[WIP] AmgX adjustments for benchmarking

[artv3]

This PR makes adjustments to python scripts to set apart amg setup time, no of iterations, and time-per-iteration.
Still a work in progress, but logging what I see.

    mfem   |    |  comp  |     |number of |  amg       | number of  |               | cg-iter dps
   device  |  p |  iler  |  np |unknowns  |  setup     | iterations | time-per-iter |   millions
-----------+----+--------+-----+---------+-------------+---------+---------------+-------------
      cuda |  1 |    xlc |   4 |     18  |    0.000468 |       1 |    0.000000 |   0.033255
      cuda |  1 |    xlc |   4 |     27  |    0.000438 |       2 |    0.001043 |   0.038509
      cuda |  1 |    xlc |   4 |     45  |    0.000471 |       3 |    0.000981 |   0.057660
      cuda |  1 |    xlc |   4 |     75  |    0.000491 |       7 |    0.000940 |   0.087167
      cuda |  1 |    xlc |   4 |    125  |    0.000497 |       8 |    0.000969 |   0.139263
      cuda |  1 |    xlc |   4 |    225  |    0.000605 |      11 |    0.000931 |   0.255691
      cuda |  1 |    xlc |   4 |    405  |    0.000924 |      11 |    0.000950 |   0.450530
      cuda |  1 |    xlc |   4 |    729  |    0.004724 |      11 |    0.001284 |   0.607944
      cuda |  1 |    xlc |   4 |   1377  |    0.005715 |      15 |    0.000986 |   1.453810
      cuda |  1 |    xlc |   4 |   2601  |    0.009194 |      16 |    0.001372 |   1.984690
      cuda |  1 |    xlc |   4 |   4913  |    0.015172 |      16 |    0.001390 |   3.707380
      cuda |  1 |    xlc |   4 |   9537  |    0.036640 |      22 |    0.001878 |   5.273700
      cuda |  1 |    xlc |   4 |  18513  |    0.039395 |      14 |    0.001856 |  10.590700
      cuda |  1 |    xlc |   4 |  35937  |    0.052646 |      14 |    0.002336 |  16.330200
      cuda |  1 |    xlc |   4 |  70785  |    0.097023 |      27 |    0.003166 |  23.070800
      cuda |  1 |    xlc |   4 | 139425  |    0.099476 |      14 |    0.002876 |  51.618500
      cuda |  1 |    xlc |   4 | 274625  |    0.140822 |      12 |    0.003380 |  87.708900
      cuda |  1 |    xlc |   4 | 545025  |    0.381351 |      31 |    0.004954 | 113.373000
      cuda |  1 |    xlc |   4 | 1081665  |    0.357588 |      14 |    0.005256 | 220.212000
      cuda |  1 |    xlc |   4 | 2146689  |    0.749115 |      11 |    0.008046 | 291.702000
      cuda |  1 |    xlc |   4 | 4276737  |    2.608220 |      37 |    0.019247 | 228.178000
      cuda |  1 |    xlc |   4 | 8520321  |    2.131120 |      15 |    0.021306 | 427.370000

[artv3]

When using AmgX as a preconditioner, I can distinguish the cost of applying AMGX as the preconditioner, along with the PCG iteration cost (which I believe includes applying preconditioner):

    mfem   |    |  comp  |     |number of |  amg   | cost of  | number of  | time per | cg-iter dps
   device  |  p |  iler  |  np |unknowns  |  setup |  precon  | iterations | cg step |   millions
-----------+----+--------+-----+---------+---------+----+---------+---------------+-------------
      cuda |  1 |    xlc |   4 |     18  |    0.000374 |  0.00024474 |       0 |         inf |   0.000000
      cuda |  1 |    xlc |   4 |     27  |    0.000381 |  0.00023962 |       1 |    0.001414 |   0.019094
      cuda |  1 |    xlc |   4 |     45  |    0.000403 |  0.00023654 |       3 |    0.000944 |   0.047687
      cuda |  1 |    xlc |   4 |     75  |    0.000413 |  0.00022106 |       6 |    0.000833 |   0.090035
      cuda |  1 |    xlc |   4 |    125  |    0.000410 |  0.00023347 |      11 |    0.001171 |   0.106763
      cuda |  1 |    xlc |   4 |    225  |    0.000509 |  0.00022026 |      16 |    0.000970 |   0.231880
      cuda |  1 |    xlc |   4 |    405  |    0.000726 |  0.00024685 |      15 |    0.000794 |   0.510359
      cuda |  1 |    xlc |   4 |    729  |    0.004634 |  0.00020685 |      15 |    0.000996 |   0.731794
      cuda |  1 |    xlc |   4 |   1377  |    0.005256 |  0.00025005 |      23 |    0.000915 |   1.504310
      cuda |  1 |    xlc |   4 |   2601  |    0.009244 |  0.00034202 |      23 |    0.000944 |   2.754890
      cuda |  1 |    xlc |   4 |   4913  |    0.014462 |  0.00047923 |      24 |    0.001153 |   4.260620
      cuda |  1 |    xlc |   4 |   9537  |    0.036590 |  0.00072102 |      32 |    0.001345 |   7.090490
      cuda |  1 |    xlc |   4 |  18513  |    0.038512 |  0.00070694 |      21 |    0.001435 |  12.903100
      cuda |  1 |    xlc |   4 |  35937  |    0.051612 |  0.00097382 |      21 |    0.002042 |  17.598400
      cuda |  1 |    xlc |   4 |  70785  |    0.097607 |  0.00129322 |      36 |    0.002544 |  27.826700
      cuda |  1 |    xlc |   4 | 139425  |    0.097561 |  0.00129434 |      20 |    0.003259 |  42.778100
      cuda |  1 |    xlc |   4 | 274625  |    0.132797 |  0.00143853 |      17 |    0.004896 |  56.086000
      cuda |  1 |    xlc |   4 | 545025  |    0.385704 |  0.00242182 |      39 |    0.008543 |  63.795000
      cuda |  1 |    xlc |   4 | 1081665  |    0.351429 |  0.00253306 |      19 |    0.014508 |  74.556000
      cuda |  1 |    xlc |   4 | 2146689  |    0.732958 |  0.00396192 |      15 |    0.028630 |  74.979900
      cuda |  1 |    xlc |   4 | 4276737  |    2.626320 |  0.00967741 |      50 |    0.057062 |  74.948400
      cuda |  1 |    xlc |   4 | 8520321  |    2.138930 |  0.01042890 |      20 |    0.109639 |  77.712200