[EM] Enable access to the number of batches. (#10691)

- Expose `NumBatches` in `DMatrix`.
- Small cleanup for removing legacy CUDA stream and ~force CUDA context initialization~.
- Purge old external memory data generation code.

include/xgboost/data.h

@@ -541,9 +541,12 @@ class DMatrix {
   [[nodiscard]] bool PageExists() const;
 
   /**
-   * @return Whether the data columns single column block.
+   * @return Whether the contains a single batch.
+   *
+   * The naming is legacy.
    */
-  [[nodiscard]] virtual bool SingleColBlock() const = 0;
+  [[nodiscard]] bool SingleColBlock() const { return this->NumBatches() == 1; }
+  [[nodiscard]] virtual std::int32_t NumBatches() const { return 1; }
 
   virtual ~DMatrix();
 

src/common/device_helpers.cuh

@@ -486,24 +486,20 @@ class TypedDiscard : public thrust::discard_iterator<T> {
 } // namespace detail
 
 template <typename T>
-using TypedDiscard =
-    std::conditional_t<HasThrustMinorVer<12>(), detail::TypedDiscardCTK114<T>,
-                       detail::TypedDiscard<T>>;
+using TypedDiscard = std::conditional_t<HasThrustMinorVer<12>(), detail::TypedDiscardCTK114<T>,
+                                        detail::TypedDiscard<T>>;
 
 template <typename VectorT, typename T = typename VectorT::value_type,
-  typename IndexT = typename xgboost::common::Span<T>::index_type>
-xgboost::common::Span<T> ToSpan(
-    VectorT &vec,
-    IndexT offset = 0,
-    IndexT size = std::numeric_limits<size_t>::max()) {
+          typename IndexT = typename xgboost::common::Span<T>::index_type>
+xgboost::common::Span<T> ToSpan(VectorT &vec, IndexT offset = 0,
+                                IndexT size = std::numeric_limits<size_t>::max()) {
   size = size == std::numeric_limits<size_t>::max() ? vec.size() : size;
   CHECK_LE(offset + size, vec.size());
-  return {vec.data().get() + offset, size};
+  return {thrust::raw_pointer_cast(vec.data()) + offset, size};
 }
 
 template <typename T>
-xgboost::common::Span<T> ToSpan(thrust::device_vector<T>& vec,
-                                size_t offset, size_t size) {
+xgboost::common::Span<T> ToSpan(thrust::device_vector<T> &vec, size_t offset, size_t size) {
   return ToSpan(vec, offset, size);
 }
 
@@ -874,13 +870,7 @@ inline void CUDAEvent::Record(CUDAStreamView stream) {  // NOLINT
 
 // Changing this has effect on prediction return, where we need to pass the pointer to
 // third-party libraries like cuPy
-inline CUDAStreamView DefaultStream() {
-#ifdef CUDA_API_PER_THREAD_DEFAULT_STREAM
-  return CUDAStreamView{cudaStreamPerThread};
-#else
-  return CUDAStreamView{cudaStreamLegacy};
-#endif
-}
+inline CUDAStreamView DefaultStream() { return CUDAStreamView{cudaStreamPerThread}; }
 
 class CUDAStream {
   cudaStream_t stream_;

src/data/extmem_quantile_dmatrix.cc

@@ -74,6 +74,8 @@ void ExtMemQuantileDMatrix::InitFromCPU(
   cpu_impl::GetDataShape(ctx, proxy, *iter, missing, &ext_info);
   ext_info.SetInfo(ctx, &this->info_);
 
+  this->n_batches_ = ext_info.n_batches;
+
   /**
    * Generate quantiles
    */

src/data/extmem_quantile_dmatrix.h

@@ -33,7 +33,7 @@ class ExtMemQuantileDMatrix : public QuantileDMatrix {
                         std::string cache, bst_bin_t max_bin, bool on_host);
   ~ExtMemQuantileDMatrix() override;
 
-  [[nodiscard]] bool SingleColBlock() const override { return false; }
+  [[nodiscard]] std::int32_t NumBatches() const override { return n_batches_; }
 
  private:
   void InitFromCPU(
@@ -63,6 +63,7 @@ class ExtMemQuantileDMatrix : public QuantileDMatrix {
   std::string cache_prefix_;
   bool on_host_;
   BatchParam batch_;
+  bst_idx_t n_batches_{0};
 
   using EllpackDiskPtr = std::shared_ptr<ExtEllpackPageSource>;
   using EllpackHostPtr = std::shared_ptr<ExtEllpackPageHostSource>;

src/data/iterative_dmatrix.h

@@ -57,8 +57,6 @@ class IterativeDMatrix : public QuantileDMatrix {
 
   BatchSet<EllpackPage> GetEllpackBatches(Context const *ctx, const BatchParam &param) override;
   BatchSet<ExtSparsePage> GetExtBatches(Context const *ctx, BatchParam const &param) override;
-
-  bool SingleColBlock() const override { return true; }
 };
 }  // namespace data
 }  // namespace xgboost

src/data/proxy_dmatrix.h

@@ -94,7 +94,6 @@ class DMatrixProxy : public DMatrix {
   MetaInfo const& Info() const override { return info_; }
   Context const* Ctx() const override { return &ctx_; }
 
-  bool SingleColBlock() const override { return false; }
   bool EllpackExists() const override { return false; }
   bool GHistIndexExists() const override { return false; }
   bool SparsePageExists() const override { return false; }

src/data/simple_dmatrix.h

@@ -33,7 +33,6 @@ class SimpleDMatrix : public DMatrix {
   const MetaInfo& Info() const override;
   Context const* Ctx() const override { return &fmat_ctx_; }
 
-  bool SingleColBlock() const override { return true; }
   DMatrix* Slice(common::Span<int32_t const> ridxs) override;
   DMatrix* SliceCol(int num_slices, int slice_id) override;
 

src/data/sparse_page_dmatrix.h

@@ -90,8 +90,7 @@ class SparsePageDMatrix : public DMatrix {
   [[nodiscard]] MetaInfo &Info() override;
   [[nodiscard]] const MetaInfo &Info() const override;
   [[nodiscard]] Context const *Ctx() const override { return &fmat_ctx_; }
-  // The only DMatrix implementation that returns false.
-  [[nodiscard]] bool SingleColBlock() const override { return false; }
+  [[nodiscard]] std::int32_t NumBatches() const override { return n_batches_; }
   DMatrix *Slice(common::Span<std::int32_t const>) override {
     LOG(FATAL) << "Slicing DMatrix is not supported for external memory.";
     return nullptr;

src/data/sparse_page_source.cc

@@ -3,10 +3,10 @@
  */
 #include "sparse_page_source.h"
 
-#include <filesystem>  // for exists
-#include <string>      // for string
 #include <cstdio>      // for remove
+#include <filesystem>  // for exists
 #include <numeric>     // for partial_sum
+#include <string>      // for string
 
 namespace xgboost::data {
 void Cache::Commit() {
@@ -27,4 +27,8 @@ void TryDeleteCacheFile(const std::string& file) {
                  << "; you may want to remove it manually";
   }
 }
+
+#if !defined(XGBOOST_USE_CUDA)
+void InitNewThread::operator()() const { *GlobalConfigThreadLocalStore::Get() = config; }
+#endif
 }  // namespace xgboost::data

src/data/sparse_page_source.cu

@@ -18,4 +18,14 @@ void DevicePush(DMatrixProxy *proxy, float missing, SparsePage *page) {
   cuda_impl::Dispatch(proxy,
                       [&](auto const &value) { CopyToSparsePage(value, device, missing, page); });
 }
+
+void InitNewThread::operator()() const {
+  *GlobalConfigThreadLocalStore::Get() = config;
+  // For CUDA 12.2, we need to force initialize the CUDA context by synchronizing the
+  // stream when creating a new thread in the thread pool. While for CUDA 11.8, this
+  // action might cause an insufficient driver version error for some reason. Lastly, it
+  // should work with CUDA 12.5 without any action being taken.
+
+  // dh::DefaultStream().Sync();
+}
 }  // namespace xgboost::data

src/data/sparse_page_source.h

@@ -210,6 +210,12 @@ class DefaultFormatPolicy {
   }
 };
 
+struct InitNewThread {
+  GlobalConfiguration config = *GlobalConfigThreadLocalStore::Get();
+
+  void operator()() const;
+};
+
 /**
  * @brief Base class for all page sources. Handles fetching, writing, and iteration.
  *
@@ -330,10 +336,7 @@ class SparsePageSourceImpl : public BatchIteratorImpl<S>, public FormatStreamPol
  public:
   SparsePageSourceImpl(float missing, int nthreads, bst_feature_t n_features, bst_idx_t n_batches,
                        std::shared_ptr<Cache> cache)
-      : workers_{std::max(2, std::min(nthreads, 16)),
-                 [config = *GlobalConfigThreadLocalStore::Get()] {
-                   *GlobalConfigThreadLocalStore::Get() = config;
-                 }},
+      : workers_{std::max(2, std::min(nthreads, 16)), InitNewThread{}},
         missing_{missing},
         nthreads_{nthreads},
         n_features_{n_features},

tests/cpp/data/test_data.cc

@@ -63,26 +63,27 @@ TEST(SparsePage, PushCSC) {
 }
 
 TEST(SparsePage, PushCSCAfterTranspose) {
-  size_t constexpr kPageSize = 1024, kEntriesPerCol = 3;
-  size_t constexpr kEntries = kPageSize * kEntriesPerCol * 2;
-  std::unique_ptr<DMatrix> dmat = CreateSparsePageDMatrix(kEntries);
+  bst_idx_t constexpr kRows = 1024, kCols = 21;
+
+  auto dmat =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(4).GenerateSparsePageDMatrix("temp", true);
   const int ncols = dmat->Info().num_col_;
-  SparsePage page; // Consolidated sparse page
-  for (const auto &batch : dmat->GetBatches<xgboost::SparsePage>()) {
+  SparsePage page;  // Consolidated sparse page
+  for (const auto& batch : dmat->GetBatches<xgboost::SparsePage>()) {
     // Transpose each batch and push
     SparsePage tmp = batch.GetTranspose(ncols, AllThreadsForTest());
     page.PushCSC(tmp);
   }
 
   // Make sure that the final sparse page has the right number of entries
-  ASSERT_EQ(kEntries, page.data.Size());
+  ASSERT_EQ(kRows * kCols, page.data.Size());
 
   page.SortRows(AllThreadsForTest());
   auto v = page.GetView();
   for (size_t i = 0; i < v.Size(); ++i) {
     auto column = v[i];
     for (size_t j = 1; j < column.size(); ++j) {
-      ASSERT_GE(column[j].fvalue, column[j-1].fvalue);
+      ASSERT_GE(column[j].fvalue, column[j - 1].fvalue);
     }
   }
 }

tests/cpp/data/test_ellpack_page.cu

@@ -140,13 +140,11 @@ struct ReadRowFunction {
 TEST(EllpackPage, Copy) {
   constexpr size_t kRows = 1024;
   constexpr size_t kCols = 16;
-  constexpr size_t kPageSize = 1024;
 
   // Create a DMatrix with multiple batches.
-  dmlc::TemporaryDirectory tmpdir;
-  std::unique_ptr<DMatrix>
-      dmat(CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
-  Context ctx{MakeCUDACtx(0)};
+  auto dmat =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(4).GenerateSparsePageDMatrix("temp", true);
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
   auto page = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
 
@@ -187,14 +185,12 @@ TEST(EllpackPage, Copy) {
 TEST(EllpackPage, Compact) {
   constexpr size_t kRows = 16;
   constexpr size_t kCols = 2;
-  constexpr size_t kPageSize = 1;
   constexpr size_t kCompactedRows = 8;
 
   // Create a DMatrix with multiple batches.
-  dmlc::TemporaryDirectory tmpdir;
-  std::unique_ptr<DMatrix> dmat(
-      CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
-  Context ctx{MakeCUDACtx(0)};
+  auto dmat =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(2).GenerateSparsePageDMatrix("temp", true);
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
   auto page = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
 

tests/cpp/data/test_sparse_page_dmatrix.cc

@@ -214,15 +214,15 @@ TEST(SparsePageDMatrix, MetaInfo) {
 }
 
 TEST(SparsePageDMatrix, RowAccess) {
-  std::unique_ptr<xgboost::DMatrix> dmat = xgboost::CreateSparsePageDMatrix(24);
+  auto dmat = RandomDataGenerator{12, 6, 0.8f}.Batches(2).GenerateSparsePageDMatrix("temp", false);
 
   // Test the data read into the first row
   auto &batch = *dmat->GetBatches<xgboost::SparsePage>().begin();
   auto page = batch.GetView();
   auto first_row = page[0];
-  ASSERT_EQ(first_row.size(), 3ul);
-  EXPECT_EQ(first_row[2].index, 2u);
-  EXPECT_NEAR(first_row[2].fvalue, 0.986566, 1e-4);
+  ASSERT_EQ(first_row.size(), 1ul);
+  EXPECT_EQ(first_row[0].index, 5u);
+  EXPECT_NEAR(first_row[0].fvalue, 0.1805125, 1e-4);
 }
 
 TEST(SparsePageDMatrix, ColAccess) {
@@ -268,11 +268,10 @@ TEST(SparsePageDMatrix, ColAccess) {
 }
 
 TEST(SparsePageDMatrix, ThreadSafetyException) {
-  size_t constexpr kEntriesPerCol = 3;
-  size_t constexpr kEntries = 64 * kEntriesPerCol * 2;
   Context ctx;
 
-  std::unique_ptr<xgboost::DMatrix> dmat = xgboost::CreateSparsePageDMatrix(kEntries);
+  auto dmat =
+      RandomDataGenerator{4096, 12, 0.0f}.Batches(8).GenerateSparsePageDMatrix("temp", true);
 
   int threads = 1000;
 
@@ -304,10 +303,9 @@ TEST(SparsePageDMatrix, ThreadSafetyException) {
 
 // Multi-batches access
 TEST(SparsePageDMatrix, ColAccessBatches) {
-  size_t constexpr kPageSize = 1024, kEntriesPerCol = 3;
-  size_t constexpr kEntries = kPageSize * kEntriesPerCol * 2;
   // Create multiple sparse pages
-  std::unique_ptr<xgboost::DMatrix> dmat{xgboost::CreateSparsePageDMatrix(kEntries)};
+  auto dmat =
+      RandomDataGenerator{1024, 32, 0.4f}.Batches(3).GenerateSparsePageDMatrix("temp", true);
   ASSERT_EQ(dmat->Ctx()->Threads(), AllThreadsForTest());
   Context ctx;
   for (auto const &page : dmat->GetBatches<xgboost::CSCPage>(&ctx)) {

tests/cpp/data/test_sparse_page_dmatrix.cu

@@ -115,13 +115,10 @@ TEST(SparsePageDMatrix, EllpackSkipSparsePage) {
 }
 
 TEST(SparsePageDMatrix, MultipleEllpackPages) {
-  Context ctx{MakeCUDACtx(0)};
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
   dmlc::TemporaryDirectory tmpdir;
-  std::string filename = tmpdir.path + "/big.libsvm";
-  size_t constexpr kPageSize = 64, kEntriesPerCol = 3;
-  size_t constexpr kEntries = kPageSize * kEntriesPerCol * 2;
-  std::unique_ptr<DMatrix> dmat = CreateSparsePageDMatrix(kEntries, filename);
+  auto dmat = RandomDataGenerator{1024, 2, 0.5f}.Batches(2).GenerateSparsePageDMatrix("temp", true);
 
   // Loop over the batches and count the records
   std::int64_t batch_count = 0;
@@ -135,15 +132,13 @@ TEST(SparsePageDMatrix, MultipleEllpackPages) {
   EXPECT_EQ(row_count, dmat->Info().num_row_);
 
   auto path =
-      data::MakeId(filename,
-                   dynamic_cast<data::SparsePageDMatrix *>(dmat.get())) +
-      ".ellpack.page";
+      data::MakeId("tmep", dynamic_cast<data::SparsePageDMatrix*>(dmat.get())) + ".ellpack.page";
 }
 
 TEST(SparsePageDMatrix, RetainEllpackPage) {
-  Context ctx{MakeCUDACtx(0)};
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{32, tree::TrainParam::DftSparseThreshold()};
-  auto m = CreateSparsePageDMatrix(10000);
+  auto m = RandomDataGenerator{2048, 4, 0.0f}.Batches(8).GenerateSparsePageDMatrix("temp", true);
 
   auto batches = m->GetBatches<EllpackPage>(&ctx, param);
   auto begin = batches.begin();
@@ -278,20 +273,19 @@ struct ReadRowFunction {
 };
 
 TEST(SparsePageDMatrix, MultipleEllpackPageContent) {
-  constexpr size_t kRows = 6;
+  constexpr size_t kRows = 16;
   constexpr size_t kCols = 2;
   constexpr int kMaxBins = 256;
-  constexpr size_t kPageSize = 1;
 
   // Create an in-memory DMatrix.
-  std::unique_ptr<DMatrix> dmat(CreateSparsePageDMatrixWithRC(kRows, kCols, 0, true));
+  auto dmat =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(1).GenerateSparsePageDMatrix("temp", true);
 
   // Create a DMatrix with multiple batches.
-  dmlc::TemporaryDirectory tmpdir;
-  std::unique_ptr<DMatrix>
-      dmat_ext(CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
+  auto dmat_ext =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(2).GenerateSparsePageDMatrix("temp", true);
 
-  Context ctx{MakeCUDACtx(0)};
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{kMaxBins, tree::TrainParam::DftSparseThreshold()};
   auto impl = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
   EXPECT_EQ(impl->base_rowid, 0);
@@ -325,17 +319,16 @@ TEST(SparsePageDMatrix, EllpackPageMultipleLoops) {
   constexpr size_t kRows = 1024;
   constexpr size_t kCols = 16;
   constexpr int kMaxBins = 256;
-  constexpr size_t kPageSize = 4096;
 
   // Create an in-memory DMatrix.
-  std::unique_ptr<DMatrix> dmat(CreateSparsePageDMatrixWithRC(kRows, kCols, 0, true));
+  auto dmat =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(1).GenerateSparsePageDMatrix("temp", true);
 
   // Create a DMatrix with multiple batches.
-  dmlc::TemporaryDirectory tmpdir;
-  std::unique_ptr<DMatrix>
-      dmat_ext(CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
+  auto dmat_ext =
+      RandomDataGenerator{kRows, kCols, 0.0f}.Batches(8).GenerateSparsePageDMatrix("temp", true);
 
-  Context ctx{MakeCUDACtx(0)};
+  auto ctx = MakeCUDACtx(0);
   auto param = BatchParam{kMaxBins, tree::TrainParam::DftSparseThreshold()};
 
   size_t current_row = 0;

tests/cpp/gbm/test_gbtree.cc

@@ -715,7 +715,7 @@ TEST(GBTree, InplacePredictionError) {
       p_fmat = rng.GenerateQuantileDMatrix(true);
     } else {
 #if defined(XGBOOST_USE_CUDA)
-      p_fmat = rng.GenerateDeviceDMatrix(true);
+      p_fmat = rng.Device(ctx->Device()).GenerateQuantileDMatrix(true);
 #else
       CHECK(p_fmat);
 #endif  // defined(XGBOOST_USE_CUDA)