Merge branch 'branch-22.04' into bug-regex-hex-a

rapidsai · Feb 8, 2022 · 2456ed7 · 2456ed7
2 parents 3ffb8ca + 1bc3727
commit 2456ed7
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diff --git a/ci/gpu/build.sh b/ci/gpu/build.sh
@@ -249,15 +249,15 @@ fi
 
 cd "$WORKSPACE/python/cudf"
 gpuci_logger "Python py.test for cuDF"
-py.test -n 6 --cache-clear --basetemp="$WORKSPACE/cudf-cuda-tmp" --ignore="$WORKSPACE/python/cudf/cudf/benchmarks" --junitxml="$WORKSPACE/junit-cudf.xml" -v --cov-config=.coveragerc --cov=cudf --cov-report=xml:"$WORKSPACE/python/cudf/cudf-coverage.xml" --cov-report term
+py.test -n 8 --cache-clear --basetemp="$WORKSPACE/cudf-cuda-tmp" --ignore="$WORKSPACE/python/cudf/cudf/benchmarks" --junitxml="$WORKSPACE/junit-cudf.xml" -v --cov-config=.coveragerc --cov=cudf --cov-report=xml:"$WORKSPACE/python/cudf/cudf-coverage.xml" --cov-report term --dist=loadscope
 
 cd "$WORKSPACE/python/dask_cudf"
 gpuci_logger "Python py.test for dask-cudf"
-py.test -n 6 --cache-clear --basetemp="$WORKSPACE/dask-cudf-cuda-tmp" --junitxml="$WORKSPACE/junit-dask-cudf.xml" -v --cov-config=.coveragerc --cov=dask_cudf --cov-report=xml:"$WORKSPACE/python/dask_cudf/dask-cudf-coverage.xml" --cov-report term
+py.test -n 8 --cache-clear --basetemp="$WORKSPACE/dask-cudf-cuda-tmp" --junitxml="$WORKSPACE/junit-dask-cudf.xml" -v --cov-config=.coveragerc --cov=dask_cudf --cov-report=xml:"$WORKSPACE/python/dask_cudf/dask-cudf-coverage.xml" --cov-report term
 
 cd "$WORKSPACE/python/custreamz"
 gpuci_logger "Python py.test for cuStreamz"
-py.test -n 6 --cache-clear --basetemp="$WORKSPACE/custreamz-cuda-tmp" --junitxml="$WORKSPACE/junit-custreamz.xml" -v --cov-config=.coveragerc --cov=custreamz --cov-report=xml:"$WORKSPACE/python/custreamz/custreamz-coverage.xml" --cov-report term
+py.test -n 8 --cache-clear --basetemp="$WORKSPACE/custreamz-cuda-tmp" --junitxml="$WORKSPACE/junit-custreamz.xml" -v --cov-config=.coveragerc --cov=custreamz --cov-report=xml:"$WORKSPACE/python/custreamz/custreamz-coverage.xml" --cov-report term
 
 gpuci_logger "Test notebooks"
 "$WORKSPACE/ci/gpu/test-notebooks.sh" 2>&1 | tee nbtest.log

diff --git a/cpp/benchmarks/CMakeLists.txt b/cpp/benchmarks/CMakeLists.txt
@@ -56,8 +56,9 @@ add_custom_command(
 function(ConfigureBench CMAKE_BENCH_NAME)
   add_executable(${CMAKE_BENCH_NAME} ${ARGN})
   set_target_properties(
-    ${CMAKE_BENCH_NAME} PROPERTIES RUNTIME_OUTPUT_DIRECTORY
-                                   "$<BUILD_INTERFACE:${CUDF_BINARY_DIR}/benchmarks>"
+    ${CMAKE_BENCH_NAME}
+    PROPERTIES RUNTIME_OUTPUT_DIRECTORY "$<BUILD_INTERFACE:${CUDF_BINARY_DIR}/benchmarks>"
+               INSTALL_RPATH "\$ORIGIN/../../../lib"
   )
   target_link_libraries(
     ${CMAKE_BENCH_NAME} PRIVATE cudf_benchmark_common cudf_datagen benchmark::benchmark_main
@@ -69,19 +70,33 @@ function(ConfigureBench CMAKE_BENCH_NAME)
     APPEND
     COMMENT "Adding ${CMAKE_BENCH_NAME}"
   )
+
+  install(
+    TARGETS ${CMAKE_BENCH_NAME}
+    COMPONENT testing
+    DESTINATION bin/benchmarks/libcudf
+    EXCLUDE_FROM_ALL
+  )
 endfunction()
 
 # This function takes in a benchmark name and benchmark source for nvbench benchmarks and handles
 # setting all of the associated properties and linking to build the benchmark
 function(ConfigureNVBench CMAKE_BENCH_NAME)
   add_executable(${CMAKE_BENCH_NAME} ${ARGN})
   set_target_properties(
-    ${CMAKE_BENCH_NAME} PROPERTIES RUNTIME_OUTPUT_DIRECTORY
-                                   "$<BUILD_INTERFACE:${CUDF_BINARY_DIR}/benchmarks>"
+    ${CMAKE_BENCH_NAME}
+    PROPERTIES RUNTIME_OUTPUT_DIRECTORY "$<BUILD_INTERFACE:${CUDF_BINARY_DIR}/benchmarks>"
+               INSTALL_RPATH "\$ORIGIN/../../../lib"
   )
   target_link_libraries(
     ${CMAKE_BENCH_NAME} PRIVATE cudf_benchmark_common cudf_datagen nvbench::main
   )
+  install(
+    TARGETS ${CMAKE_BENCH_NAME}
+    COMPONENT testing
+    DESTINATION bin/benchmarks/libcudf
+    EXCLUDE_FROM_ALL
+  )
 endfunction()
 
 # ##################################################################################################

diff --git a/cpp/benchmarks/common/generate_input.cpp b/cpp/benchmarks/common/generate_input.cpp
@@ -65,45 +65,46 @@ T get_distribution_mean(distribution_params<T> const& dist)
 }
 
 // Utilities to determine the mean size of an element, given the data profile
-template <typename T>
-std::enable_if_t<cudf::is_fixed_width<T>(), size_t> avg_element_size(data_profile const& profile)
+template <typename T, CUDF_ENABLE_IF(cudf::is_fixed_width<T>())>
+size_t non_fixed_width_size(data_profile const& profile)
 {
-  return sizeof(T);
+  CUDF_FAIL("Should not be called, use `size_of` for this type instead");
 }
 
-template <typename T>
-std::enable_if_t<!cudf::is_fixed_width<T>(), size_t> avg_element_size(data_profile const& profile)
+template <typename T, CUDF_ENABLE_IF(!cudf::is_fixed_width<T>())>
+size_t non_fixed_width_size(data_profile const& profile)
 {
   CUDF_FAIL("not implemented!");
 }
 
 template <>
-size_t avg_element_size<cudf::string_view>(data_profile const& profile)
+size_t non_fixed_width_size<cudf::string_view>(data_profile const& profile)
 {
   auto const dist = profile.get_distribution_params<cudf::string_view>().length_params;
   return get_distribution_mean(dist);
 }
 
 template <>
-size_t avg_element_size<cudf::list_view>(data_profile const& profile)
+size_t non_fixed_width_size<cudf::list_view>(data_profile const& profile)
 {
   auto const dist_params       = profile.get_distribution_params<cudf::list_view>();
   auto const single_level_mean = get_distribution_mean(dist_params.length_params);
   auto const element_size      = cudf::size_of(cudf::data_type{dist_params.element_type});
   return element_size * pow(single_level_mean, dist_params.max_depth);
 }
 
-struct avg_element_size_fn {
+struct non_fixed_width_size_fn {
   template <typename T>
   size_t operator()(data_profile const& profile)
   {
-    return avg_element_size<T>(profile);
+    return non_fixed_width_size<T>(profile);
   }
 };
 
-size_t avg_element_bytes(data_profile const& profile, cudf::type_id tid)
+size_t avg_element_size(data_profile const& profile, cudf::data_type dtype)
 {
-  return cudf::type_dispatcher(cudf::data_type(tid), avg_element_size_fn{}, profile);
+  if (cudf::is_fixed_width(dtype)) { return cudf::size_of(dtype); }
+  return cudf::type_dispatcher(dtype, non_fixed_width_size_fn{}, profile);
 }
 
 /**
@@ -419,7 +420,7 @@ std::unique_ptr<cudf::column> create_random_column<cudf::string_view>(data_profi
     random_value_fn<uint32_t>{profile.get_distribution_params<cudf::string_view>().length_params};
   auto valid_dist = std::bernoulli_distribution{1. - profile.get_null_frequency()};
 
-  auto const avg_string_len = avg_element_size<cudf::string_view>(profile);
+  auto const avg_string_len = non_fixed_width_size<cudf::string_view>(profile);
   auto const cardinality    = std::min(profile.get_cardinality(), num_rows);
   string_column_data samples(cardinality, cardinality * avg_string_len);
   for (cudf::size_type si = 0; si < cardinality; ++si) {
@@ -593,7 +594,7 @@ std::unique_ptr<cudf::table> create_random_table(std::vector<cudf::type_id> cons
   auto const out_dtype_ids = repeat_dtypes(dtype_ids, num_cols);
   size_t const avg_row_bytes =
     std::accumulate(out_dtype_ids.begin(), out_dtype_ids.end(), 0ul, [&](size_t sum, auto tid) {
-      return sum + avg_element_bytes(profile, tid);
+      return sum + avg_element_size(profile, cudf::data_type(tid));
     });
   cudf::size_type const num_rows = table_bytes.size / avg_row_bytes;