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// Copyright (c) 2017-2024 Advanced Micro Devices, Inc. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
#ifndef ROCPRIM_BENCHMARK_UTILS_HPP_
#define ROCPRIM_BENCHMARK_UTILS_HPP_
#include <benchmark/benchmark.h>
// rocPRIM
#include <rocprim/block/block_load.hpp>
#include <rocprim/block/block_scan.hpp>
#include <rocprim/device/config_types.hpp>
#include <rocprim/device/detail/device_config_helper.hpp> // partition_config_params
#include <rocprim/intrinsics/arch.hpp>
#include <rocprim/types.hpp>
#include <algorithm>
#include <iostream>
#include <iterator>
#include <memory>
#include <numeric>
#include <random>
#include <regex>
#include <sstream>
#include <string>
#include <type_traits>
#include <utility>
#include <vector>
#define HIP_CHECK(condition) \
{ \
hipError_t error = condition; \
if(error != hipSuccess) \
{ \
std::cout << "HIP error: " << hipGetErrorString(error) << " file: " << __FILE__ \
<< " line: " << __LINE__ << std::endl; \
exit(error); \
} \
}
#define TUNING_SHARED_MEMORY_MAX 65536u
// Support half operators on host side
inline const char* get_seed_message()
{
return "seed for input generation, either an unsigned integer value for determinisic results "
"or 'random' for different inputs for each repetition";
}
/// \brief Provides a sequence of seeds.
class managed_seed
{
public:
/// \param[in] seed_string Either "random" to get random seeds,
/// or an unsigned integer to get (a sequence) of deterministic seeds.
managed_seed(const std::string& seed_string)
{
is_random = seed_string == "random";
if(!is_random)
{
const unsigned int seed = std::stoul(seed_string);
std::seed_seq seq{seed};
seq.generate(seeds.begin(), seeds.end());
}
}
unsigned int get_0() const
{
return is_random ? std::random_device{}() : seeds[0];
}
unsigned int get_1() const
{
return is_random ? std::random_device{}() : seeds[1];
}
unsigned int get_2() const
{
return is_random ? std::random_device{}() : seeds[2];
}
private:
std::array<unsigned int, 3> seeds;
bool is_random;
};
ROCPRIM_HOST inline
rocprim::native_half half_to_native(const rocprim::half& x)
{
return *reinterpret_cast<const rocprim::native_half *>(&x);
}
ROCPRIM_HOST inline
rocprim::half native_to_half(const rocprim::native_half& x)
{
return *reinterpret_cast<const rocprim::half *>(&x);
}
struct half_less
{
ROCPRIM_HOST_DEVICE inline
bool operator()(const rocprim::half& a, const rocprim::half& b) const
{
#if __HIP_DEVICE_COMPILE__
return a < b;
#else
return half_to_native(a) < half_to_native(b);
#endif
}
};
struct half_plus
{
ROCPRIM_HOST_DEVICE inline
rocprim::half operator()(const rocprim::half& a, const rocprim::half& b) const
{
#if __HIP_DEVICE_COMPILE__
return a + b;
#else
return native_to_half(half_to_native(a) + half_to_native(b));
#endif
}
};
struct half_equal_to
{
ROCPRIM_HOST_DEVICE inline
bool operator()(const rocprim::half& a, const rocprim::half& b) const
{
#if __HIP_DEVICE_COMPILE__
return a == b;
#else
return half_to_native(a) == half_to_native(b);
#endif
}
};
// std::uniform_int_distribution is undefined for anything other than:
// short, int, long, long long, unsigned short, unsigned int, unsigned long, or unsigned long long
template <typename T>
struct is_valid_for_int_distribution :
std::integral_constant<bool,
std::is_same<short, T>::value ||
std::is_same<unsigned short, T>::value ||
std::is_same<int, T>::value ||
std::is_same<unsigned int, T>::value ||
std::is_same<long, T>::value ||
std::is_same<unsigned long, T>::value ||
std::is_same<long long, T>::value ||
std::is_same<unsigned long long, T>::value
> {};
template<typename Iterator>
using it_value_t = typename std::iterator_traits<Iterator>::value_type;
using engine_type = std::minstd_rand;
// generate_random_data_n() generates only part of sequence and replicates it,
// because benchmarks usually do not need "true" random sequence.
template<class OutputIter, class U, class V, class Generator>
inline auto generate_random_data_n(
OutputIter it, size_t size, U min, V max, Generator& gen, size_t max_random_size = 1024 * 1024)
-> typename std::enable_if_t<rocprim::is_integral<it_value_t<OutputIter>>::value, OutputIter>
{
using T = it_value_t<OutputIter>;
using dis_type = typename std::conditional<
is_valid_for_int_distribution<T>::value,
T,
typename std::conditional<std::is_signed<T>::value,
int,
unsigned int>::type
>::type;
std::uniform_int_distribution<dis_type> distribution((T)min, (T)max);
std::generate_n(it, std::min(size, max_random_size), [&]() { return distribution(gen); });
for(size_t i = max_random_size; i < size; i += max_random_size)
{
std::copy_n(it, std::min(size - i, max_random_size), it + i);
}
return it + size;
}
template<class OutputIterator, class U, class V, class Generator>
inline auto generate_random_data_n(OutputIterator it,
size_t size,
U min,
V max,
Generator& gen,
size_t max_random_size = 1024 * 1024)
-> std::enable_if_t<rocprim::is_floating_point<it_value_t<OutputIterator>>::value,
OutputIterator>
{
using T = typename std::iterator_traits<OutputIterator>::value_type;
// Generate floats when T is half
using dis_type = std::conditional_t<std::is_same<rocprim::half, T>::value
|| std::is_same<rocprim::bfloat16, T>::value,
float,
T>;
std::uniform_real_distribution<dis_type> distribution((dis_type)min, (dis_type)max);
std::generate_n(it, std::min(size, max_random_size), [&]() { return distribution(gen); });
for(size_t i = max_random_size; i < size; i += max_random_size)
{
std::copy_n(it, std::min(size - i, max_random_size), it + i);
}
return it + size;
}
template<class T>
inline std::vector<T>
get_random_data01(size_t size, float p, unsigned int seed, size_t max_random_size = 1024 * 1024)
{
engine_type gen(seed);
std::bernoulli_distribution distribution(p);
std::vector<T> data(size);
std::generate(data.begin(),
data.begin() + std::min(size, max_random_size),
[&]() { return distribution(gen); });
for(size_t i = max_random_size; i < size; i += max_random_size)
{
std::copy_n(data.begin(), std::min(size - i, max_random_size), data.begin() + i);
}
return data;
}
template<class T, class U = T>
struct custom_type
{
using first_type = T;
using second_type = U;
T x;
U y;
ROCPRIM_HOST_DEVICE inline
custom_type(T xx = 0, U yy = 0) : x(xx), y(yy)
{
}
ROCPRIM_HOST_DEVICE inline
~custom_type() = default;
ROCPRIM_HOST_DEVICE inline
custom_type operator+(const custom_type& rhs) const
{
return custom_type(x + rhs.x, y + rhs.y);
}
ROCPRIM_HOST_DEVICE inline
bool operator<(const custom_type& rhs) const
{
// intentionally suboptimal choice for short-circuting,
// required to generate more performant device code
return ((x == rhs.x && y < rhs.y) || x < rhs.x);
}
ROCPRIM_HOST_DEVICE inline
bool operator==(const custom_type& rhs) const
{
return x == rhs.x && y == rhs.y;
}
ROCPRIM_HOST_DEVICE custom_type& operator+=(const custom_type& rhs)
{
this->x += rhs.x;
this->y += rhs.y;
return *this;
}
};
template<typename>
struct is_custom_type : std::false_type
{};
template<class T, class U>
struct is_custom_type<custom_type<T, U>> : std::true_type
{};
template<typename T, typename U>
struct is_comparable
{
private:
// A dummy template function that attempts to compare two objects of types T and U
template<typename V, typename W>
static auto test(V&& v, W&& w)
-> decltype(std::declval<V>() < std::declval<W>(), std::true_type{});
// Fallback if the above template function is not valid
template<typename, typename>
static std::false_type test(...);
public:
// Final result
static constexpr bool value = decltype(test<T, U>(std::declval<T>(), std::declval<U>()))::value;
};
template<typename T, typename U, typename V>
struct is_comparable<custom_type<U, V>, T>
: std::conditional_t<rocprim::is_arithmetic<T>::value
|| !std::is_same<T, custom_type<U, V>>::value,
std::false_type,
std::true_type>
{};
template<class CustomType>
struct custom_type_decomposer
{
static_assert(is_custom_type<CustomType>::value,
"custom_type_decomposer can only be used with instantiations of custom_type");
using T = typename CustomType::first_type;
using U = typename CustomType::second_type;
__host__ __device__ ::rocprim::tuple<T&, U&> operator()(CustomType& key) const
{
return ::rocprim::tuple<T&, U&>{key.x, key.y};
}
};
template<class T, class enable = void>
struct generate_limits;
template<class T>
struct generate_limits<T, std::enable_if_t<rocprim::is_integral<T>::value>>
{
static inline T min()
{
return rocprim::numeric_limits<T>::min();
}
static inline T max()
{
return rocprim::numeric_limits<T>::max();
}
};
template<class T>
struct generate_limits<T, std::enable_if_t<is_custom_type<T>::value>>
{
using F = typename T::first_type;
using S = typename T::second_type;
static inline T min()
{
return T(generate_limits<F>::min(), generate_limits<S>::min());
}
static inline T max()
{
return T(generate_limits<F>::max(), generate_limits<S>::max());
}
};
template<class T>
struct generate_limits<T, std::enable_if_t<rocprim::is_floating_point<T>::value>>
{
static inline T min()
{
return T(-1000);
}
static inline T max()
{
return T(1000);
}
};
template<class OutputIterator, class Generator>
inline auto generate_random_data_n(OutputIterator it,
size_t size,
it_value_t<OutputIterator> min,
it_value_t<OutputIterator> max,
Generator& gen,
size_t max_random_size = 1024 * 1024)
-> std::enable_if_t<is_custom_type<it_value_t<OutputIterator>>::value, OutputIterator>
{
using T = it_value_t<OutputIterator>;
using first_type = typename T::first_type;
using second_type = typename T::second_type;
std::vector<first_type> fdata(size);
std::vector<second_type> sdata(size);
generate_random_data_n(fdata.begin(), size, min.x, max.x, gen, max_random_size);
generate_random_data_n(sdata.begin(), size, min.y, max.y, gen, max_random_size);
for(size_t i = 0; i < size; i++)
{
it[i] = T(fdata[i], sdata[i]);
}
return it + size;
}
template<class OutputIterator, class Generator>
inline auto generate_random_data_n(OutputIterator it,
size_t size,
it_value_t<OutputIterator> min,
it_value_t<OutputIterator> max,
Generator& gen,
size_t max_random_size = 1024 * 1024)
-> std::enable_if_t<!is_custom_type<it_value_t<OutputIterator>>::value
&& !std::is_same<decltype(max.x), void>::value,
OutputIterator>
{
using T = it_value_t<OutputIterator>;
using field_type = decltype(max.x);
std::vector<field_type> field_data(size);
generate_random_data_n(field_data.begin(), size, min.x, max.x, gen, max_random_size);
for(size_t i = 0; i < size; i++)
{
it[i] = T(field_data[i]);
}
return it + size;
}
template<class T, class U, class V>
inline std::vector<T> get_random_data(
size_t size, U min, V max, unsigned int seed, size_t max_random_size = 1024 * 1024)
{
std::vector<T> data(size);
engine_type gen(seed);
generate_random_data_n(data.begin(), size, min, max, gen, max_random_size);
return data;
}
template<typename T, typename U>
auto limit_cast(U value) -> T
{
static_assert(rocprim::is_arithmetic<T>::value && rocprim::is_arithmetic<U>::value
&& is_comparable<T, U>::value,
"Cannot use limit_cast with chosen types of T and U");
using common_type = typename std::common_type<T, U>::type;
if(rocprim::is_unsigned<T>::value)
{
if(value < 0)
{
return rocprim::numeric_limits<T>::min();
}
if(static_cast<common_type>(value)
> static_cast<common_type>(rocprim::numeric_limits<T>::max()))
{
return rocprim::numeric_limits<T>::max();
}
}
else if(rocprim::is_signed<T>::value && rocprim::is_unsigned<U>::value)
{
if(value > rocprim::numeric_limits<T>::max())
{
return rocprim::numeric_limits<T>::max();
}
}
else if(rocprim::is_floating_point<T>::value)
{
return static_cast<T>(value);
}
else // Both T and U are signed
{
if(value < static_cast<common_type>(rocprim::numeric_limits<T>::min()))
{
return rocprim::numeric_limits<T>::min();
}
else if(value > static_cast<common_type>(rocprim::numeric_limits<T>::max()))
{
return rocprim::numeric_limits<T>::max();
}
}
return static_cast<T>(value);
}
// This overload below is selected for non-standard float types, e.g. half, which cannot be compared with the limit types.
template<class T, class U, class V>
inline auto limit_random_range(U range_start, V range_end)
-> std::enable_if_t<!is_custom_type<T>::value
&& (!is_comparable<T, U>::value || !is_comparable<T, V>::value),
std::pair<T, T>>
{
return {static_cast<T>(range_start), static_cast<T>(range_end)};
}
template<typename T, typename U, typename V>
auto limit_random_range(U range_start, V range_end)
-> std::enable_if_t<(is_custom_type<T>::value && is_comparable<typename T::first_type, U>::value
&& is_comparable<typename T::second_type, U>::value
&& is_comparable<typename T::first_type, V>::value
&& is_comparable<typename T::second_type, V>::value
&& rocprim::is_arithmetic<typename T::first_type>::value
&& rocprim::is_arithmetic<typename T::second_type>::value
&& rocprim::is_arithmetic<U>::value && rocprim::is_arithmetic<V>::value),
std::pair<T, T>>
{
return {
T{limit_cast<typename T::first_type>(range_start),
limit_cast<typename T::second_type>(range_start)},
T{ limit_cast<typename T::first_type>(range_end),
limit_cast<typename T::second_type>(range_end) }
};
}
template<class T, class U, class V>
inline auto limit_random_range(U range_start, V range_end)
-> std::enable_if_t<!is_custom_type<T>::value && is_comparable<T, U>::value
&& is_comparable<T, V>::value,
std::pair<T, T>>
{
if(is_comparable<V, U>::value)
{
using common_type = typename std::common_type<T, U>::type;
if(static_cast<common_type>(range_start) > static_cast<common_type>(range_end))
{
throw std::range_error("limit_random_range: Incorrect range used!");
}
}
T start = limit_cast<T>(range_start);
T end = limit_cast<T>(range_end);
return std::make_pair(start, end);
}
inline bool is_warp_size_supported(const unsigned int required_warp_size, const int device_id)
{
unsigned int warp_size;
HIP_CHECK(::rocprim::host_warp_size(device_id, warp_size));
return warp_size >= required_warp_size;
}
template<unsigned int LogicalWarpSize>
__device__ constexpr bool device_test_enabled_for_warp_size_v
= ::rocprim::arch::wavefront::min_size() >= LogicalWarpSize;
/// \brief Get segments of uniform random size in [1, max_segment_length] with random key.
template<typename T>
std::vector<T>
get_random_segments(const size_t size, const size_t max_segment_length, unsigned int seed)
{
static_assert(rocprim::is_arithmetic<T>::value, "Key type must be arithmetic");
engine_type prng(seed);
std::uniform_int_distribution<size_t> segment_length_distribution(
std::numeric_limits<size_t>::min(),
max_segment_length);
// std::uniform_real_distribution cannot handle rocprim::half, use float instead
using dis_type =
typename std::conditional<std::is_same<rocprim::half, T>::value, float, T>::type;
using key_distribution_type = std::conditional_t<rocprim::is_integral<T>::value,
std::uniform_int_distribution<dis_type>,
std::uniform_real_distribution<dis_type>>;
key_distribution_type key_distribution(rocprim::numeric_limits<T>::max());
std::vector<T> keys(size);
size_t keys_start_index = 0;
while(keys_start_index < size)
{
const size_t new_segment_length = segment_length_distribution(prng);
const size_t new_segment_end = std::min(size, keys_start_index + new_segment_length);
const T key = key_distribution(prng);
std::fill(keys.begin() + keys_start_index, keys.begin() + new_segment_end, key);
keys_start_index += new_segment_length;
}
return keys;
}
/// \brief Get segments of uniform random size in [1, max_segment_length] with unique incrementing key.
template<typename T>
std::vector<T>
get_random_segments_iota(const size_t size, const size_t max_segment_length, unsigned int seed)
{
engine_type prng(seed);
std::uniform_int_distribution<size_t> segment_length_distribution(1, max_segment_length);
std::vector<T> keys(size);
size_t segment_index = 0;
size_t keys_start_index = 0;
while(keys_start_index < size)
{
const size_t new_segment_length = segment_length_distribution(prng);
const size_t new_segment_end = std::min(size, keys_start_index + new_segment_length);
const T key = segment_index++;
std::fill(keys.begin() + keys_start_index, keys.begin() + new_segment_end, key);
keys_start_index += new_segment_length;
}
return keys;
}
template<class T, class U, class V>
inline auto get_random_value(U min, V max, size_t seed_value)
-> std::enable_if_t<rocprim::is_arithmetic<T>::value, T>
{
T result;
engine_type gen(seed_value);
generate_random_data_n(&result, 1, min, max, gen);
return result;
}
template<class T>
inline auto get_random_value(T min, T max, size_t seed_value)
-> std::enable_if_t<is_custom_type<T>::value, T>
{
typename T::first_type result_first;
typename T::second_type result_second;
engine_type gen(seed_value);
generate_random_data_n(&result_first, 1, min.x, max.x, gen);
generate_random_data_n(&result_second, 1, min.y, max.y, gen);
return T{result_first, result_second};
}
template <typename T, T, typename>
struct make_index_range_impl;
template <typename T, T Start, T... I>
struct make_index_range_impl<T, Start, std::integer_sequence<T, I...>>
{
using type = std::integer_sequence<T, (Start + I)...>;
};
// make a std::integer_sequence with values from Start to End inclusive
template <typename T, T Start, T End>
using make_index_range =
typename make_index_range_impl<T, Start, std::make_integer_sequence<T, End - Start + 1>>::type;
template<typename T, template<T> class Function, T... I, typename... Args>
void static_for_each_impl(std::integer_sequence<T, I...>, Args&&... args)
{
int a[] = {(Function<I>{}(std::forward<Args>(args)...), 0)...};
static_cast<void>(a);
}
// call the supplied template with all values of the std::integer_sequence Indices
template<typename Indices, template<typename Indices::value_type> class Function, typename... Args>
void static_for_each(Args&&... args)
{
static_for_each_impl<typename Indices::value_type, Function>(Indices{},
std::forward<Args>(args)...);
}
#define REGISTER_BENCHMARK(benchmarks, size, seed, stream, instance) \
benchmark::internal::Benchmark* benchmark = benchmark::RegisterBenchmark( \
instance.name().c_str(), \
[instance](benchmark::State& state, \
size_t _size, \
const managed_seed& _seed, \
hipStream_t _stream) { instance.run(state, _size, _seed, _stream); }, \
size, \
seed, \
stream); \
benchmarks.emplace_back(benchmark)
struct config_autotune_interface
{
virtual std::string name() const = 0;
virtual std::string sort_key() const
{
return name();
};
virtual ~config_autotune_interface() = default;
virtual void run(benchmark::State&, size_t, const managed_seed&, hipStream_t) const = 0;
};
struct config_autotune_register
{
static std::vector<std::unique_ptr<config_autotune_interface>>& vector() {
static std::vector<std::unique_ptr<config_autotune_interface>> storage;
return storage;
}
template <typename T>
static config_autotune_register create() {
vector().push_back(std::make_unique<T>());
return config_autotune_register();
}
template<typename BulkCreateFunction>
static config_autotune_register create_bulk(BulkCreateFunction&& f)
{
std::forward<BulkCreateFunction>(f)(vector());
return config_autotune_register();
}
// Register a subset of all created benchmarks for the current parallel instance and add to vector.
static void register_benchmark_subset(std::vector<benchmark::internal::Benchmark*>& benchmarks,
int parallel_instance_index,
int parallel_instance_count,
size_t size,
const managed_seed& seed,
hipStream_t stream)
{
std::vector<std::unique_ptr<config_autotune_interface>>& configs = vector();
// sorting to get a consistent order because order of initialization of static variables is undefined by the C++ standard.
std::sort(configs.begin(),
configs.end(),
[](const auto& l, const auto& r) { return l->sort_key() < r->sort_key(); });
size_t configs_per_instance
= (configs.size() + parallel_instance_count - 1) / parallel_instance_count;
size_t start = std::min(parallel_instance_index * configs_per_instance, configs.size());
size_t end = std::min((parallel_instance_index + 1) * configs_per_instance, configs.size());
for(size_t i = start; i < end; i++)
{
std::unique_ptr<config_autotune_interface>& uniq_ptr = configs.at(i);
config_autotune_interface* tuning_benchmark = uniq_ptr.get();
benchmark::internal::Benchmark* benchmark = benchmark::RegisterBenchmark(
tuning_benchmark->name().c_str(),
[tuning_benchmark](benchmark::State& state,
size_t size,
const managed_seed& seed,
hipStream_t stream)
{ tuning_benchmark->run(state, size, seed, stream); },
size,
seed,
stream);
benchmarks.emplace_back(benchmark);
}
}
};
// Inserts spaces at beginning of string if string shorter than specified length.
inline std::string pad_string(std::string str, const size_t len)
{
if(len > str.size())
{
str.insert(str.begin(), len - str.size(), ' ');
}
return str;
}
struct bench_naming
{
public:
enum format
{
json,
human,
txt
};
static format& get_format()
{
static format storage = human;
return storage;
}
static void set_format(const std::string& argument)
{
format result = human;
if(argument == "json")
{
result = json;
}
else if(argument == "txt")
{
result = txt;
}
get_format() = result;
}
private:
static std::string matches_as_json(std::sregex_iterator& matches)
{
std::stringstream result;
int brackets_count = 1;
result << "{";
bool insert_comma = false;
for(std::sregex_iterator i = matches; i != std::sregex_iterator(); ++i)
{
std::smatch m = *i;
if(insert_comma)
{
result << ",";
}
else
{
insert_comma = true;
}
result << "\"" << m[1].str() << "\":";
if(m[2].length() > 0)
{
if(m[2].str().find_first_not_of("0123456789") == std::string::npos)
{
result << m[2].str();
}
else
{
result << "\"" << m[2].str() << "\"";
}
if(m[3].length() > 0 && brackets_count > 0)
{
int n = std::min(brackets_count, static_cast<int>(m[3].length()));
brackets_count -= n;
for(int c = 0; c < n; c++)
{
result << "}";
}
}
}
else
{
brackets_count++;
result << "{";
insert_comma = false;
}
}
while(brackets_count > 0)
{
brackets_count--;
result << "}";
}
return result.str();
}
static std::string matches_as_human(std::sregex_iterator& matches)
{
std::stringstream result;
int brackets_count = 0;
bool insert_comma = false;
for(std::sregex_iterator i = matches; i != std::sregex_iterator(); ++i)
{
std::smatch m = *i;
if(insert_comma)
{
result << ",";
}
else
{
insert_comma = true;
}
if(m[2].length() > 0)
{
result << m[2].str();
if(m[3].length() > 0 && brackets_count > 0)
{
int n = std::min(brackets_count, static_cast<int>(m[3].length()));
brackets_count -= n;
for(int c = 0; c < n; c++)
{
result << ">";
}
}
}
else
{
brackets_count++;
result << "<";
insert_comma = false;
}
}
while(brackets_count > 0)
{
brackets_count--;
result << ">";
}
return result.str();
}
public:
static std::string format_name(std::string string)
{
format format = get_format();
std::regex r("([A-z0-9]*):\\s*((?:custom_type<[A-z0-9,]*>)|[A-z:\\(\\)\\.<>\\s0-9]*)(\\}*)");
// First we perform some checks
bool checks[4] = {false};
for(std::sregex_iterator i = std::sregex_iterator(string.begin(), string.end(), r);
i != std::sregex_iterator();
++i)
{
std::smatch m = *i;
if(m[1].str() == "lvl")
{
checks[0] = true;
}
else if(m[1].str() == "algo")
{
checks[1] = true;
}
else if(m[1].str() == "cfg")
{
checks[2] = true;
}
}
std::string string_substitute = std::regex_replace(string, r, "");
checks[3] = string_substitute.find_first_not_of(" ,{}") == std::string::npos;
for(bool check_name_format : checks)
{
if(!check_name_format)
{
std::cout << "Benchmark name \"" << string
<< "\" not in the correct format (e.g. "
"{lvl:block,algo:reduce,cfg:default_config} )"
<< std::endl;
exit(1);
}
}
// Now we generate the desired format
std::sregex_iterator matches = std::sregex_iterator(string.begin(), string.end(), r);
switch(format)
{
case format::json: return matches_as_json(matches);
case format::human: return matches_as_human(matches);
case format::txt: return string;
}
return string;
}
};
template <typename T>
struct Traits
{
//static inline method instead of static inline attribute because that's only supported from C++17 onwards
static inline const char* name(){
static_assert(sizeof(T) == 0, "Traits<T>::name() unknown");
return "unknown";
}
};
// Explicit definitions
template<>
inline const char* Traits<char>::name()
{
return "char";
}
template <>
inline const char* Traits<int>::name() { return "int"; }
template <>
inline const char* Traits<short>::name() { return "short"; }
template <>
inline const char* Traits<int8_t>::name() { return "int8_t"; }
template <>
inline const char* Traits<uint8_t>::name() { return "uint8_t"; }
template<>
inline const char* Traits<uint16_t>::name()
{
return "uint16_t";
}
template<>
inline const char* Traits<uint32_t>::name()
{
return "uint32_t";
}
template<>
inline const char* Traits<rocprim::half>::name()
{
return "rocprim::half";
}
template<>
inline const char* Traits<rocprim::bfloat16>::name()
{
return "rocprim::bfloat16";
}
template<>
inline const char* Traits<long long>::name()
{
return "int64_t";
}
// On MSVC `int64_t` and `long long` are the same, leading to multiple definition errors
#ifndef _WIN32
template <>
inline const char* Traits<int64_t>::name() { return "int64_t"; }
#endif
template <>
inline const char* Traits<float>::name() { return "float"; }
template <>
inline const char* Traits<double>::name() { return "double"; }
template<>
inline const char* Traits<custom_type<int, int>>::name()
{
return "custom_type<int,int>";
}
template<>
inline const char* Traits<custom_type<float, float>>::name()
{
return "custom_type<float,float>";
}
template<>
inline const char* Traits<custom_type<double, double>>::name()
{
return "custom_type<double,double>";
}
template<>
inline const char* Traits<custom_type<int, double>>::name()
{
return "custom_type<int,double>";
}
template<>
inline const char* Traits<custom_type<char, double>>::name()
{
return "custom_type<char,double>";
}
template<>
inline const char* Traits<custom_type<char, short>>::name()
{
return "custom_type<char,short>";
}
template<>
inline const char* Traits<custom_type<long, double>>::name()
{
return "custom_type<long,double>";
}
template<>
inline const char* Traits<custom_type<long long, double>>::name()
{
return "custom_type<int64_t,double>";
}
template<>
inline const char* Traits<custom_type<float, int16_t>>::name()
{
return "custom_type<float,int16_t>";
}
template<>
inline const char* Traits<rocprim::empty_type>::name()
{
return "empty_type";
}
template<>
inline const char* Traits<HIP_vector_type<float, 2>>::name()
{
return "float2";
}
template<>
inline const char* Traits<HIP_vector_type<double, 2>>::name()
{
return "double2";
}
inline void add_common_benchmark_info()
{
hipDeviceProp_t devProp;
int device_id = 0;
HIP_CHECK(hipGetDevice(&device_id));
HIP_CHECK(hipGetDeviceProperties(&devProp, device_id));
auto str = [](const std::string& name, const std::string& val) {
benchmark::AddCustomContext(name, val);
};
auto num = [](const std::string& name, const auto& value) {
benchmark::AddCustomContext(name, std::to_string(value));
};
auto dim2 = [num](const std::string& name, const auto* values) {
num(name + "_x", values[0]);
num(name + "_y", values[1]);
};
auto dim3 = [num, dim2](const std::string& name, const auto* values) {
dim2(name, values);
num(name + "_z", values[2]);
};
str("hdp_name", devProp.name);
num("hdp_total_global_mem", devProp.totalGlobalMem);
num("hdp_shared_mem_per_block", devProp.sharedMemPerBlock);
num("hdp_regs_per_block", devProp.regsPerBlock);
num("hdp_warp_size", devProp.warpSize);
num("hdp_max_threads_per_block", devProp.maxThreadsPerBlock);
dim3("hdp_max_threads_dim", devProp.maxThreadsDim);
dim3("hdp_max_grid_size", devProp.maxGridSize);
num("hdp_clock_rate", devProp.clockRate);
num("hdp_memory_clock_rate", devProp.memoryClockRate);
num("hdp_memory_bus_width", devProp.memoryBusWidth);
num("hdp_total_const_mem", devProp.totalConstMem);
num("hdp_major", devProp.major);
num("hdp_minor", devProp.minor);
num("hdp_multi_processor_count", devProp.multiProcessorCount);
num("hdp_l2_cache_size", devProp.l2CacheSize);
num("hdp_max_threads_per_multiprocessor", devProp.maxThreadsPerMultiProcessor);
num("hdp_compute_mode", devProp.computeMode);
num("hdp_clock_instruction_rate", devProp.clockInstructionRate);
num("hdp_concurrent_kernels", devProp.concurrentKernels);
num("hdp_pci_domain_id", devProp.pciDomainID);
num("hdp_pci_bus_id", devProp.pciBusID);
num("hdp_pci_device_id", devProp.pciDeviceID);
num("hdp_max_shared_memory_per_multi_processor", devProp.maxSharedMemoryPerMultiProcessor);
num("hdp_is_multi_gpu_board", devProp.isMultiGpuBoard);
num("hdp_can_map_host_memory", devProp.canMapHostMemory);
str("hdp_gcn_arch_name", devProp.gcnArchName);
num("hdp_integrated", devProp.integrated);
num("hdp_cooperative_launch", devProp.cooperativeLaunch);
num("hdp_cooperative_multi_device_launch", devProp.cooperativeMultiDeviceLaunch);
num("hdp_max_texture_1d_linear", devProp.maxTexture1DLinear);
num("hdp_max_texture_1d", devProp.maxTexture1D);
dim2("hdp_max_texture_2d", devProp.maxTexture2D);
dim3("hdp_max_texture_3d", devProp.maxTexture3D);
num("hdp_mem_pitch", devProp.memPitch);
num("hdp_texture_alignment", devProp.textureAlignment);
num("hdp_texture_pitch_alignment", devProp.texturePitchAlignment);
num("hdp_kernel_exec_timeout_enabled", devProp.kernelExecTimeoutEnabled);
num("hdp_ecc_enabled", devProp.ECCEnabled);
num("hdp_tcc_driver", devProp.tccDriver);
num("hdp_cooperative_multi_device_unmatched_func", devProp.cooperativeMultiDeviceUnmatchedFunc);
num("hdp_cooperative_multi_device_unmatched_grid_dim", devProp.cooperativeMultiDeviceUnmatchedGridDim);
num("hdp_cooperative_multi_device_unmatched_block_dim", devProp.cooperativeMultiDeviceUnmatchedBlockDim);
num("hdp_cooperative_multi_device_unmatched_shared_mem", devProp.cooperativeMultiDeviceUnmatchedSharedMem);
num("hdp_is_large_bar", devProp.isLargeBar);
num("hdp_asic_revision", devProp.asicRevision);
num("hdp_managed_memory", devProp.managedMemory);
num("hdp_direct_managed_mem_access_from_host", devProp.directManagedMemAccessFromHost);
num("hdp_concurrent_managed_access", devProp.concurrentManagedAccess);
num("hdp_pageable_memory_access", devProp.pageableMemoryAccess);
num("hdp_pageable_memory_access_uses_host_page_tables", devProp.pageableMemoryAccessUsesHostPageTables);
const auto arch = devProp.arch;
num("hdp_arch_has_global_int32_atomics", arch.hasGlobalInt32Atomics);
num("hdp_arch_has_global_float_atomic_exch", arch.hasGlobalFloatAtomicExch);
num("hdp_arch_has_shared_int32_atomics", arch.hasSharedInt32Atomics);
num("hdp_arch_has_shared_float_atomic_exch", arch.hasSharedFloatAtomicExch);
num("hdp_arch_has_float_atomic_add", arch.hasFloatAtomicAdd);
num("hdp_arch_has_global_int64_atomics", arch.hasGlobalInt64Atomics);
num("hdp_arch_has_shared_int64_atomics", arch.hasSharedInt64Atomics);
num("hdp_arch_has_doubles", arch.hasDoubles);
num("hdp_arch_has_warp_vote", arch.hasWarpVote);
num("hdp_arch_has_warp_ballot", arch.hasWarpBallot);
num("hdp_arch_has_warp_shuffle", arch.hasWarpShuffle);
num("hdp_arch_has_funnel_shift", arch.hasFunnelShift);
num("hdp_arch_has_thread_fence_system", arch.hasThreadFenceSystem);
num("hdp_arch_has_sync_threads_ext", arch.hasSyncThreadsExt);
num("hdp_arch_has_surface_funcs", arch.hasSurfaceFuncs);
num("hdp_arch_has_3d_grid", arch.has3dGrid);
num("hdp_arch_has_dynamic_parallelism", arch.hasDynamicParallelism);
}
inline const char* get_block_scan_algorithm_name(rocprim::block_scan_algorithm alg)
{
switch(alg)
{
case rocprim::block_scan_algorithm::using_warp_scan:
return "block_scan_algorithm::using_warp_scan";
case rocprim::block_scan_algorithm::reduce_then_scan:
return "block_scan_algorithm::reduce_then_scan";
// Not using `default: ...` because it kills effectiveness of -Wswitch
}
return "default_algorithm";
}
inline const char* get_block_load_method_name(rocprim::block_load_method method)
{
switch(method)
{
case rocprim::block_load_method::block_load_direct:
return "block_load_method::block_load_direct";
case rocprim::block_load_method::block_load_striped:
return "block_load_method::block_load_striped";
case rocprim::block_load_method::block_load_vectorize:
return "block_load_method::block_load_vectorize";
case rocprim::block_load_method::block_load_transpose:
return "block_load_method::block_load_transpose";
case rocprim::block_load_method::block_load_warp_transpose:
return "block_load_method::block_load_warp_transpose";
}
return "default_method";
}
template<std::size_t Size, std::size_t Alignment>
struct alignas(Alignment) custom_aligned_type
{
unsigned char data[Size];
};
template<typename Config>
std::string partition_config_name()
{
const rocprim::detail::partition_config_params config = Config();
return "{bs:" + std::to_string(config.kernel_config.block_size)
+ ",ipt:" + std::to_string(config.kernel_config.items_per_thread) + "}";
}
template<>
inline std::string partition_config_name<rocprim::default_config>()
{
return "default_config";
}
#endif // ROCPRIM_BENCHMARK_UTILS_HPP_
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