- training with external memory part 1 of 2 (#4486)

* - training with external memory part 1 of 2
   - this pr focuses on computing the quantiles using multiple gpus on a
     dataset that uses the external cache capabilities
   - there will a follow-up pr soon after this that will support creation
     of histogram indices on large dataset as well
   - both of these changes are required to support training with external memory
   - the sparse pages in dmatrix are taken in batches and the the cut matrices
     are incrementally built
   - also snuck in some (perf) changes related to sketches aggregation amongst multiple
     features across multiple sparse page batches. instead of aggregating the summary
     inside each device and merged later, it is aggregated in-place when the device
     is working on different rows but the same feature

src/common/hist_util.h

@@ -8,6 +8,7 @@
 #define XGBOOST_COMMON_HIST_UTIL_H_
 
 #include <xgboost/data.h>
+#include <xgboost/generic_parameters.h>
 #include <limits>
 #include <vector>
 #include "row_set.h"
@@ -84,9 +85,6 @@ struct SimpleArray {
   size_t n_ = 0;
 };
 
-
-
-
 /*! \brief Cut configuration for all the features. */
 struct HistCutMatrix {
   /*! \brief Unit pointer to rows by element position */
@@ -115,11 +113,13 @@ struct HistCutMatrix {
   Monitor monitor_;
 };
 
-/*! \brief Builds the cut matrix on the GPU */
-void DeviceSketch
-  (const SparsePage& batch, const MetaInfo& info,
-   const tree::TrainParam& param, HistCutMatrix* hmat, int gpu_batch_nrows,
-   GPUSet const& devices);
+/*! \brief Builds the cut matrix on the GPU.
+ *  
+ *  \return The row stride across the entire dataset.
+ */
+size_t DeviceSketch
+  (const tree::TrainParam& param, const LearnerTrainParam &learner_param, int gpu_batch_nrows,
+   DMatrix* dmat, HistCutMatrix* hmat);
 
 /*!
  * \brief A single row in global histogram index.