. C
  247. IWORK(4) = LOCDIN
  248. IWORK(9) = LOCIW
  249. IWORK(10) = LOCW
  250. C
  251. C Compute the inverse of the diagonal of the matrix.
  252. CALL SSDS(N, NELT, IA, JA, A, ISYM, RWORK(LOCDIN))
  253. C
  254. C Perform the Diagonally Scaled Orthomin iteration algorithm.
  255. CALL SOMN(N, B, X, NELT, IA, JA, A, ISYM, SSMV,
  256. $ SSDI, NSAVE, ITOL, TOL, ITMAX, ITER, ERR, IERR, IUNIT,
  257. $ RWORK(LOCR), RWORK(LOCZ), RWORK(LOCP), RWORK(LOCAP),
  258. $ RWORK(LOCEMA), RWORK(LOCDZ), RWORK(LOCCSA),
  259. $ RWORK, IWORK )
  260. RETURN
  261. C------------- LAST LINE OF SSDOMN FOLLOWS ----------------------------
  262. END