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/* | ||
* Copyright (c) 2022-2024, NVIDIA CORPORATION. | ||
* | ||
* Licensed under the Apache License, Version 2.0 (the "License"); | ||
* you may not use this file except in compliance with the License. | ||
* You may obtain a copy of the License at | ||
* | ||
* http://www.apache.org/licenses/LICENSE-2.0 | ||
* | ||
* Unless required by applicable law or agreed to in writing, software | ||
* distributed under the License is distributed on an "AS IS" BASIS, | ||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
* See the License for the specific language governing permissions and | ||
* limitations under the License. | ||
*/ | ||
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#include <common/benchmark.hpp> | ||
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#include <raft/core/device_resources.hpp> | ||
#include <raft/core/nvtx.hpp> | ||
#include <raft/matrix/detail/select_radix.cuh> | ||
#include <raft/matrix/detail/select_warpsort.cuh> | ||
#include <raft/matrix/select_k.cuh> | ||
#include <raft/random/rng.cuh> | ||
#include <raft/sparse/detail/utils.h> | ||
#include <raft/util/cudart_utils.hpp> | ||
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#include <raft_internal/matrix/select_k.cuh> | ||
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#include <rmm/device_uvector.hpp> | ||
#include <rmm/mr/device/per_device_resource.hpp> | ||
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#include <cstdint> | ||
#include <cstring> | ||
#include <type_traits> | ||
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namespace raft::matrix { | ||
using namespace raft::bench; // NOLINT | ||
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template <typename KeyT> | ||
struct replace_with_mask { | ||
KeyT replacement; | ||
int64_t line_length; | ||
int64_t spared_inputs; | ||
constexpr auto inline operator()(int64_t offset, KeyT x, uint8_t mask) -> KeyT | ||
{ | ||
auto i = offset % line_length; | ||
// don't replace all the inputs, spare a few elements at the beginning of the input | ||
return (mask && i >= spared_inputs) ? replacement : x; | ||
} | ||
}; | ||
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template <typename KeyT, typename IdxT, SelectAlgo Algo> | ||
struct selection : public fixture { | ||
explicit selection(const select::params& p) | ||
: fixture(p.use_memory_pool), | ||
params_(p), | ||
in_dists_(p.batch_size * p.len, stream), | ||
in_ids_(p.batch_size * p.len, stream), | ||
out_dists_(p.batch_size * p.k, stream), | ||
out_ids_(p.batch_size * p.k, stream) | ||
{ | ||
raft::sparse::iota_fill(in_ids_.data(), IdxT(p.batch_size), IdxT(p.len), stream); | ||
raft::random::RngState state{42}; | ||
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KeyT min_value = -1.0; | ||
KeyT max_value = 1.0; | ||
if (p.use_same_leading_bits) { | ||
if constexpr (std::is_same_v<KeyT, float>) { | ||
uint32_t min_bits = 0x3F800000; // 1.0 | ||
uint32_t max_bits = 0x3F8000FF; // 1.00003 | ||
memcpy(&min_value, &min_bits, sizeof(KeyT)); | ||
memcpy(&max_value, &max_bits, sizeof(KeyT)); | ||
} else if constexpr (std::is_same_v<KeyT, double>) { | ||
uint64_t min_bits = 0x3FF0000000000000; // 1.0 | ||
uint64_t max_bits = 0x3FF0000FFFFFFFFF; // 1.000015 | ||
memcpy(&min_value, &min_bits, sizeof(KeyT)); | ||
memcpy(&max_value, &max_bits, sizeof(KeyT)); | ||
} | ||
} | ||
raft::random::uniform(handle, state, in_dists_.data(), in_dists_.size(), min_value, max_value); | ||
if (p.frac_infinities > 0.0) { | ||
rmm::device_uvector<uint8_t> mask_buf(p.batch_size * p.len, stream); | ||
auto mask = make_device_vector_view<uint8_t, size_t>(mask_buf.data(), mask_buf.size()); | ||
raft::random::bernoulli(handle, state, mask, p.frac_infinities); | ||
KeyT bound = p.select_min ? raft::upper_bound<KeyT>() : raft::lower_bound<KeyT>(); | ||
auto mask_in = | ||
make_device_vector_view<const uint8_t, size_t>(mask_buf.data(), mask_buf.size()); | ||
auto dists_in = make_device_vector_view<const KeyT>(in_dists_.data(), in_dists_.size()); | ||
auto dists_out = make_device_vector_view<KeyT>(in_dists_.data(), in_dists_.size()); | ||
raft::linalg::map_offset(handle, | ||
dists_out, | ||
replace_with_mask<KeyT>{bound, int64_t(p.len), int64_t(p.k / 2)}, | ||
dists_in, | ||
mask_in); | ||
} | ||
} | ||
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void run_benchmark(::benchmark::State& state) override // NOLINT | ||
{ | ||
try { | ||
std::ostringstream label_stream; | ||
label_stream << params_.batch_size << "#" << params_.len << "#" << params_.k; | ||
if (params_.use_same_leading_bits) { label_stream << "#same-leading-bits"; } | ||
if (params_.frac_infinities > 0) { label_stream << "#infs-" << params_.frac_infinities; } | ||
state.SetLabel(label_stream.str()); | ||
common::nvtx::range case_scope("%s - %s", state.name().c_str(), label_stream.str().c_str()); | ||
int iter = 0; | ||
loop_on_state(state, [&iter, this]() { | ||
common::nvtx::range lap_scope("lap-", iter++); | ||
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std::optional<raft::device_matrix_view<const IdxT, int64_t, row_major>> in_ids_view; | ||
if (params_.use_index_input) { | ||
in_ids_view = raft::make_device_matrix_view<const IdxT, int64_t>( | ||
in_ids_.data(), params_.batch_size, params_.len); | ||
} | ||
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matrix::select_k<KeyT, IdxT>(handle, | ||
raft::make_device_matrix_view<const KeyT, int64_t>( | ||
in_dists_.data(), params_.batch_size, params_.len), | ||
in_ids_view, | ||
raft::make_device_matrix_view<KeyT, int64_t>( | ||
out_dists_.data(), params_.batch_size, params_.k), | ||
raft::make_device_matrix_view<IdxT, int64_t>( | ||
out_ids_.data(), params_.batch_size, params_.k), | ||
params_.select_min, | ||
false, | ||
Algo); | ||
}); | ||
} catch (raft::exception& e) { | ||
state.SkipWithError(e.what()); | ||
} | ||
} | ||
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private: | ||
const select::params params_; | ||
rmm::device_uvector<KeyT> in_dists_, out_dists_; | ||
rmm::device_uvector<IdxT> in_ids_, out_ids_; | ||
}; | ||
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const std::vector<select::params> kInputs{ | ||
{20000, 500, 1, true}, | ||
{20000, 500, 2, true}, | ||
{20000, 500, 4, true}, | ||
{20000, 500, 8, true}, | ||
{20000, 500, 16, true}, | ||
{20000, 500, 32, true}, | ||
{20000, 500, 64, true}, | ||
{20000, 500, 128, true}, | ||
{20000, 500, 256, true}, | ||
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{1000, 10000, 1, true}, | ||
{1000, 10000, 2, true}, | ||
{1000, 10000, 4, true}, | ||
{1000, 10000, 8, true}, | ||
{1000, 10000, 16, true}, | ||
{1000, 10000, 32, true}, | ||
{1000, 10000, 64, true}, | ||
{1000, 10000, 128, true}, | ||
{1000, 10000, 256, true}, | ||
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{100, 100000, 1, true}, | ||
{100, 100000, 2, true}, | ||
{100, 100000, 4, true}, | ||
{100, 100000, 8, true}, | ||
{100, 100000, 16, true}, | ||
{100, 100000, 32, true}, | ||
{100, 100000, 64, true}, | ||
{100, 100000, 128, true}, | ||
{100, 100000, 256, true}, | ||
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{10, 1000000, 1, true}, | ||
{10, 1000000, 2, true}, | ||
{10, 1000000, 4, true}, | ||
{10, 1000000, 8, true}, | ||
{10, 1000000, 16, true}, | ||
{10, 1000000, 32, true}, | ||
{10, 1000000, 64, true}, | ||
{10, 1000000, 128, true}, | ||
{10, 1000000, 256, true}, | ||
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{10, 1000000, 1, true, false, true}, | ||
{10, 1000000, 2, true, false, true}, | ||
{10, 1000000, 4, true, false, true}, | ||
{10, 1000000, 8, true, false, true}, | ||
{10, 1000000, 16, true, false, true}, | ||
{10, 1000000, 32, true, false, true}, | ||
{10, 1000000, 64, true, false, true}, | ||
{10, 1000000, 128, true, false, true}, | ||
{10, 1000000, 256, true, false, true}, | ||
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{10, 1000000, 1, true, false, false, true, 0.1}, | ||
{10, 1000000, 16, true, false, false, true, 0.1}, | ||
{10, 1000000, 64, true, false, false, true, 0.1}, | ||
{10, 1000000, 128, true, false, false, true, 0.1}, | ||
{10, 1000000, 256, true, false, false, true, 0.1}, | ||
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{10, 1000000, 1, true, false, false, true, 0.9}, | ||
{10, 1000000, 16, true, false, false, true, 0.9}, | ||
{10, 1000000, 64, true, false, false, true, 0.9}, | ||
{10, 1000000, 128, true, false, false, true, 0.9}, | ||
{10, 1000000, 256, true, false, false, true, 0.9}, | ||
{1000, 10000, 1, true, false, false, true, 0.9}, | ||
{1000, 10000, 16, true, false, false, true, 0.9}, | ||
{1000, 10000, 64, true, false, false, true, 0.9}, | ||
{1000, 10000, 128, true, false, false, true, 0.9}, | ||
{1000, 10000, 256, true, false, false, true, 0.9}, | ||
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{10, 1000000, 1, true, false, false, true, 1.0}, | ||
{10, 1000000, 16, true, false, false, true, 1.0}, | ||
{10, 1000000, 64, true, false, false, true, 1.0}, | ||
{10, 1000000, 128, true, false, false, true, 1.0}, | ||
{10, 1000000, 256, true, false, false, true, 1.0}, | ||
{1000, 10000, 1, true, false, false, true, 1.0}, | ||
{1000, 10000, 16, true, false, false, true, 1.0}, | ||
{1000, 10000, 64, true, false, false, true, 1.0}, | ||
{1000, 10000, 128, true, false, false, true, 1.0}, | ||
{1000, 10000, 256, true, false, false, true, 1.0}, | ||
{1000, 10000, 256, true, false, false, true, 0.999}, | ||
}; | ||
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#define SELECTION_REGISTER(KeyT, IdxT, A) \ | ||
namespace BENCHMARK_PRIVATE_NAME(selection) { \ | ||
using SelectK = selection<KeyT, IdxT, raft::matrix::SelectAlgo::A>; \ | ||
RAFT_BENCH_REGISTER(SelectK, #KeyT "/" #IdxT "/" #A, kInputs); \ | ||
} | ||
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SELECTION_REGISTER(float, uint32_t, kAuto); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kRadix8bits); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kRadix11bits); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kRadix11bitsExtraPass); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kWarpAuto); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kWarpImmediate); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kWarpFiltered); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kWarpDistributed); // NOLINT | ||
SELECTION_REGISTER(float, uint32_t, kWarpDistributedShm); // NOLINT | ||
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SELECTION_REGISTER(double, uint32_t, kRadix8bits); // NOLINT | ||
SELECTION_REGISTER(double, uint32_t, kRadix11bits); // NOLINT | ||
SELECTION_REGISTER(double, uint32_t, kRadix11bitsExtraPass); // NOLINT | ||
SELECTION_REGISTER(double, uint32_t, kWarpAuto); // NOLINT | ||
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SELECTION_REGISTER(double, int64_t, kRadix8bits); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kRadix11bits); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kRadix11bitsExtraPass); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kWarpImmediate); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kWarpFiltered); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kWarpDistributed); // NOLINT | ||
SELECTION_REGISTER(double, int64_t, kWarpDistributedShm); // NOLINT | ||
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// For learning a heuristic of which selection algorithm to use, we | ||
// have a couple of additional constraints when generating the dataset: | ||
// 1. We want these benchmarks to be optionally enabled from the commandline - | ||
// there are thousands of them, and the run-time is non-trivial. This should be opt-in only | ||
// 2. We test out larger k values - that won't work for all algorithms. This requires filtering | ||
// the input parameters per algorithm. | ||
// This makes the code to generate this dataset different from the code above to | ||
// register other benchmarks | ||
#define SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, A, input) \ | ||
{ \ | ||
using SelectK = selection<KeyT, IdxT, SelectAlgo::A>; \ | ||
std::stringstream name; \ | ||
name << "SelectKDataset/" << #KeyT "/" #IdxT "/" #A << "/" << input.batch_size << "/" \ | ||
<< input.len << "/" << input.k << "/" << input.use_index_input << "/" \ | ||
<< input.use_memory_pool; \ | ||
auto* b = ::benchmark::internal::RegisterBenchmarkInternal( \ | ||
new raft::bench::internal::Fixture<SelectK, select::params>(name.str(), input)); \ | ||
b->UseManualTime(); \ | ||
b->Unit(benchmark::kMillisecond); \ | ||
} | ||
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const static size_t MAX_MEMORY = 16 * 1024 * 1024 * 1024ULL; | ||
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// registers the input for all algorithms | ||
#define SELECTION_REGISTER_INPUT(KeyT, IdxT, input) \ | ||
{ \ | ||
size_t mem = input.batch_size * input.len * (sizeof(KeyT) + sizeof(IdxT)); \ | ||
if (mem < MAX_MEMORY) { \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kRadix8bits, input) \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kRadix11bits, input) \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kRadix11bitsExtraPass, input) \ | ||
if (input.k <= raft::matrix::detail::select::warpsort::kMaxCapacity) { \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kWarpImmediate, input) \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kWarpFiltered, input) \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kWarpDistributed, input) \ | ||
SELECTION_REGISTER_ALGO_INPUT(KeyT, IdxT, kWarpDistributedShm, input) \ | ||
} \ | ||
} \ | ||
} | ||
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void add_select_k_dataset_benchmarks() | ||
{ | ||
// define a uniform grid | ||
std::vector<select::params> inputs; | ||
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size_t grid_increment = 1; | ||
std::vector<int> k_vals; | ||
for (size_t k = 0; k < 13; k += grid_increment) { | ||
k_vals.push_back(1 << k); | ||
} | ||
// Add in values just past the limit for warp/faiss select | ||
k_vals.push_back(257); | ||
k_vals.push_back(2049); | ||
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const static bool select_min = true; | ||
const static bool use_ids = false; | ||
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for (size_t row = 0; row < 13; row += grid_increment) { | ||
for (size_t col = 10; col < 28; col += grid_increment) { | ||
for (auto k : k_vals) { | ||
inputs.push_back( | ||
select::params{size_t(1 << row), size_t(1 << col), k, select_min, use_ids}); | ||
} | ||
} | ||
} | ||
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// also add in some random values | ||
std::default_random_engine rng(42); | ||
std::uniform_real_distribution<> row_dist(0, 13); | ||
std::uniform_real_distribution<> col_dist(10, 28); | ||
std::uniform_real_distribution<> k_dist(0, 13); | ||
for (size_t i = 0; i < 1024; ++i) { | ||
auto row = static_cast<size_t>(pow(2, row_dist(rng))); | ||
auto col = static_cast<size_t>(pow(2, col_dist(rng))); | ||
auto k = static_cast<int>(pow(2, k_dist(rng))); | ||
inputs.push_back(select::params{row, col, k, select_min, use_ids}); | ||
} | ||
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for (auto& input : inputs) { | ||
SELECTION_REGISTER_INPUT(double, int64_t, input); | ||
SELECTION_REGISTER_INPUT(double, uint32_t, input); | ||
SELECTION_REGISTER_INPUT(float, int64_t, input); | ||
SELECTION_REGISTER_INPUT(float, uint32_t, input); | ||
} | ||
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// also try again without a memory pool to see if there are significant differences | ||
for (auto input : inputs) { | ||
input.use_memory_pool = false; | ||
SELECTION_REGISTER_INPUT(double, int64_t, input); | ||
SELECTION_REGISTER_INPUT(double, uint32_t, input); | ||
SELECTION_REGISTER_INPUT(float, int64_t, input); | ||
SELECTION_REGISTER_INPUT(float, uint32_t, input); | ||
} | ||
} | ||
} // namespace raft::matrix |
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