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project_6/cccl_upstream/thrust/testing/reduce_into.cu
EngineX CI 56fd68e7dd [INFRA] Import NVIDIA/CCCL upstream as optimization reference library
CCCL (CUDA C++ Core Libraries) provides:
- CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk)
- Thrust: high-level parallel algorithms (transform_reduce, sort, scan)
- libcudacxx: CUDA C++ standard library (atomics, barriers, memory)
- cudax: experimental features (memory resources, allocators)
- Tuning policies: per-SM hardware-specific algorithm parameters

Competition optimization vectors mapped to CCCL:
- Output TPS (83% weight): warp_reduce, block_reduce, device_topk
- Input TPS (14% weight): device_scan, block_load, prefetch
- Cache TPS (3% weight): prefix caching strategy patterns
- Memory (0.9 util): pooled/cached/buddy allocators

Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only)
License: Apache-2.0
2026-07-30 09:35:51 +00:00

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#include <thrust/iterator/counting_iterator.h>
#include <thrust/iterator/retag.h>
#include <thrust/reduce.h>
#include <limits>
#include <unittest/unittest.h>
template <typename T>
struct plus_mod_10
{
_CCCL_HOST_DEVICE T operator()(T lhs, T rhs) const
{
return ((lhs % 10) + (rhs % 10)) % 10;
}
};
template <class Vector>
void TestReduceIntoSimple()
{
using T = typename Vector::value_type;
Vector i{1, -2, 3};
Vector o(1);
// no initializer
thrust::reduce_into(i.begin(), i.end(), o.begin());
ASSERT_EQUAL(o[0], 2);
// with initializer
thrust::reduce_into(i.begin(), i.end(), o.begin(), T(10));
ASSERT_EQUAL(o[0], 12);
}
DECLARE_VECTOR_UNITTEST(TestReduceIntoSimple);
template <typename InputIterator, typename OutputIterator>
void reduce_into(my_system& system, InputIterator, InputIterator, OutputIterator output)
{
system.validate_dispatch();
*output = 13;
}
void TestReduceIntoDispatchExplicit()
{
thrust::device_vector<int> i;
thrust::device_vector<int> o(1);
my_system sys(0);
thrust::reduce_into(sys, i.begin(), i.end(), o.begin());
ASSERT_EQUAL(true, sys.is_valid());
ASSERT_EQUAL(o[0], 13);
}
DECLARE_UNITTEST(TestReduceIntoDispatchExplicit);
template <typename InputIterator, typename OutputIterator>
void reduce_into(my_tag, InputIterator, InputIterator, OutputIterator output)
{
*output = 13;
}
void TestReduceIntoDispatchImplicit()
{
thrust::device_vector<int> i;
thrust::device_vector<int> o(1);
thrust::reduce_into(
thrust::retag<my_tag>(i.begin()), thrust::retag<my_tag>(i.end()), thrust::retag<my_tag>(o.begin()));
ASSERT_EQUAL(o[0], 13);
}
DECLARE_UNITTEST(TestReduceIntoDispatchImplicit);
template <typename T>
struct TestReduceInto
{
void operator()(const size_t n)
{
thrust::host_vector<T> h_data(unittest::random_integers<T>(n));
thrust::device_vector<T> d_data(h_data);
thrust::host_vector<T> h_result(1);
thrust::device_vector<T> d_result(1);
T init = 13;
thrust::reduce_into(h_data.begin(), h_data.end(), h_result.begin(), init);
thrust::reduce_into(d_data.begin(), d_data.end(), d_result.begin(), init);
ASSERT_EQUAL(h_result, d_result);
}
};
VariableUnitTest<TestReduceInto, IntegralTypes> TestReduceIntoInstance;
void TestReduceIntoMixedTypesHost()
{
// make sure we get types for default args and operators correct
thrust::host_vector<int> int_input{1, 2, 3, 4};
thrust::host_vector<float> float_input{1.5, 2.5, 3.5, 4.5};
// float -> int should use using plus<int> operator by default
thrust::host_vector<int> int_output(1);
thrust::reduce_into(float_input.begin(), float_input.end(), int_output.begin(), int(0));
ASSERT_EQUAL(int_output[0], 10);
// int -> float should use using plus<float> operator by default
thrust::host_vector<float> float_output(1);
thrust::reduce_into(int_input.begin(), int_input.end(), float_output.begin(), float(0.5));
ASSERT_EQUAL(float_output[0], 10.5);
}
DECLARE_UNITTEST(TestReduceIntoMixedTypesHost);
void TestReduceIntoMixedTypesDevice()
{
// make sure we get types for default args and operators correct
thrust::device_vector<int> int_input{1, 2, 3, 4};
thrust::device_vector<float> float_input{1.5, 2.5, 3.5, 4.5};
// float -> int should use using plus<int> operator by default
thrust::device_vector<int> int_output(1);
thrust::reduce_into(float_input.begin(), float_input.end(), int_output.begin(), int(0));
ASSERT_EQUAL(int_output[0], 10);
// int -> float should use using plus<float> operator by default
thrust::device_vector<float> float_output(1);
thrust::reduce_into(int_input.begin(), int_input.end(), float_output.begin(), float(0.5));
ASSERT_EQUAL(float_output[0], 10.5);
}
DECLARE_UNITTEST(TestReduceIntoMixedTypesDevice);
template <typename T>
struct TestReduceIntoWithOperator
{
void operator()(const size_t n)
{
thrust::host_vector<T> h_data = unittest::random_integers<T>(n);
thrust::device_vector<T> d_data = h_data;
thrust::host_vector<T> h_result(1);
thrust::device_vector<T> d_result(1);
T init = 3;
thrust::reduce_into(h_data.begin(), h_data.end(), h_result.begin(), init, plus_mod_10<T>());
thrust::reduce_into(d_data.begin(), d_data.end(), d_result.begin(), init, plus_mod_10<T>());
ASSERT_EQUAL(h_result, d_result);
}
};
VariableUnitTest<TestReduceIntoWithOperator, UnsignedIntegralTypes> TestReduceIntoWithOperatorInstance;
template <typename T>
struct plus_mod3
{
T* table;
plus_mod3(T* table)
: table(table)
{}
_CCCL_HOST_DEVICE T operator()(T a, T b)
{
return table[(int) (a + b)];
}
};
template <typename Vector>
void TestReduceIntoWithIndirection()
{
// add numbers modulo 3 with external lookup table
using T = typename Vector::value_type;
Vector data{0, 1, 2, 1, 2, 0, 1};
Vector table{0, 1, 2, 0, 1, 2};
Vector result(1);
thrust::reduce_into(data.begin(), data.end(), result.begin(), T(0), plus_mod3<T>(thrust::raw_pointer_cast(&table[0])));
ASSERT_EQUAL(result[0], T(1));
}
DECLARE_INTEGRAL_VECTOR_UNITTEST(TestReduceIntoWithIndirection);
template <typename T>
void TestReduceIntoCountingIterator()
{
size_t const n = 15 * sizeof(T);
ASSERT_LEQUAL(T(n), unittest::truncate_to_max_representable<T>(n));
thrust::counting_iterator<T, thrust::host_system_tag> h_first = thrust::make_counting_iterator<T>(0);
thrust::counting_iterator<T, thrust::device_system_tag> d_first = thrust::make_counting_iterator<T>(0);
thrust::host_vector<T> h_result(1);
thrust::device_vector<T> d_result(1);
T init = unittest::random_integer<T>();
thrust::reduce_into(h_first, h_first + n, h_result.begin(), init);
thrust::reduce_into(d_first, d_first + n, d_result.begin(), init);
// we use ASSERT_ALMOST_EQUAL because we're testing floating point types
ASSERT_ALMOST_EQUAL(h_result, d_result);
}
DECLARE_GENERIC_UNITTEST(TestReduceIntoCountingIterator);