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// MIT License
//
// 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.
#include "benchmark_utils.hpp"
// CmdParser
#include "cmdparser.hpp"
// Google Benchmark
#include <benchmark/benchmark.h>
// HIP API
#include <hip/hip_runtime.h>
// rocPRIM
#include <rocprim/block/block_reduce.hpp>
#include <iostream>
#include <limits>
#include <string>
#include <vector>
#include <cstdio>
#include <cstdlib>
#ifndef DEFAULT_N
const size_t DEFAULT_BYTES = 1024 * 1024 * 32 * 4;
#endif
namespace rp = rocprim;
template<
class Runner,
class T,
unsigned int BlockSize,
unsigned int ItemsPerThread,
unsigned int Trials
>
__global__
__launch_bounds__(BlockSize)
void kernel(const T* input, T* output)
{
Runner::template run<T, BlockSize, ItemsPerThread, Trials>(input, output);
}
template<rocprim::block_reduce_algorithm algorithm>
struct reduce
{
template<
class T,
unsigned int BlockSize,
unsigned int ItemsPerThread,
unsigned int Trials
>
__device__
static void run(const T* input, T* output)
{
const unsigned int i = blockIdx.x * blockDim.x + threadIdx.x;
T values[ItemsPerThread];
T reduced_value;
for(unsigned int k = 0; k < ItemsPerThread; k++)
{
values[k] = input[i * ItemsPerThread + k];
}
using breduce_t = rp::block_reduce<T, BlockSize, algorithm>;
__shared__ typename breduce_t::storage_type storage;
ROCPRIM_NO_UNROLL
for(unsigned int trial = 0; trial < Trials; trial++)
{
breduce_t().reduce(values, reduced_value, storage);
values[0] = reduced_value;
}
if(threadIdx.x == 0)
{
output[blockIdx.x] = reduced_value;
}
}
};
template<
class Benchmark,
class T,
unsigned int BlockSize,
unsigned int ItemsPerThread,
unsigned int Trials = 100
>
void run_benchmark(benchmark::State& state, hipStream_t stream, size_t bytes)
{
// Calculate the number of elements N
size_t N = bytes / sizeof(T);
// Make sure size is a multiple of BlockSize
constexpr auto items_per_block = BlockSize * ItemsPerThread;
const auto size = items_per_block * ((N + items_per_block - 1)/items_per_block);
// Allocate and fill memory
std::vector<T> input(size, T(1));
T * d_input;
T * d_output;
HIP_CHECK(hipMalloc(reinterpret_cast<void**>(&d_input), size * sizeof(T)));
HIP_CHECK(hipMalloc(reinterpret_cast<void**>(&d_output), size * sizeof(T)));
HIP_CHECK(
hipMemcpy(
d_input, input.data(),
size * sizeof(T),
hipMemcpyHostToDevice
)
);
HIP_CHECK(hipDeviceSynchronize());
// HIP events creation
hipEvent_t start, stop;
HIP_CHECK(hipEventCreate(&start));
HIP_CHECK(hipEventCreate(&stop));
for (auto _ : state)
{
// Record start event
HIP_CHECK(hipEventRecord(start, stream));
hipLaunchKernelGGL(
HIP_KERNEL_NAME(kernel<Benchmark, T, BlockSize, ItemsPerThread, Trials>),
dim3(size/items_per_block), dim3(BlockSize), 0, stream,
d_input, d_output
);
HIP_CHECK(hipGetLastError());
// Record stop event and wait until it completes
HIP_CHECK(hipEventRecord(stop, stream));
HIP_CHECK(hipEventSynchronize(stop));
float elapsed_mseconds;
HIP_CHECK(hipEventElapsedTime(&elapsed_mseconds, start, stop));
state.SetIterationTime(elapsed_mseconds / 1000);
}
// Destroy HIP events
HIP_CHECK(hipEventDestroy(start));
HIP_CHECK(hipEventDestroy(stop));
state.SetBytesProcessed(state.iterations() * size * sizeof(T) * Trials);
state.SetItemsProcessed(state.iterations() * size * Trials);
HIP_CHECK(hipFree(d_input));
HIP_CHECK(hipFree(d_output));
}
// IPT - items per thread
#define CREATE_BENCHMARK(T, BS, IPT) \
benchmark::RegisterBenchmark(bench_naming::format_name("{lvl:block,algo:reduce,key_type:" #T \
",cfg:{bs:" #BS ",ipt:" #IPT ",method:" \
+ method_name + "}}") \
.c_str(), \
run_benchmark<Benchmark, T, BS, IPT>, \
stream, \
bytes)
#define BENCHMARK_TYPE(type, block) \
CREATE_BENCHMARK(type, block, 1), \
CREATE_BENCHMARK(type, block, 2), \
CREATE_BENCHMARK(type, block, 3), \
CREATE_BENCHMARK(type, block, 4), \
CREATE_BENCHMARK(type, block, 8), \
CREATE_BENCHMARK(type, block, 11), \
CREATE_BENCHMARK(type, block, 16)
template<class Benchmark>
void add_benchmarks(std::vector<benchmark::internal::Benchmark*>& benchmarks,
const std::string& method_name,
hipStream_t stream,
size_t bytes)
{
using custom_float2 = custom_type<float, float>;
using custom_double2 = custom_type<double, double>;
std::vector<benchmark::internal::Benchmark*> new_benchmarks =
{
// When block size is less than or equal to warp size
BENCHMARK_TYPE(int, 64),
BENCHMARK_TYPE(float, 64),
BENCHMARK_TYPE(double, 64),
BENCHMARK_TYPE(int8_t, 64),
BENCHMARK_TYPE(uint8_t, 64),
BENCHMARK_TYPE(rocprim::half, 64),
BENCHMARK_TYPE(int, 256),
BENCHMARK_TYPE(float, 256),
BENCHMARK_TYPE(double, 256),
BENCHMARK_TYPE(int8_t, 256),
BENCHMARK_TYPE(uint8_t, 256),
BENCHMARK_TYPE(rocprim::half, 256),
CREATE_BENCHMARK(custom_float2, 256, 1),
CREATE_BENCHMARK(custom_float2, 256, 4),
CREATE_BENCHMARK(custom_float2, 256, 8),
CREATE_BENCHMARK(float2, 256, 1),
CREATE_BENCHMARK(float2, 256, 4),
CREATE_BENCHMARK(float2, 256, 8),
CREATE_BENCHMARK(custom_double2, 256, 1),
CREATE_BENCHMARK(custom_double2, 256, 4),
CREATE_BENCHMARK(custom_double2, 256, 8),
CREATE_BENCHMARK(double2, 256, 1),
CREATE_BENCHMARK(double2, 256, 4),
CREATE_BENCHMARK(double2, 256, 8),
CREATE_BENCHMARK(float4, 256, 1),
CREATE_BENCHMARK(float4, 256, 4),
CREATE_BENCHMARK(float4, 256, 8),
};
benchmarks.insert(benchmarks.end(), new_benchmarks.begin(), new_benchmarks.end());
}
int main(int argc, char *argv[])
{
cli::Parser parser(argc, argv);
parser.set_optional<size_t>("size", "size", DEFAULT_BYTES, "number of bytes");
parser.set_optional<int>("trials", "trials", -1, "number of iterations");
parser.set_optional<std::string>("name_format",
"name_format",
"human",
"either: json,human,txt");
parser.run_and_exit_if_error();
// Parse argv
benchmark::Initialize(&argc, argv);
const size_t bytes = parser.get<size_t>("size");
const int trials = parser.get<int>("trials");
bench_naming::set_format(parser.get<std::string>("name_format"));
// HIP
hipStream_t stream = 0; // default
// Benchmark info
add_common_benchmark_info();
benchmark::AddCustomContext("bytes", std::to_string(bytes));
// Add benchmarks
std::vector<benchmark::internal::Benchmark*> benchmarks;
// using_warp_scan
using reduce_uwr_t = reduce<rocprim::block_reduce_algorithm::using_warp_reduce>;
add_benchmarks<reduce_uwr_t>(benchmarks, "using_warp_reduce", stream, bytes);
// reduce then scan
using reduce_rr_t = reduce<rocprim::block_reduce_algorithm::raking_reduce>;
add_benchmarks<reduce_rr_t>(benchmarks, "raking_reduce", stream, bytes);
// reduce commutative only
using reduce_rrco_t = reduce<rocprim::block_reduce_algorithm::raking_reduce_commutative_only>;
add_benchmarks<reduce_rrco_t>(benchmarks, "raking_reduce_commutative_only", stream, bytes);
// 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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