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project_6/cccl_upstream/thrust/testing/cuda/transform_scan.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/execution_policy.h>
#include <thrust/transform_scan.h>
#include <unittest/unittest.h>
#ifdef THRUST_TEST_DEVICE_SIDE
template <typename ExecutionPolicy,
typename Iterator1,
typename Iterator2,
typename Function1,
typename Function2,
typename Iterator3>
__global__ void transform_inclusive_scan_kernel(
ExecutionPolicy exec,
Iterator1 first,
Iterator1 last,
Iterator2 result1,
Function1 f1,
Function2 f2,
Iterator3 result2)
{
*result2 = thrust::transform_inclusive_scan(exec, first, last, result1, f1, f2);
}
template <typename ExecutionPolicy,
typename Iterator1,
typename Iterator2,
typename Function1,
typename T,
typename Function2,
typename Iterator3>
__global__ void transform_inclusive_scan_init_kernel(
ExecutionPolicy exec,
Iterator1 first,
Iterator1 last,
Iterator2 result1,
Function1 f1,
T init,
Function2 f2,
Iterator3 result2)
{
*result2 = thrust::transform_inclusive_scan(exec, first, last, result1, f1, init, f2);
}
template <typename ExecutionPolicy,
typename Iterator1,
typename Iterator2,
typename Function1,
typename T,
typename Function2,
typename Iterator3>
__global__ void transform_exclusive_scan_kernel(
ExecutionPolicy exec,
Iterator1 first,
Iterator1 last,
Iterator2 result,
Function1 f1,
T init,
Function2 f2,
Iterator3 result2)
{
*result2 = thrust::transform_exclusive_scan(exec, first, last, result, f1, init, f2);
}
template <typename ExecutionPolicy>
void TestTransformScanDevice(ExecutionPolicy exec)
{
using Vector = thrust::device_vector<int>;
using T = typename Vector::value_type;
typename Vector::iterator iter;
Vector input{1, 3, -2, 4, -5};
Vector ref{-1, -4, -2, -6, -1};
Vector output(5);
Vector input_copy(input);
thrust::device_vector<typename Vector::iterator> iter_vec(1);
// inclusive scan
transform_inclusive_scan_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(ref, output);
// inclusive scan with nonzero init
transform_inclusive_scan_init_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ref = {2, -1, 1, -3, 2};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(ref, output);
// exclusive scan with 0 init
transform_exclusive_scan_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
0,
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
ref = {0, -1, -4, -2, -6};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(ref, output);
// exclusive scan with nonzero init
transform_exclusive_scan_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ref = {3, 2, -1, 1, -3};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(ref, output);
// inplace inclusive scan
input = input_copy;
transform_inclusive_scan_kernel<<<1, 1>>>(
exec, input.begin(), input.end(), input.begin(), ::cuda::std::negate<T>(), ::cuda::std::plus<T>(), iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ref = {-1, -4, -2, -6, -1};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(ref, input);
// inplace inclusive scan with init
input = input_copy;
transform_inclusive_scan_init_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
input.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ref = {2, -1, 1, -3, 2};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(ref, input);
// inplace exclusive scan with init
input = input_copy;
transform_exclusive_scan_kernel<<<1, 1>>>(
exec,
input.begin(),
input.end(),
input.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>(),
iter_vec.begin());
{
cudaError_t const err = cudaDeviceSynchronize();
ASSERT_EQUAL(cudaSuccess, err);
}
iter = iter_vec[0];
ref = {3, 2, -1, 1, -3};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(ref, input);
}
void TestTransformScanDeviceSeq()
{
TestTransformScanDevice(thrust::seq);
}
DECLARE_UNITTEST(TestTransformScanDeviceSeq);
void TestTransformScanDeviceDevice()
{
TestTransformScanDevice(thrust::device);
}
DECLARE_UNITTEST(TestTransformScanDeviceDevice);
#endif
void TestTransformScanCudaStreams()
{
using Vector = thrust::device_vector<int>;
using T = Vector::value_type;
Vector::iterator iter;
Vector input{1, 3, -2, 4, -5};
Vector result{-1, -4, -2, -6, -1};
Vector output(5);
Vector input_copy(input);
cudaStream_t s;
cudaStreamCreate(&s);
// inclusive scan
iter = thrust::transform_inclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(output, result);
// inclusive scan with nonzero init
iter = thrust::transform_inclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {2, -1, 1, -3, 2};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(output, result);
// exclusive scan with 0 init
iter = thrust::transform_exclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
0,
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {0, -1, -4, -2, -6};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(output, result);
// exclusive scan with nonzero init
iter = thrust::transform_exclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
output.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {3, 2, -1, 1, -3};
ASSERT_EQUAL(std::size_t(iter - output.begin()), input.size());
ASSERT_EQUAL(input, input_copy);
ASSERT_EQUAL(output, result);
// inplace inclusive scan
input = input_copy;
iter = thrust::transform_inclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
input.begin(),
::cuda::std::negate<T>(),
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {-1, -4, -2, -6, -1};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(input, result);
// inplace inclusive scan with init
input = input_copy;
iter = thrust::transform_inclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
input.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {2, -1, 1, -3, 2};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(input, result);
// inplace exclusive scan with init
input = input_copy;
iter = thrust::transform_exclusive_scan(
thrust::cuda::par.on(s),
input.begin(),
input.end(),
input.begin(),
::cuda::std::negate<T>(),
3,
::cuda::std::plus<T>());
cudaStreamSynchronize(s);
result = {3, 2, -1, 1, -3};
ASSERT_EQUAL(std::size_t(iter - input.begin()), input.size());
ASSERT_EQUAL(input, result);
cudaStreamDestroy(s);
}
DECLARE_UNITTEST(TestTransformScanCudaStreams);
void TestTransformScanConstAccumulator()
{
using Vector = thrust::device_vector<int>;
using T = Vector::value_type;
Vector::iterator iter;
Vector input{1, 3, -2, 4, -5};
Vector reference(5);
Vector output(5);
thrust::transform_inclusive_scan(
input.begin(), input.end(), output.begin(), ::cuda::std::identity{}, ::cuda::std::plus<T>());
thrust::inclusive_scan(input.begin(), input.end(), reference.begin(), ::cuda::std::plus<T>());
ASSERT_EQUAL(output, reference);
}
DECLARE_UNITTEST(TestTransformScanConstAccumulator);