1 files changed, 70 insertions, 0 deletions
diff --git a/staging_vespalib/src/tests/sequencedtaskexecutor/sequencedtaskexecutor_benchmark.cpp b/staging_vespalib/src/tests/sequencedtaskexecutor/sequencedtaskexecutor_benchmark.cpp
new file mode 100644
index 00000000000..042408d439f
--- /dev/null
+++ b/staging_vespalib/src/tests/sequencedtaskexecutor/sequencedtaskexecutor_benchmark.cpp
@@ -0,0 +1,70 @@
+// Copyright 2020 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+
+#include <vespa/vespalib/util/sequencedtaskexecutor.h>
+#include <vespa/vespalib/util/adaptive_sequenced_executor.h>
+#include <vespa/vespalib/util/lambdatask.h>
+#include <vespa/vespalib/util/time.h>
+#include <atomic>
+
+using vespalib::ISequencedTaskExecutor;
+using vespalib::SequencedTaskExecutor;
+using vespalib::AdaptiveSequencedExecutor;
+using ExecutorId = vespalib::ISequencedTaskExecutor::ExecutorId;
+
+size_t do_work(size_t size) {
+    size_t ret = 0;
+    for (size_t i = 0; i < size; ++i) {
+        for (size_t j = 0; j < 128; ++j) {
+            ret = (ret + i) * j;
+        }
+    }
+    return ret;
+}
+
+struct SimpleParams {
+    int argc;
+    char **argv;
+    int idx;
+    SimpleParams(int argc_in, char **argv_in) : argc(argc_in), argv(argv_in), idx(0) {}
+    int next(const char *name, int fallback) {
+        ++idx;
+        int value = 0;
+        if (argc > idx) {
+            value = atoi(argv[idx]);
+        } else {
+            value = fallback;
+        }
+        fprintf(stderr, "param %s: %d\n", name, value);
+        return value;
+    }
+};
+
+int main(int argc, char **argv) {
+    SimpleParams params(argc, argv);
+    bool use_adaptive_executor = params.next("use_adaptive_executor", 0);
+    bool optimize_for_throughput = params.next("optimize_for_throughput", 0);
+    size_t num_tasks = params.next("num_tasks", 1000000);
+    size_t num_strands = params.next("num_strands", 4);
+    size_t task_limit = params.next("task_limit", 1000);
+    size_t num_threads = params.next("num_threads", num_strands);
+    size_t max_waiting = params.next("max_waiting", optimize_for_throughput ? 32 : 0);
+    size_t work_size = params.next("work_size", 0);
+    std::atomic<long> counter(0);
+    std::unique_ptr<ISequencedTaskExecutor> executor;
+    if (use_adaptive_executor) {
+        executor = std::make_unique<AdaptiveSequencedExecutor>(num_strands, num_threads, max_waiting, task_limit);
+    } else {
+        auto optimize = optimize_for_throughput
+                        ? vespalib::Executor::OptimizeFor::THROUGHPUT
+                        : vespalib::Executor::OptimizeFor::LATENCY;
+        executor = SequencedTaskExecutor::create(num_strands, task_limit, optimize);
+    }
+    vespalib::Timer timer;
+    for (size_t task_id = 0; task_id < num_tasks; ++task_id) {
+        executor->executeTask(ExecutorId(task_id % num_strands),
+                              vespalib::makeLambdaTask([&counter,work_size] { (void) do_work(work_size); counter++; }));
+    }
+    executor.reset();
+    fprintf(stderr, "\ntotal time: %zu ms\n", vespalib::count_ms(timer.elapsed()));
+    return (size_t(counter) == num_tasks) ? 0 : 1;
+}