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// Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/eval/eval/typed_cells.h>
#include <vespa/searchlib/common/geo_gcd.h>
#include <vespa/searchlib/tensor/distance_functions.h>
#include <vespa/searchlib/tensor/distance_function_factory.h>
#include <vespa/searchlib/tensor/mips_distance_transform.h>
#include <vespa/vespalib/util/benchmark_timer.h>
#include <vespa/vespalib/util/classname.h>
using namespace search::tensor;
using vespalib::eval::Int8Float;
using vespalib::BFloat16;
using vespalib::eval::TypedCells;
using search::attribute::DistanceMetric;
size_t npos = std::string::npos;
double run_calc(size_t iterations, TypedCells b, const BoundDistanceFunction & df) __attribute__((noinline));
double run_calc_with_limit(size_t iterations, TypedCells b, const BoundDistanceFunction & df) __attribute__((noinline));
double
run_calc(size_t iterations, TypedCells b, const BoundDistanceFunction & df) {
vespalib::BenchmarkTimer timer(1.0);
double min_result = std::numeric_limits<double>::max();
while (timer.has_budget()) {
timer.before();
for (size_t i(0); i < iterations; i++) {
min_result = std::min(df.calc(b), min_result);
}
timer.after();
}
printf("%s::calc: Time used = %1.3f, min_result=%3.3f\n",
vespalib::getClassName(df).c_str(), timer.min_time(), min_result);
return min_result;
}
double
run_calc_with_limit(size_t iterations, TypedCells b, const BoundDistanceFunction & df) {
vespalib::BenchmarkTimer timer(1.0);
double min_result = std::numeric_limits<double>::max();
while (timer.has_budget()) {
timer.before();
for (size_t i(0); i < iterations; i++) {
min_result = std::min(df.calc_with_limit(b, std::numeric_limits<double>::max()), min_result);
}
timer.after();
}
printf("%s::calc_with_limit: Time used = %1.3f, min_result=%3.3f\n",
vespalib::getClassName(df).c_str(), timer.min_time(), min_result);
return min_result;
}
template<typename T>
void benchmark(size_t iterations, size_t elems) __attribute__((noinline));
template<typename T>
void benchmark(size_t iterations, size_t elems, const DistanceFunctionFactory & df) {
std::vector<T> av, bv;
srandom(7);
av.reserve(elems);
bv.reserve(elems);
for (size_t i(0); i < elems; i++) {
av.push_back(random()%128);
bv.push_back(random()%128);
}
TypedCells a_cells(av), b_cells(bv);
double calc_result = run_calc(iterations, b_cells, *df.for_query_vector(a_cells));
double calc_with_limit_result = run_calc_with_limit(iterations, b_cells, *df.for_query_vector(a_cells));
assert(calc_result == calc_with_limit_result);
}
template<typename T>
void benchmark(size_t iterations, size_t elems, const std::string & dist_functions) {
if (dist_functions.find("euclid") != npos) {
benchmark<T>(iterations, elems, EuclideanDistanceFunctionFactory<T>());
}
if (dist_functions.find("angular") != npos) {
if constexpr ( ! std::is_same<T, BFloat16>()) {
benchmark<T>(iterations, elems, AngularDistanceFunctionFactory<T>());
}
}
if (dist_functions.find("prenorm") != npos) {
if constexpr ( ! std::is_same<T, BFloat16>()) {
benchmark<T>(iterations, elems, PrenormalizedAngularDistanceFunctionFactory<T>());
}
}
if (dist_functions.find("mips") != npos) {
if constexpr ( !std::is_same<T, BFloat16>()) {
benchmark<T>(iterations, elems, MipsDistanceFunctionFactory<T>());
}
}
}
void
benchmark(size_t iterations, size_t elems, const std::string & dist_functions, const std::string & data_types) {
if (data_types.find("double") != npos) {
benchmark<double>(iterations, elems, dist_functions);
}
if (data_types.find("float32") != npos) {
benchmark<float>(iterations, elems, dist_functions);
}
if (data_types.find("bfloat16") != npos) {
benchmark<BFloat16>(iterations, elems, dist_functions);
}
if (data_types.find("float8") != npos) {
benchmark<Int8Float>(iterations, elems, dist_functions);
}
}
int
main(int argc, char *argv[]) {
size_t num_iterations = 10000000;
size_t num_elems = 1024;
std::string dist_functions = "angular euclid prenorm mips";
std::string data_types = "double float32 bfloat16 float8";
if (argc > 1) { num_iterations = atol(argv[1]); }
if (argc > 2) { num_elems = atol(argv[2]); }
if (argc > 3) { dist_functions = argv[3]; }
if (argc > 4) { data_types = argv[4]; }
printf("Benchmarking %ld iterations with vector length %ld with distance functions '%s' for data types '%s'\n",
num_iterations, num_elems, dist_functions.c_str(), data_types.c_str());
benchmark(num_iterations, num_elems, dist_functions, data_types);
return 0;
}
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