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// MIT License
//
// Copyright (c) 2020 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.
// CUB's implementation of single_pass_scan_operators has maybe uninitialized
// parameters, disable the warning because all warnings are threated as errors:
#ifdef __HIP_PLATFORM_NVIDIA__
#pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
#include "common_benchmark_header.hpp"
// HIP API
#include "hipcub/device/device_reduce.hpp"
#ifndef DEFAULT_N
const size_t DEFAULT_N = 1024 * 1024 * 32;
#endif
const unsigned int batch_size = 10;
const unsigned int warmup_size = 5;
template<class Key, class Value, class BinaryFunction>
void run_benchmark(benchmark::State& state,
size_t max_length,
hipStream_t stream,
size_t size,
BinaryFunction reduce_op)
{
using key_type = Key;
using value_type = Value;
// Generate data
std::vector<key_type> keys_input(size);
unsigned int unique_count = 0;
std::vector<size_t> key_counts
= benchmark_utils::get_random_data<size_t>(100000, 1, max_length);
size_t offset = 0;
while(offset < size)
{
const size_t key_count = key_counts[unique_count % key_counts.size()];
const size_t end = std::min(size, offset + key_count);
for(size_t i = offset; i < end; i++)
{
keys_input[i] = unique_count;
}
unique_count++;
offset += key_count;
}
std::vector<value_type> values_input(size);
std::iota(values_input.begin(), values_input.end(), 0);
key_type* d_keys_input;
HIP_CHECK(hipMalloc(&d_keys_input, size * sizeof(key_type)));
HIP_CHECK(
hipMemcpy(d_keys_input, keys_input.data(), size * sizeof(key_type), hipMemcpyHostToDevice));
value_type* d_values_input;
HIP_CHECK(hipMalloc(&d_values_input, size * sizeof(value_type)));
HIP_CHECK(hipMemcpy(d_values_input,
values_input.data(),
size * sizeof(value_type),
hipMemcpyHostToDevice));
key_type* d_unique_output;
value_type* d_aggregates_output;
unsigned int* d_unique_count_output;
HIP_CHECK(hipMalloc(&d_unique_output, unique_count * sizeof(key_type)));
HIP_CHECK(hipMalloc(&d_aggregates_output, unique_count * sizeof(value_type)));
HIP_CHECK(hipMalloc(&d_unique_count_output, sizeof(unsigned int)));
void* d_temporary_storage = nullptr;
size_t temporary_storage_bytes = 0;
HIP_CHECK(hipcub::DeviceReduce::ReduceByKey(nullptr,
temporary_storage_bytes,
d_keys_input,
d_unique_output,
d_values_input,
d_aggregates_output,
d_unique_count_output,
reduce_op,
size,
stream));
HIP_CHECK(hipMalloc(&d_temporary_storage, temporary_storage_bytes));
HIP_CHECK(hipDeviceSynchronize());
// Warm-up
for(size_t i = 0; i < warmup_size; i++)
{
HIP_CHECK(hipcub::DeviceReduce::ReduceByKey(d_temporary_storage,
temporary_storage_bytes,
d_keys_input,
d_unique_output,
d_values_input,
d_aggregates_output,
d_unique_count_output,
reduce_op,
size,
stream));
}
HIP_CHECK(hipDeviceSynchronize());
for(auto _ : state)
{
auto start = std::chrono::high_resolution_clock::now();
for(size_t i = 0; i < batch_size; i++)
{
HIP_CHECK(hipcub::DeviceReduce::ReduceByKey(d_temporary_storage,
temporary_storage_bytes,
d_keys_input,
d_unique_output,
d_values_input,
d_aggregates_output,
d_unique_count_output,
reduce_op,
size,
stream));
}
HIP_CHECK(hipStreamSynchronize(stream));
auto end = std::chrono::high_resolution_clock::now();
auto elapsed_seconds
= std::chrono::duration_cast<std::chrono::duration<double>>(end - start);
state.SetIterationTime(elapsed_seconds.count());
}
state.SetBytesProcessed(state.iterations() * batch_size * size
* (sizeof(key_type) + sizeof(value_type)));
state.SetItemsProcessed(state.iterations() * batch_size * size);
HIP_CHECK(hipFree(d_temporary_storage));
HIP_CHECK(hipFree(d_keys_input));
HIP_CHECK(hipFree(d_values_input));
HIP_CHECK(hipFree(d_unique_output));
HIP_CHECK(hipFree(d_aggregates_output));
HIP_CHECK(hipFree(d_unique_count_output));
}
#define CREATE_BENCHMARK(Key, Value, REDUCE_OP) \
benchmark::RegisterBenchmark(std::string("device_reduce_by_key" \
"<key_data_type:" #Key ",value_data_type:" #Value \
",reduce_op:" #REDUCE_OP ">." \
"(random_number_range:[1, " \
+ std::to_string(max_length) + "])") \
.c_str(), \
&run_benchmark<Key, Value, REDUCE_OP>, \
max_length, \
stream, \
size, \
REDUCE_OP())
#define CREATE_BENCHMARKS(REDUCE_OP) \
CREATE_BENCHMARK(int, float, REDUCE_OP), CREATE_BENCHMARK(int, double, REDUCE_OP), \
CREATE_BENCHMARK(int, custom_double2, REDUCE_OP), \
CREATE_BENCHMARK(int8_t, int8_t, REDUCE_OP), \
CREATE_BENCHMARK(long long, float, REDUCE_OP), \
CREATE_BENCHMARK(long long, double, REDUCE_OP)
void add_benchmarks(size_t max_length,
std::vector<benchmark::internal::Benchmark*>& benchmarks,
hipStream_t stream,
size_t size)
{
using custom_double2 = benchmark_utils::custom_type<double, double>;
std::vector<benchmark::internal::Benchmark*> bs = {
CREATE_BENCHMARKS(hipcub::Sum),
CREATE_BENCHMARK(long long, custom_double2, hipcub::Sum),
CREATE_BENCHMARKS(hipcub::Min),
#ifdef HIPCUB_ROCPRIM_API
CREATE_BENCHMARK(long long, custom_double2, hipcub::Min),
#endif
};
benchmarks.insert(benchmarks.end(), bs.begin(), bs.end());
}
int main(int argc, char* argv[])
{
cli::Parser parser(argc, argv);
parser.set_optional<size_t>("size", "size", DEFAULT_N, "number of values");
parser.set_optional<int>("trials", "trials", -1, "number of iterations");
parser.run_and_exit_if_error();
// Parse argv
benchmark::Initialize(&argc, argv);
const size_t size = parser.get<size_t>("size");
const int trials = parser.get<int>("trials");
std::cout << "benchmark_device_reduce_by_key" << std::endl;
// HIP
hipStream_t stream = 0; // default
hipDeviceProp_t devProp;
int device_id = 0;
HIP_CHECK(hipGetDevice(&device_id));
HIP_CHECK(hipGetDeviceProperties(&devProp, device_id));
std::cout << "[HIP] Device name: " << devProp.name << std::endl;
// Add benchmarks
std::vector<benchmark::internal::Benchmark*> benchmarks;
add_benchmarks(1000, benchmarks, stream, size);
add_benchmarks(10, benchmarks, stream, size);
// Use manual timing
for(auto& b : benchmarks)
{
b->UseManualTime();
b->Unit(benchmark::kMillisecond);
}
// Force number of iterations
if(trials > 0)
{
for(auto& b : benchmarks)
{
b->Iterations(trials);
}
}
// Run benchmarks
benchmark::RunSpecifiedBenchmarks();
return 0;
}
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