Using pinned host memory for Random Forest and DBSCAN

[divyegala]

Benchmarks show that RF performs consistently better with pinned host memory, while DBSCAN sometimes better and sometimes not (within the margin of error), so using pinned host memory by default for both these algorithms.

Ignoring KMeans and LARS for now as both show slightly better perf with pinned host memory but only with increasing number of columns. Since this would need more analysis and deciding if a heuristic is needed for selecting memory, deferring it to 21.12.

Here are the raw numbers:

1. LARS
   Normal memory:
   {'lars': {(100000, 10): 0.12429666519165039, (100000, 100): 0.015396833419799805, (100000, 250): 0.015408039093017578, (250000, 10): 0.00986933708190918, (250000, 100): 0.023822546005249023, (250000, 250): 0.03715157508850098, (500000, 10): 0.013423442840576172, (500000, 100): 0.044762372970581055, (500000, 250): 0.07782578468322754}
   Pinned memory:
   {'lars': {(100000, 10): 0.12958097457885742, (100000, 100): 0.01501011848449707, (100000, 250): 0.016597509384155273, (250000, 10): 0.01801013946533203, (250000, 100): 0.022644996643066406, (250000, 250): 0.037090301513671875, (500000, 10): 0.020437955856323242, (500000, 100): 0.044635772705078125, (500000, 250): 0.07696056365966797}
2. RFR
   Normal memory:
   'rfr': {(100000, 10): 1.1951744556427002, (100000, 100): 5.099738359451294, (100000, 250): 11.32804536819458, (250000, 10): 2.0097765922546387, (250000, 100): 9.109776496887207, (250000, 250): 21.058837890625, (500000, 10): 3.3387184143066406, (500000, 100): 15.802990436553955, (500000, 250): 36.80855870246887}
   Pinned memory:
   'rfr': {(100000, 10): 1.1727137565612793, (100000, 100): 4.804195880889893, (100000, 250): 11.621357917785645, (250000, 10): 1.8899295330047607, (250000, 100): 9.16961407661438, (250000, 250): 21.12194561958313, (500000, 10): 3.2937560081481934, (500000, 100): 15.66197681427002, (500000, 250): 36.6080117225647}
3. KMeans
   Normal memory:
   {(100000, 10): 0.11008882522583008, (100000, 100): 0.15475797653198242, (100000, 250): 0.15683507919311523, (250000, 10): 0.18775177001953125, (250000, 100): 0.25696277618408203, (250000, 250): 0.40389132499694824, (500000, 10): 0.4578282833099365, (500000, 100): 0.3917391300201416, (500000, 250): 0.6426849365234375}
   Pinned memory:
   'kmeans': {(100000, 10): 0.11982870101928711, (100000, 100): 0.16992664337158203, (100000, 250): 0.1021108627319336, (250000, 10): 0.16021251678466797, (250000, 100): 0.31025242805480957, (250000, 250): 0.298201322555542, (500000, 10): 0.21084189414978027, (500000, 100): 0.50473952293396, (500000, 250): 0.6191830635070801}
4. DBSCAN
   Normal memory:
   'dbscan': {(100000, 10): 0.4957292079925537, (100000, 100): 0.8680248260498047, (100000, 250): 1.585218906402588, (250000, 10): 4.52524995803833, (250000, 100): 7.175846099853516, (250000, 250): 12.135416269302368, (500000, 10): 26.427770853042603, (500000, 100): 37.57275915145874, (500000, 250): 57.98261737823486}}
   Pinned memory:
   'dbscan': {(100000, 10): 0.49578166007995605, (100000, 100): 0.8678708076477051, (100000, 250): 1.5854766368865967, (250000, 10): 4.526952505111694, (250000, 100): 7.172863006591797, (250000, 250): 12.145166397094727, (500000, 10): 26.422622680664062, (500000, 100): 37.56665277481079, (500000, 250): 58.02563738822937}}

[RAMitchell]

LGTM!

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[dantegd]

@gpucibot merge