Add more examples.

- exec_tag_timer
- exec_tag_sync
- skip
- throughput

examples/throughput.cu

@@ -0,0 +1,60 @@
+/*
+ *  Copyright 2021 NVIDIA Corporation
+ *
+ *  Licensed under the Apache License, Version 2.0 with the LLVM exception
+ *  (the "License"); you may not use this file except in compliance with
+ *  the License.
+ *
+ *  You may obtain a copy of the License at
+ *
+ *      http://llvm.org/foundation/relicensing/LICENSE.txt
+ *
+ *  Unless required by applicable law or agreed to in writing, software
+ *  distributed under the License is distributed on an "AS IS" BASIS,
+ *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ *  See the License for the specific language governing permissions and
+ *  limitations under the License.
+ */
+
+#include <nvbench/nvbench.cuh>
+
+// Grab some testing kernels from NVBench:
+#include <nvbench/test_kernels.cuh>
+
+// Thrust vectors simplify memory management:
+#include <thrust/device_vector.h>
+
+// `throughput_bench` copies a 64 MiB buffer of int32_t, and reports throughput
+// in a variety of ways.
+//
+// Calling `state.add_element_count(num_elements)` with the number of input
+// items will report the item throughput rate in elements-per-second.
+//
+// Calling `state.add_global_memory_reads<T>(num_elements)` and/or
+// `state.add_global_memory_writes<T>(num_elements)` will report global device
+// memory throughput as a percentage of the current device's peak global memory
+// bandwidth, and also in bytes-per-second.
+//
+// All of these methods take an optional second `column_name` argument, which
+// will add a new column to the output with the reported element count / buffer
+// size and column name.
+void throughput_bench(nvbench::state &state)
+{
+  // Allocate input data:
+  const std::size_t num_values = 64 * 1024 * 1024 / sizeof(nvbench::int32_t);
+  thrust::device_vector<nvbench::int32_t> input(num_values);
+  thrust::device_vector<nvbench::int32_t> output(num_values);
+
+  // Provide throughput information:
+  state.add_element_count(num_values, "NumElements");
+  state.add_global_memory_reads<nvbench::int32_t>(num_values, "DataSize");
+  state.add_global_memory_writes<nvbench::int32_t>(num_values);
+
+  state.exec([&input, &output, num_values](nvbench::launch &launch) {
+    nvbench::copy_kernel<<<256, 256, 0, launch.get_stream()>>>(
+      thrust::raw_pointer_cast(input.data()),
+      thrust::raw_pointer_cast(output.data()),
+      num_values);
+  });
+}
+NVBENCH_BENCH(throughput_bench);