Added finding quantiles on GPU. (#3393)

* Added finding quantiles on GPU.

- this includes datasets where weights are assigned to data rows
- as the quantiles found by the new algorithm are not the same
  as those found by the old one, test thresholds in
    tests/python-gpu/test_gpu_updaters.py have been adjusted.

* Adjustments and improved testing for finding quantiles on the GPU.

- added C++ tests for the DeviceSketch() function
- reduced one of the thresholds in test_gpu_updaters.py
- adjusted the cuts found by the find_cuts_k kernel

tests/cpp/common/test_gpu_hist_util.cu

@@ -0,0 +1,60 @@
+#include "../../../src/common/device_helpers.cuh"
+#include "../../../src/common/hist_util.h"
+#include "gtest/gtest.h"
+#include "xgboost/c_api.h"
+#include <algorithm>
+#include <cmath>
+#include <thrust/device_vector.h>
+#include <thrust/iterator/counting_iterator.h>
+
+namespace xgboost {
+namespace common {
+
+TEST(gpu_hist_util, TestDeviceSketch) {
+  // create the data
+  int nrows = 10001;
+  std::vector<float> test_data(nrows);
+  auto count_iter = thrust::make_counting_iterator(0);
+  // fill in reverse order
+  std::copy(count_iter, count_iter + nrows, test_data.rbegin());
+
+  // create the DMatrix
+  DMatrixHandle dmat_handle;
+  XGDMatrixCreateFromMat(test_data.data(), nrows, 1, -1,
+                         &dmat_handle);
+  auto dmat = *static_cast<std::shared_ptr<xgboost::DMatrix> *>(dmat_handle);
+
+  // parameters for finding quantiles
+  tree::TrainParam p;
+  p.max_bin = 20;
+  p.gpu_id = 0;
+  p.n_gpus = 1;
+  // ensure that the exact quantiles are found
+  p.gpu_batch_nrows = nrows * 10;
+
+  // find quantiles on the CPU
+  HistCutMatrix hmat_cpu;
+  hmat_cpu.Init(dmat.get(), p.max_bin);
+
+  // find the cuts on the GPU
+  dmlc::DataIter<SparsePage>* iter = dmat->RowIterator();
+  iter->BeforeFirst();
+  CHECK(iter->Next());
+  const SparsePage& batch = iter->Value();
+  HistCutMatrix hmat_gpu;
+  DeviceSketch(batch, dmat->Info(), p, &hmat_gpu);
+  CHECK(!iter->Next());
+
+  // compare the cuts
+  double eps = 1e-2;
+  ASSERT_EQ(hmat_gpu.min_val.size(), 1);
+  ASSERT_EQ(hmat_gpu.row_ptr.size(), 2);
+  ASSERT_EQ(hmat_gpu.cut.size(), hmat_cpu.cut.size());
+  ASSERT_LT(fabs(hmat_cpu.min_val[0] - hmat_gpu.min_val[0]), eps * nrows);
+  for (int i = 0; i < hmat_gpu.cut.size(); ++i) {
+    ASSERT_LT(fabs(hmat_cpu.cut[i] - hmat_gpu.cut[i]), eps * nrows);
+  }
+}
+
+}  // namespace common
+}  // namespace xgboost