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Use fewer ramp up repetitions when KeepRunningBatch is used (#1113)
Use the benchmark's reported iteration count when estimating iterations for the next repetition, rather than the requested iteration count. When the benchmark uses KeepRunningBatch the actual iteration count can be larger than the one the runner requested. Prior to this fix the runner was underestimating the next iteration count, sometimes significantly so. Consider the case of a benchmark using a batch size of 1024. Prior to this change, the benchmark runner would attempt iteration counts 1, 10, 100 and 1000, yet the benchmark itself would do the same amount of work each time: a single batch of 1024 iterations. The discrepancy could also contribute to estimation errors once the benchmark time reached 10% of the target. For example, if the very first batch of 1024 iterations reached 10% of benchmark_min_min time, the runner would attempt to scale that to 100% from a basis of one iteration rather than 1024. This bug was particularly noticeable in benchmarks with large batch sizes, especially when the benchmark also had slow set up or tear down phases. With this fix in place it is possible to use KeepRunningBatch to achieve a kind of "minimum iteration count" feature by using a larger fixed batch size. For example, a benchmark may build a map of 500K elements and test a "find" operation. There is no point in running "find" just 1, 10, 100, etc., times. The benchmark can now pick a batch size of something like 10K, and the runner will arrive at the final max iteration count with in noticeably fewer repetitions.
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@ -109,7 +109,7 @@ BenchmarkReporter::Run CreateRunReport(
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}
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// Execute one thread of benchmark b for the specified number of iterations.
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// Adds the stats collected for the thread into *total.
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// Adds the stats collected for the thread into manager->results.
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void RunInThread(const BenchmarkInstance* b, IterationCount iters,
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int thread_id, ThreadManager* manager) {
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internal::ThreadTimer timer(
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@ -236,8 +236,10 @@ class BenchmarkRunner {
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VLOG(2) << "Ran in " << i.results.cpu_time_used << "/"
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<< i.results.real_time_used << "\n";
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// So for how long were we running?
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i.iters = iters;
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// By using KeepRunningBatch a benchmark can iterate more times than
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// requested, so take the iteration count from i.results.
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i.iters = i.results.iterations / b.threads;
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// Base decisions off of real time if requested by this benchmark.
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i.seconds = i.results.cpu_time_used;
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if (b.use_manual_time) {
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@ -108,15 +108,30 @@ void BM_KeepRunning(benchmark::State& state) {
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BENCHMARK(BM_KeepRunning);
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void BM_KeepRunningBatch(benchmark::State& state) {
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// Choose a prime batch size to avoid evenly dividing max_iterations.
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const benchmark::IterationCount batch_size = 101;
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// Choose a batch size >1000 to skip the typical runs with iteration
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// targets of 10, 100 and 1000. If these are not actually skipped the
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// bug would be detectable as consecutive runs with the same iteration
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// count. Below we assert that this does not happen.
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const benchmark::IterationCount batch_size = 1009;
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static benchmark::IterationCount prior_iter_count = 0;
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benchmark::IterationCount iter_count = 0;
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while (state.KeepRunningBatch(batch_size)) {
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iter_count += batch_size;
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}
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assert(state.iterations() == iter_count);
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// Verify that the iteration count always increases across runs (see
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// comment above).
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assert(iter_count == batch_size // max_iterations == 1
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|| iter_count > prior_iter_count); // max_iterations > batch_size
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prior_iter_count = iter_count;
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}
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BENCHMARK(BM_KeepRunningBatch);
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// Register with a fixed repetition count to establish the invariant that
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// the iteration count should always change across runs. This overrides
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// the --benchmark_repetitions command line flag, which would otherwise
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// cause this test to fail if set > 1.
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BENCHMARK(BM_KeepRunningBatch)->Repetitions(1);
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void BM_RangedFor(benchmark::State& state) {
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benchmark::IterationCount iter_count = 0;
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