[GPU-Plugin] Add GPU accelerated prediction (#2593)

* [GPU-Plugin] Add GPU accelerated prediction

* Improve allocation message

* Update documentation

* Resolve linker error for predictor

* Add unit tests

doc/parameter.md

@@ -56,7 +56,7 @@ Parameters for Tree Booster
 * tree_method, string [default='auto']
   - The tree construction algorithm used in XGBoost(see description in the [reference paper](http://arxiv.org/abs/1603.02754))
   - Distributed and external memory version only support approximate algorithm.
-  - Choices: {'auto', 'exact', 'approx', 'hist'}
+  - Choices: {'auto', 'exact', 'approx', 'hist', 'gpu_exact', 'gpu_hist'}
     - 'auto': Use heuristic to choose faster one.
       - For small to medium dataset, exact greedy will be used.
       - For very large-dataset, approximate algorithm will be chosen.
@@ -65,6 +65,8 @@ Parameters for Tree Booster
     - 'exact': Exact greedy algorithm.
     - 'approx': Approximate greedy algorithm using sketching and histogram.
     - 'hist': Fast histogram optimized approximate greedy algorithm. It uses some performance improvements such as bins caching.
+	- 'gpu_exact': GPU implementation of exact algorithm. 
+	- 'gpu_hist': GPU implementation of hist algorithm. 
 * sketch_eps, [default=0.03]
   - This is only used for approximate greedy algorithm.
   - This roughly translated into ```O(1 / sketch_eps)``` number of bins.
@@ -107,7 +109,10 @@ Parameters for Tree Booster
   - This is only used if 'hist' is specified as `tree_method`.
   - Maximum number of discrete bins to bucket continuous features.
   - Increasing this number improves the optimality of splits at the cost of higher computation time.
-
+* predictor, [default='cpu_predictor']
+  - The type of predictor algorithm to use. Provides the same results but allows the use of GPU or CPU.
+    - 'cpu_predictor': Multicore CPU prediction algorithm.
+    - 'gpu_predictor': Prediction using GPU. Default for 'gpu_exact' and 'gpu_hist' tree method.
 Additional parameters for Dart Booster
 --------------------------------------
 * sample_type [default="uniform"]