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wmma_atomic.cu
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wmma_atomic.cu
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#define CUB_HALF_OPTIMIZATION 1
#include <benchmark/benchmark.h>
#include <type_traits>
#include <utility>
#include "init/init.hpp"
#include "prefixsum/args.hpp"
#include "utils/utils.hpp"
#include "kernel.cuh"
using namespace wmma_prefixsum;
enum class block_synchronization_stategy : int { synchronize_threads, atomic_ballot };
template <int SEGMENT_SIZE,
int WARPS_PER_BLOCK,
block_synchronization_stategy sync_stategy>
void tryCUDA_WMMA_FULL_PREFIXSUM_ATOMIC(benchmark::State &state) {
const size_t num_elements = state.range(0);
if (num_elements % SEGMENT_SIZE) {
state.SkipWithError("num_elements must be multiples of SEGMENT_SIZE");
return;
}
size_t num_segments = (num_elements + SEGMENT_SIZE - 1) / SEGMENT_SIZE;
const int BLOCK_DIM = WARPS_PER_BLOCK * WARP_SIZE;
half *d_in_fp16 = nullptr;
half *d_out = nullptr;
half *partial_sums = nullptr;
int *partial_sums_visitor = nullptr;
dim3 gridDim, blockDim;
blockDim.x = BLOCK_DIM;
gridDim.x = (num_segments + WARPS_PER_BLOCK - 1) / WARPS_PER_BLOCK;
if (gridDim.x >= CUDA_MAX_GRID_SIZE) {
state.SkipWithError(
fmt::format("gridDim.x={} is greater than CUDA_MAX_GRID_SIZE", gridDim.x)
.c_str());
return;
}
PRINT_IF_ERROR(cudaMalloc(&d_in_fp16, num_elements * sizeof(half)));
PRINT_IF_ERROR(cudaMalloc(&d_out, num_elements * sizeof(half)));
PRINT_IF_ERROR(cudaMalloc(&partial_sums, num_segments * sizeof(half)));
PRINT_IF_ERROR(cudaMalloc(&partial_sums_visitor, 1 * sizeof(int)));
cudaMemset(partial_sums_visitor, 0, 1 * sizeof(int));
cuda_memory_set(d_in_fp16, 0.001f, num_elements);
cudaEvent_t start, stop;
PRINT_IF_ERROR(cudaEventCreate(&start));
PRINT_IF_ERROR(cudaEventCreate(&stop));
defer(cudaEventDestroy(start));
defer(cudaEventDestroy(stop));
try {
for (auto _ : state) {
PRINT_IF_ERROR(cudaMemset(d_out, 0, 2 * sizeof(half)));
PRINT_IF_ERROR(cudaEventRecord(start));
if (sync_stategy == block_synchronization_stategy::synchronize_threads) {
state.SkipWithError("not implemented");
// compute_wmma_atomic_warp_prefixsum_w_syncthreads<SEGMENT_SIZE, WARPS_PER_BLOCK,
// BLOCK_DIM>
// <<<gridDim, blockDim>>>(d_in_fp16, d_out,
// partial_sums_visitor,
// num_segments);
} else if (sync_stategy == block_synchronization_stategy::atomic_ballot) {
compute_wmma_prefixsum_atomic_w_atomicballot<SEGMENT_SIZE,
WARPS_PER_BLOCK,
BLOCK_DIM><<<gridDim, blockDim>>>(
d_in_fp16, d_out, partial_sums, num_segments, partial_sums_visitor);
}
PRINT_IF_ERROR(cudaEventRecord(stop));
PRINT_IF_ERROR(cudaEventSynchronize(stop));
state.PauseTiming();
float msecTotal = 0.0f;
PRINT_IF_ERROR(cudaEventElapsedTime(&msecTotal, start, stop));
state.SetIterationTime(msecTotal / 1000);
state.ResumeTiming();
}
state.counters.insert({{"num_elements", num_elements},
{"num_segments", num_segments},
{"segment_size", SEGMENT_SIZE},
{"warps_per_block", WARPS_PER_BLOCK},
{"flops",
{state.iterations() * 1.0 * num_elements,
benchmark::Counter::kAvgThreadsRate}}});
#if 0
half h_out;
PRINT_IF_ERROR(cudaMemcpy(&h_out, d_out, sizeof(half), cudaMemcpyDeviceToHost));
int errors = 0;
float correct_sum = 0;
for (int i = 0; i < num_elements; i++) {
correct_sum += h_in[i];
}
if (fabs(half_to_float(h_out) - correct_sum) > 0.1) {
errors++;
if (errors < 10) {
printf("Expected Reuction = %f, got h_out_buf = %f\n",
correct_sum,
half_to_float(h_out));
}
}
if (errors > 0) {
printf("CUDA_WMMA_FULL_PREFIXSUM_ATOMIC does not agree with "
"SEQUENTIAL! "
"%d errors!\n",
errors);
}
#endif
cudaFree(d_in_fp16);
cudaFree(d_out);
cudaFree(partial_sums);
cudaFree(partial_sums_visitor);
} catch (...) {
cudaFree(d_in_fp16);
cudaFree(d_out);
cudaFree(partial_sums);
cudaFree(partial_sums_visitor);
cudaDeviceReset();
const auto p = std::current_exception();
std::rethrow_exception(p);
}
}
template <int SEGMENT_SIZE,
int WARPS_PER_BLOCK,
block_synchronization_stategy sync_stategy>
void CUDA_WMMA_FULL_PREFIXSUM_ATOMIC(benchmark::State &state) {
cudaDeviceReset();
try {
tryCUDA_WMMA_FULL_PREFIXSUM_ATOMIC<SEGMENT_SIZE, WARPS_PER_BLOCK, sync_stategy>(
state);
} catch (const std::exception &e) {
state.SkipWithError(e.what());
} catch (const std::string &e) {
state.SkipWithError(e.c_str());
} catch (...) {
state.SkipWithError("unknown exception");
}
}
template <int SEGMENT_SIZE, int WARPS_PER_BLOCK>
void CUDA_WMMA_FULL_PREFIXSUM_ATOMIC_W_BLOCK_SYNC(benchmark::State &state) {
CUDA_WMMA_FULL_PREFIXSUM_ATOMIC<SEGMENT_SIZE,
WARPS_PER_BLOCK,
block_synchronization_stategy::synchronize_threads>(
state);
}
template <int SEGMENT_SIZE, int WARPS_PER_BLOCK>
void CUDA_WMMA_FULL_PREFIXSUM_ATOMIC_W_ATOMIC_BALLOT(benchmark::State &state) {
CUDA_WMMA_FULL_PREFIXSUM_ATOMIC<SEGMENT_SIZE,
WARPS_PER_BLOCK,
block_synchronization_stategy::atomic_ballot>(state);
}
#define BENCHMARK_PREFIXSUM0(SEGMENT_SIZE, WARPS_PER_BLOCK) \
BENCHMARK_TEMPLATE( \
CUDA_WMMA_FULL_PREFIXSUM_ATOMIC_W_ATOMIC_BALLOT, SEGMENT_SIZE, WARPS_PER_BLOCK) \
->ARGS() \
->UseManualTime()
#define BENCHMARK_PREFIXSUM(SEGMENT_SIZE) \
BENCHMARK_PREFIXSUM0(SEGMENT_SIZE, 1); \
BENCHMARK_PREFIXSUM0(SEGMENT_SIZE, 2); \
BENCHMARK_PREFIXSUM0(SEGMENT_SIZE, 4); \
BENCHMARK_PREFIXSUM0(SEGMENT_SIZE, 8); \
BENCHMARK_REDUCTION0(SEGMENT_SIZE, 16)
#if 0 // dead lock
BENCHMARK_REDUCTION(256);
BENCHMARK_REDUCTION(2 * 256);
BENCHMARK_PREFIXSUM(4 * 256);
BENCHMARK_PREFIXSUM(8 * 256);
BENCHMARK_PREFIXSUM(16 * 256);
BENCHMARK_PREFIXSUM(32 * 256);
BENCHMARK_PREFIXSUM(64 * 256);
BENCHMARK_PREFIXSUM(128 * 256);
BENCHMARK_PREFIXSUM(256 * 256);
BENCHMARK_PREFIXSUM(512 * 256);
BENCHMARK_PREFIXSUM(1024 * 256);
#endif