openpower/sv/remapmatrixprint.py

   1 # a "yield" version of the REMAP algorithm. a little easier to read
   2 # than the Finite State Machine version
   3
   4 from remapyield import iterate_indices
   5
   6
   7 def matrixscheduledemo():
   8     ydim2, xdim2, ydim1 = (3, 4, 3)
   9
  10     print ("ydim2 xdim2 ydim1", ydim2, xdim2, ydim1)
  11
  12     # got this from running an earlier version
  13     expected = [
  14         ( 0 , (0, 0, 0) ),
  15         ( 1 , (1, 0, 1) ),
  16         ( 2 , (2, 0, 2) ),
  17         ( 3 , (3, 0, 3) ),
  18         ( 4 , (4, 3, 0) ),
  19         ( 5 , (5, 3, 1) ),
  20         ( 6 , (6, 3, 2) ),
  21         ( 7 , (7, 3, 3) ),
  22         ( 8 , (8, 6, 0) ),
  23         ( 9 , (9, 6, 1) ),
  24         ( 10 , (10, 6, 2) ),
  25         ( 11 , (11, 6, 3) ),
  26         ( 12 , (0, 1, 4) ),
  27         ( 13 , (1, 1, 5) ),
  28         ( 14 , (2, 1, 6) ),
  29         ( 15 , (3, 1, 7) ),
  30         ( 16 , (4, 4, 4) ),
  31         ( 17 , (5, 4, 5) ),
  32         ( 18 , (6, 4, 6) ),
  33         ( 19 , (7, 4, 7) ),
  34         ( 20 , (8, 7, 4) ),
  35         ( 21 , (9, 7, 5) ),
  36         ( 22 , (10, 7, 6) ),
  37         ( 23 , (11, 7, 7) ),
  38         ( 24 , (0, 2, 8) ),
  39         ( 25 , (1, 2, 9) ),
  40         ( 26 , (2, 2, 10) ),
  41         ( 27 , (3, 2, 11) ),
  42         ( 28 , (4, 5, 8) ),
  43         ( 29 , (5, 5, 9) ),
  44         ( 30 , (6, 5, 10) ),
  45         ( 31 , (7, 5, 11) ),
  46         ( 32 , (8, 8, 8) ),
  47         ( 33 , (9, 8, 9) ),
  48         ( 34 , (10, 8, 10) ),
  49         ( 35 , (11, 8, 11) ),
  50     ]
  51
  52     class SVSHAPE:
  53         pass
  54     # result uses SVSHAPE0
  55     SVSHAPE0 = SVSHAPE()
  56     SVSHAPE0.lims = [xdim2, ydim2, 1]
  57     SVSHAPE0.order = [0,1,2]  # result iterates through i and j (modulo)
  58     SVSHAPE0.mode = 0b00
  59     SVSHAPE0.skip = 0b00
  60     SVSHAPE0.offset = 0       # no offset
  61     SVSHAPE0.invxyz = [0,0,0] # no inversion
  62     # X uses SVSHAPE1
  63     SVSHAPE1 = SVSHAPE()
  64     SVSHAPE1.lims = [xdim2, ydim2, ydim1]
  65     SVSHAPE1.order = [0,2,1]  # X iterates through i and k
  66     SVSHAPE1.mode = 0b00
  67     SVSHAPE1.skip = 0b01
  68     SVSHAPE1.offset = 0       # no offset
  69     SVSHAPE1.invxyz = [0,0,0] # no inversion
  70     # y-selector uses SHAPE2
  71     SVSHAPE2 = SVSHAPE()
  72     SVSHAPE2.lims = [xdim2, ydim2, ydim1]
  73     SVSHAPE2.order = [0,2,1]  # X iterates through i and k
  74     SVSHAPE2.mode = 0b00
  75     SVSHAPE2.skip = 0b11
  76     SVSHAPE2.offset = 0       # no offset
  77     SVSHAPE2.invxyz = [0,0,0] # no inversion
  78
  79     # perform the iteration over the *linear* arrays using the
  80     # schedules
  81     VL = ydim2 * xdim2 * ydim1
  82     i = 0
  83     for i, idxs in enumerate(zip(iterate_indices(SVSHAPE0),
  84                                  iterate_indices(SVSHAPE1),
  85                                  iterate_indices(SVSHAPE2))):
  86
  87         if i == VL:
  88             break
  89         print ("(", i, ",", idxs, "),", "expected", expected[i])
  90         if expected[i] != (i, idxs):
  91             print ("row incorrect")
  92
  93
  94 # run the demo
  95 if __name__ == '__main__':
  96     matrixscheduledemo()