diff --git a/src/sparse/KokkosSparse_CrsMatrix.hpp b/src/sparse/KokkosSparse_CrsMatrix.hpp
index d734d9ac3a..3ce574602c 100644
--- a/src/sparse/KokkosSparse_CrsMatrix.hpp
+++ b/src/sparse/KokkosSparse_CrsMatrix.hpp
@@ -554,7 +554,37 @@ class CrsMatrix {
              OrdinalType* rowmap,
              OrdinalType* cols)
   {
-    ctor_impl (label, nrows, ncols, annz, val, rowmap, cols);
+    using Kokkos::Unmanaged;
+    using HostRowmap = Kokkos::View<SizeType*, Kokkos::HostSpace>;
+    using UnmanagedRowmap = Kokkos::View<const SizeType*, Kokkos::HostSpace, Kokkos::MemoryTraits<Unmanaged>>;
+    using UnmanagedEntries = Kokkos::View<const OrdinalType*, Kokkos::HostSpace, Kokkos::MemoryTraits<Unmanaged>>;
+    using UnmanagedValues = Kokkos::View<const ScalarType*, Kokkos::HostSpace, Kokkos::MemoryTraits<Unmanaged>>;
+    //Allocate device rowmap, entries, values views
+    typename row_map_type::non_const_type rowmapDevice(Kokkos::ViewAllocateWithoutInitializing("rowmap"), nrows + 1);
+    index_type entriesDevice(Kokkos::ViewAllocateWithoutInitializing("entries"), annz);
+    //given rowmap in ordinal_type, so may need to convert to size_type explicitly
+    HostRowmap rowmapConverted;
+    UnmanagedRowmap rowmapRaw;
+    if(!std::is_same<OrdinalType, SizeType>::value)
+    {
+      rowmapConverted = HostRowmap(Kokkos::ViewAllocateWithoutInitializing("rowmap raw"), nrows + 1);
+      for(OrdinalType i = 0; i <= nrows; i++)
+        rowmapConverted(i) = rowmap[i];
+      rowmapRaw = rowmapConverted;
+    }
+    else
+    {
+      rowmapRaw = UnmanagedRowmap((const SizeType*) rowmap, nrows + 1);
+    }
+    Kokkos::deep_copy(rowmapDevice, rowmapRaw);
+    UnmanagedEntries entriesRaw(cols, annz);
+    Kokkos::deep_copy(entriesDevice, entriesRaw);
+    //Construct graph and populate all members
+    this->numCols_ = ncols;
+    this->graph = StaticCrsGraphType(entriesDevice, rowmapDevice);
+    this->values = values_type(Kokkos::ViewAllocateWithoutInitializing("values"), annz);
+    UnmanagedValues valuesRaw(val, annz);
+    Kokkos::deep_copy(this->values, valuesRaw);
 
     // FIXME (mfh 09 Aug 2013) Specialize this on the Device type.
     // Only use cuSPARSE for the Cuda Device.
@@ -646,15 +676,6 @@ class CrsMatrix {
 #endif // KOKKOS_USE_CUSPARSE
   }
 
-  void
-  ctor_impl (const std::string &label,
-          const OrdinalType nrows,
-          const OrdinalType ncols,
-          const size_type annz,
-          ScalarType* val,
-          OrdinalType* rows,
-          OrdinalType* cols);
-
   KOKKOS_INLINE_FUNCTION
   OrdinalType
   sumIntoValues (const OrdinalType rowi,
@@ -883,50 +904,5 @@ class CrsMatrix {
   ordinal_type numCols_;
 };
 
-//----------------------------------------------------------------------------
-//----------------------------------------------------------------------------
-
-template< typename ScalarType , typename OrdinalType, class Device, class MemoryTraits, typename SizeType >
-void
-CrsMatrix<ScalarType , OrdinalType, Device, MemoryTraits, SizeType >::
-ctor_impl (const std::string &label,
-           const OrdinalType nrows,
-           const OrdinalType ncols,
-           const size_type annz,
-           ScalarType* val,
-           OrdinalType* rows,
-           OrdinalType* cols)
-{
-  std::string str = label;
-  values = values_type (str.append (".values"), annz);
-
-  numCols_ = ncols;
-
-  // FIXME (09 Aug 2013) CrsArray only takes std::vector for now.
-  // We'll need to fix that.
-  std::vector<int> row_lengths (nrows, 0);
-
-  // FIXME (mfh 21 Jun 2013) This calls for a parallel_for kernel.
-  for (OrdinalType i = 0; i < nrows; ++i) {
-    row_lengths[i] = rows[i + 1] - rows[i];
-  }
-
-  graph = Kokkos::create_staticcrsgraph<staticcrsgraph_type> (str.append (".graph"), row_lengths);
-  typename values_type::HostMirror h_values = Kokkos::create_mirror_view (values);
-  typename index_type::HostMirror h_entries = Kokkos::create_mirror_view (graph.entries);
-
-  // FIXME (mfh 21 Jun 2013) This needs to be a parallel copy.
-  // Furthermore, why are the arrays copied twice? -- once here, to a
-  // host view, and once below, in the deep copy?
-  for (size_type i = 0; i < annz; ++i) {
-    if (val) {
-      h_values(i) = val[i];
-    }
-    h_entries(i) = cols[i];
-  }
-
-  Kokkos::deep_copy (values, h_values);
-  Kokkos::deep_copy (graph.entries, h_entries);
-}
 }
 #endif
diff --git a/unit_test/sparse/Test_Sparse_CrsMatrix.hpp b/unit_test/sparse/Test_Sparse_CrsMatrix.hpp
index 792bb56466..facdafa28a 100644
--- a/unit_test/sparse/Test_Sparse_CrsMatrix.hpp
+++ b/unit_test/sparse/Test_Sparse_CrsMatrix.hpp
@@ -192,6 +192,26 @@ testCrsMatrix ()
   //printf ("A is %d by %d\n", A.numRows (), A.numCols ());
 }
 
+template <typename scalar_t, typename lno_t, typename size_type, typename device>
+void
+testCrsMatrixRawConstructor()
+{
+  int nrows = 5;
+  //note: last 2 columns will be empty.
+  //This makes sure the ncols provided to constructor is preserved.
+  int ncols = 7;
+  int nnz = 9;
+  //NOTE: this is not a mistake, the raw ptr constructor takes rowmap as ordinal.
+  std::vector<lno_t> rowmap = {0, 0, 2, 5, 6, 9};
+  std::vector<lno_t> entries = {3, 4, 0, 1, 2, 2, 0, 3, 4};
+  std::vector<scalar_t> values(nnz, Kokkos::ArithTraits<scalar_t>::one());
+  KokkosSparse::CrsMatrix<scalar_t, lno_t, device, void, size_type> A(
+      "A", nrows, ncols, nnz, values.data(), rowmap.data(), entries.data());
+  EXPECT_EQ(A.numRows(), nrows);
+  EXPECT_EQ(A.numCols(), ncols);
+  EXPECT_EQ(A.nnz(), nnz);
+}
+
 template <typename scalar_t, typename lno_t, typename size_type, typename device>
 void
 testCrsMatrixHostMirror ()
@@ -229,6 +249,7 @@ testCrsMatrixHostMirror ()
 #define EXECUTE_TEST(SCALAR, ORDINAL, OFFSET, DEVICE) \
 TEST_F( TestCategory, sparse ## _ ## crsmatrix ## _ ## SCALAR ## _ ## ORDINAL ## _ ## OFFSET ## _ ## DEVICE ) { \
   testCrsMatrix<SCALAR, ORDINAL, OFFSET, DEVICE> (); \
+  testCrsMatrixRawConstructor<SCALAR, ORDINAL, OFFSET, DEVICE> (); \
 } \
 TEST_F( TestCategory, sparse ## _ ## crsmatrix_host_mirror ## _ ## SCALAR ## _ ## ORDINAL ## _ ## OFFSET ## _ ## DEVICE ) { \
   testCrsMatrixHostMirror<SCALAR, ORDINAL, OFFSET, DEVICE> (); \