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ANN bench fix latency measurement overhead #2084

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Jan 24, 2024
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16 changes: 7 additions & 9 deletions cpp/bench/ann/src/common/benchmark.hpp
Original file line number Diff line number Diff line change
Expand Up @@ -287,11 +287,11 @@ void bench_search(::benchmark::State& state,
std::make_shared<buf<std::size_t>>(current_algo_props->query_memory_type, k * query_set_size);

cuda_timer gpu_timer;
auto start = std::chrono::high_resolution_clock::now();
{
nvtx_case nvtx{state.name()};

auto algo = dynamic_cast<ANN<T>*>(current_algo.get())->copy();
auto algo = dynamic_cast<ANN<T>*>(current_algo.get())->copy();
auto start = std::chrono::high_resolution_clock::now();
for (auto _ : state) {
[[maybe_unused]] auto ntx_lap = nvtx.lap();
[[maybe_unused]] auto gpu_lap = gpu_timer.lap();
Expand All @@ -314,17 +314,15 @@ void bench_search(::benchmark::State& state,

queries_processed += n_queries;
}
auto end = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::duration<double>>(end - start).count();
if (state.thread_index() == 0) { state.counters.insert({{"end_to_end", duration}}); }
state.counters.insert({"Latency", {duration, benchmark::Counter::kAvgIterations}});
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I have also applied Artem's suggestion to store latency values with benchmark::Counter::kAvgIterations marker.

Earlier we manually divided by number of iterations and let gbench average over threads using kAvgThreads. Since iterations are counted as total iterations performed by all threads, using kAviIterations leads to the same results (without manual divisions by iterations).

}
auto end = std::chrono::high_resolution_clock::now();
auto duration = std::chrono::duration_cast<std::chrono::duration<double>>(end - start).count();
if (state.thread_index() == 0) { state.counters.insert({{"end_to_end", duration}}); }
state.counters.insert(
{"Latency", {duration / double(state.iterations()), benchmark::Counter::kAvgThreads}});

state.SetItemsProcessed(queries_processed);
if (cudart.found()) {
double gpu_time_per_iteration = gpu_timer.total_time() / (double)state.iterations();
state.counters.insert({"GPU", {gpu_time_per_iteration, benchmark::Counter::kAvgThreads}});
state.counters.insert({"GPU", {gpu_timer.total_time(), benchmark::Counter::kAvgIterations}});
}

// This will be the total number of queries across all threads
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