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/******************************************************************************
* Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of the NVIDIA CORPORATION nor the
* names of its contributors may be used to endorse or promote products
* derived from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
******************************************************************************/
#include <cub/device/device_copy.cuh>
#include <cub/util_ptx.cuh>
#include <thrust/iterator/constant_iterator.h>
#include <thrust/iterator/transform_iterator.h>
#include <thrust/iterator/transform_output_iterator.h>
#include <thrust/logical.h>
#include <thrust/sequence.h>
#include <thrust/tuple.h>
#include <algorithm>
#include <cstdint>
#include <limits>
#include <numeric>
#include <random>
#include <string>
#include <type_traits>
#include <utility>
#include <vector>
#include "c2h/vector.cuh"
#include "test_util.h"
/**
* @brief Host-side random data generation
*/
template <typename T>
void GenerateRandomData(
T* rand_out,
const std::size_t num_items,
const T min_rand_val = std::numeric_limits<T>::min(),
const T max_rand_val = std::numeric_limits<T>::max(),
const std::uint_fast32_t seed = 320981U,
typename std::enable_if<std::is_integral<T>::value && (sizeof(T) >= 2)>::type* = nullptr)
{
// initialize random number generator
std::mt19937 rng(seed);
std::uniform_int_distribution<T> uni_dist(min_rand_val, max_rand_val);
// generate random numbers
for (std::size_t i = 0; i < num_items; ++i)
{
rand_out[i] = uni_dist(rng);
}
}
/**
* @brief Used for generating a shuffled but cohesive sequence of output-range offsets for the
* sequence of input-ranges.
*/
template <typename RangeOffsetT, typename ByteOffsetT, typename RangeSizeT>
c2h::host_vector<ByteOffsetT>
GetShuffledRangeOffsets(const c2h::host_vector<RangeSizeT>& range_sizes, const std::uint_fast32_t seed = 320981U)
{
RangeOffsetT num_ranges = static_cast<RangeOffsetT>(range_sizes.size());
// We're remapping the i-th range to pmt_idxs[i]
std::mt19937 rng(seed);
c2h::host_vector<RangeOffsetT> pmt_idxs(num_ranges);
std::iota(pmt_idxs.begin(), pmt_idxs.end(), static_cast<RangeOffsetT>(0));
std::shuffle(std::begin(pmt_idxs), std::end(pmt_idxs), rng);
// Compute the offsets using the new mapping
ByteOffsetT running_offset = {};
c2h::host_vector<ByteOffsetT> permuted_offsets;
permuted_offsets.reserve(num_ranges);
for (auto permuted_range_idx : pmt_idxs)
{
permuted_offsets.push_back(running_offset);
running_offset += range_sizes[permuted_range_idx];
}
// Generate the scatter indexes that identify where each range was mapped to
c2h::host_vector<RangeOffsetT> scatter_idxs(num_ranges);
for (RangeOffsetT i = 0; i < num_ranges; i++)
{
scatter_idxs[pmt_idxs[i]] = i;
}
c2h::host_vector<ByteOffsetT> new_offsets(num_ranges);
for (RangeOffsetT i = 0; i < num_ranges; i++)
{
new_offsets[i] = permuted_offsets[scatter_idxs[i]];
}
return new_offsets;
}
template <size_t n, typename... T>
typename std::enable_if<n >= thrust::tuple_size<thrust::tuple<T...>>::value>::type
print_tuple(std::ostream&, const thrust::tuple<T...>&)
{}
template <size_t n, typename... T>
typename std::enable_if<n + 1 <= thrust::tuple_size<thrust::tuple<T...>>::value>::type
print_tuple(std::ostream& os, const thrust::tuple<T...>& tup)
{
_CCCL_IF_CONSTEXPR (n != 0)
{
os << ", ";
}
os << thrust::get<n>(tup);
print_tuple<n + 1>(os, tup);
}
template <typename... T>
std::ostream& operator<<(std::ostream& os, const thrust::tuple<T...>& tup)
{
os << "[";
print_tuple<0>(os, tup);
return os << "]";
}
struct Identity
{
template <typename T>
__host__ __device__ __forceinline__ T operator()(T x)
{
return x;
}
};
/**
* @brief Function object class template that takes an offset and returns an iterator at the given
* offset relative to a fixed base iterator.
*
* @tparam IteratorT The random-access iterator type to be returned
*/
template <typename IteratorT>
struct OffsetToIteratorOp
{
template <typename OffsetT>
__host__ __device__ __forceinline__ thrust::transform_output_iterator<Identity, IteratorT>
operator()(OffsetT offset) const
{
return thrust::make_transform_output_iterator(base_it + offset, Identity{});
}
IteratorT base_it;
};
template <typename AtomicT>
struct RepeatIndex
{
template <typename OffsetT>
__host__ __device__ __forceinline__ thrust::constant_iterator<AtomicT> operator()(OffsetT i)
{
return thrust::constant_iterator<AtomicT>(static_cast<AtomicT>(i));
}
};
enum class TestDataGen
{
// Random offsets into a data segment
RANDOM,
// Ranges cohesively reside next to each other
CONSECUTIVE
};
std::string TestDataGenToString(TestDataGen gen)
{
switch (gen)
{
case TestDataGen::RANDOM:
return "TestDataGen::RANDOM";
case TestDataGen::CONSECUTIVE:
return "TestDataGen::CONSECUTIVE";
default:
return "Unknown";
}
}
/**
* @brief
*
* @tparam AtomicT The type of the elements being copied
* @tparam RangeOffsetT Type used for indexing into the array of ranges
* @tparam RangeSizeT Type used for indexing into individual elements of a range (large enough to
* cover the max range size)
* @tparam ByteOffsetT Type used for indexing into elements over *all* the ranges' sizes
*/
template <typename AtomicT, typename RangeOffsetT, typename RangeSizeT, typename ByteOffsetT>
void RunTest(RangeOffsetT num_ranges, RangeSizeT min_range_size, RangeSizeT max_range_size, TestDataGen output_gen)
try
{
// Range segment data (their offsets and sizes)
c2h::host_vector<RangeSizeT> h_range_sizes(num_ranges);
thrust::counting_iterator<RangeOffsetT> iota(0);
auto d_range_srcs = thrust::make_transform_iterator(iota, RepeatIndex<AtomicT>{});
c2h::host_vector<ByteOffsetT> h_offsets(num_ranges + 1);
// Generate the range sizes
GenerateRandomData(h_range_sizes.data(), h_range_sizes.size(), min_range_size, max_range_size);
// Compute the total bytes to be copied
std::partial_sum(h_range_sizes.begin(), h_range_sizes.end(), h_offsets.begin() + 1);
const ByteOffsetT num_total_items = h_offsets.back();
h_offsets.pop_back();
constexpr int32_t shuffle_seed = 123241;
// Shuffle output range source-offsets
if (output_gen == TestDataGen::RANDOM)
{
h_offsets = GetShuffledRangeOffsets<RangeOffsetT, ByteOffsetT>(h_range_sizes, shuffle_seed);
}
// Device-side resources
c2h::device_vector<AtomicT> d_out(num_total_items);
c2h::device_vector<ByteOffsetT> d_offsets(h_offsets);
c2h::device_vector<RangeSizeT> d_range_sizes(h_range_sizes);
// Prepare d_range_dsts
using AtomicIterT = typename c2h::device_vector<AtomicT>::iterator;
OffsetToIteratorOp<AtomicIterT> dst_transform_op{d_out.begin()};
auto d_range_dsts = thrust::make_transform_iterator(d_offsets.begin(), dst_transform_op);
// Get temporary storage requirements
size_t temp_storage_bytes = 0;
CubDebugExit(cub::DeviceCopy::Batched(
nullptr, temp_storage_bytes, d_range_srcs, d_range_dsts, d_range_sizes.cbegin(), num_ranges));
c2h::device_vector<std::uint8_t> d_temp_storage(temp_storage_bytes);
c2h::host_vector<AtomicT> h_out(num_total_items);
c2h::host_vector<AtomicT> h_gpu_results(num_total_items);
// Invoke device-side algorithm being under test
CubDebugExit(cub::DeviceCopy::Batched(
thrust::raw_pointer_cast(d_temp_storage.data()),
temp_storage_bytes,
d_range_srcs,
d_range_dsts,
d_range_sizes.cbegin(),
num_ranges));
// Copy back the output range
h_gpu_results = d_out;
// CPU-side result generation for verification
for (RangeOffsetT i = 0; i < num_ranges; i++)
{
std::copy(d_range_srcs[i], d_range_srcs[i] + h_range_sizes[i], h_out.begin() + h_offsets[i]);
}
const auto it_pair = std::mismatch(h_gpu_results.cbegin(), h_gpu_results.cend(), h_out.cbegin());
if (it_pair.first != h_gpu_results.cend())
{
std::cout << "Mismatch at index " << std::distance(h_gpu_results.cbegin(), it_pair.first)
<< ", CPU vs. GPU: " << *it_pair.second << ", " << *it_pair.first << "\n";
}
AssertEquals(it_pair.first, h_gpu_results.cend());
}
catch (std::bad_alloc& e)
{
(void) e;
#ifdef DEBUG_CHECKED_ALLOC_FAILURE
std::cout
<< "Skipping test 'RunTest(" << num_ranges << ", " //
<< min_range_size << ", " //
<< max_range_size << ", " //
<< TestDataGenToString(output_gen) << ")" //
<< "' due to insufficient memory: " << e.what() << "\n";
#endif // DEBUG_CHECKED_ALLOC_FAILURE
}
struct object_with_non_trivial_ctor
{
static constexpr int MAGIC = 923390;
int field;
int magic;
__host__ __device__ object_with_non_trivial_ctor()
{
magic = MAGIC;
field = 0;
}
__host__ __device__ object_with_non_trivial_ctor(int f)
{
magic = MAGIC;
field = f;
}
object_with_non_trivial_ctor(const object_with_non_trivial_ctor& x) = default;
__host__ __device__ object_with_non_trivial_ctor& operator=(const object_with_non_trivial_ctor& x)
{
if (magic == MAGIC)
{
field = x.field;
}
return *this;
}
};
void nontrivial_constructor_test()
{
constexpr int num_buffers = 3;
c2h::device_vector<object_with_non_trivial_ctor> a(num_buffers, object_with_non_trivial_ctor(99));
c2h::device_vector<object_with_non_trivial_ctor> b(num_buffers);
using iterator = c2h::device_vector<object_with_non_trivial_ctor>::iterator;
c2h::device_vector<iterator> a_iter{a.begin(), a.begin() + 1, a.begin() + 2};
c2h::device_vector<iterator> b_iter{b.begin(), b.begin() + 1, b.begin() + 2};
auto sizes = thrust::make_constant_iterator(1);
std::uint8_t* d_temp_storage{};
std::size_t temp_storage_bytes{};
cub::DeviceCopy::Batched(d_temp_storage, temp_storage_bytes, a_iter.begin(), b_iter.begin(), sizes, num_buffers);
c2h::device_vector<std::uint8_t> temp_storage(temp_storage_bytes);
d_temp_storage = thrust::raw_pointer_cast(temp_storage.data());
cub::DeviceCopy::Batched(d_temp_storage, temp_storage_bytes, a_iter.begin(), b_iter.begin(), sizes, num_buffers);
for (int i = 0; i < 10; i++)
{
object_with_non_trivial_ctor ha(a[i]);
object_with_non_trivial_ctor hb(b[i]);
int ia = ha.field;
int ib = hb.field;
if (ia != ib)
{
std::cerr << "error: " << ia << " != " << ib << "\n";
}
}
}
int main(int argc, char** argv)
{
CommandLineArgs args(argc, argv);
// Initialize device
CubDebugExit(args.DeviceInit());
//---------------------------------------------------------------------
// DeviceCopy::Batched tests
//---------------------------------------------------------------------
// Run the nontrivial constructor test suggested by senior-zero
nontrivial_constructor_test();
// Type used for indexing into the array of ranges
using RangeOffsetT = uint32_t;
// Type used for indexing into individual elements of a range (large enough to cover the max range
using RangeSizeT = uint32_t;
// Type used for indexing into bytes over *all* the ranges' sizes
using ByteOffsetT = uint32_t;
// Total number of bytes that are targeted to be copied on each run
constexpr RangeOffsetT target_copy_size = 64U << 20;
// The number of randomly
constexpr std::size_t num_rnd_range_tests = 32;
// Each range's size will be random within this interval
c2h::host_vector<std::pair<std::size_t, std::size_t>> size_ranges = {
{0, 1},
{1, 2},
{0, 16},
{1, 32},
{1, 1024},
{1, 32 * 1024},
{128 * 1024, 256 * 1024},
{target_copy_size, target_copy_size}};
std::mt19937 rng(0);
std::uniform_int_distribution<std::size_t> size_dist(1, 1000000);
for (std::size_t i = 0; i < num_rnd_range_tests; i++)
{
auto range_begin = size_dist(rng);
auto range_end = size_dist(rng);
if (range_begin > range_end)
{
std::swap(range_begin, range_end);
}
size_ranges.push_back({range_begin, range_end});
}
for (const auto& size_range : size_ranges)
{
// The most granular type being copied.
using AtomicCopyT = int64_t;
RangeSizeT min_range_size = static_cast<RangeSizeT>(CUB_ROUND_UP_NEAREST(size_range.first, sizeof(AtomicCopyT)));
RangeSizeT max_range_size =
static_cast<RangeSizeT>(CUB_ROUND_UP_NEAREST(size_range.second, static_cast<RangeSizeT>(sizeof(AtomicCopyT))));
double average_range_size = (min_range_size + max_range_size) / 2.0;
RangeOffsetT target_num_ranges = static_cast<RangeOffsetT>(target_copy_size / average_range_size);
// Run tests with output ranges being consecutive
RunTest<AtomicCopyT, RangeOffsetT, RangeSizeT, ByteOffsetT>(
target_num_ranges, min_range_size, max_range_size, TestDataGen::CONSECUTIVE);
// Run tests with output ranges being randomly shuffled
RunTest<AtomicCopyT, RangeOffsetT, RangeSizeT, ByteOffsetT>(
target_num_ranges, min_range_size, max_range_size, TestDataGen::RANDOM);
}
for (const auto& size_range : size_ranges)
{
// The most granular type being copied.
using AtomicCopyT = thrust::tuple<int64_t, int32_t, int16_t, char, char>;
RangeSizeT min_range_size = static_cast<RangeSizeT>(CUB_ROUND_UP_NEAREST(size_range.first, sizeof(AtomicCopyT)));
RangeSizeT max_range_size =
static_cast<RangeSizeT>(CUB_ROUND_UP_NEAREST(size_range.second, static_cast<RangeSizeT>(sizeof(AtomicCopyT))));
double average_range_size = (min_range_size + max_range_size) / 2.0;
RangeOffsetT target_num_ranges = static_cast<RangeOffsetT>(target_copy_size / average_range_size);
// Run tests with output ranges being consecutive
RunTest<AtomicCopyT, RangeOffsetT, RangeSizeT, ByteOffsetT>(
target_num_ranges, min_range_size, max_range_size, TestDataGen::CONSECUTIVE);
// Run tests with output ranges being randomly shuffled
RunTest<AtomicCopyT, RangeOffsetT, RangeSizeT, ByteOffsetT>(
target_num_ranges, min_range_size, max_range_size, TestDataGen::RANDOM);
}
//---------------------------------------------------------------------
// DeviceCopy::Batched test with 64-bit offsets
//---------------------------------------------------------------------
using ByteOffset64T = uint64_t;
using RangeSize64T = uint64_t;
ByteOffset64T large_target_copy_size =
static_cast<ByteOffset64T>(std::numeric_limits<uint32_t>::max()) + (128ULL * 1024ULL * 1024ULL);
// Make sure min_range_size is in fact smaller than max range size
constexpr RangeOffsetT single_range = 1;
// Run tests with output ranges being consecutive
RunTest<uint8_t, RangeOffsetT, RangeSize64T, ByteOffset64T>(
single_range, large_target_copy_size, large_target_copy_size, TestDataGen::CONSECUTIVE);
}
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