[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

cccl_upstream/thrust/testing/cuda/sequence.cu

@@ -0,0 +1,100 @@
+#include <thrust/execution_policy.h>
+#include <thrust/sequence.h>
+
+#include <unittest/unittest.h>
+
+#ifdef THRUST_TEST_DEVICE_SIDE
+template <typename ExecutionPolicy, typename Iterator>
+__global__ void sequence_kernel(ExecutionPolicy exec, Iterator first, Iterator last)
+{
+  thrust::sequence(exec, first, last);
+}
+
+template <typename ExecutionPolicy, typename Iterator, typename T>
+__global__ void sequence_kernel(ExecutionPolicy exec, Iterator first, Iterator last, T init)
+{
+  thrust::sequence(exec, first, last, init);
+}
+
+template <typename ExecutionPolicy, typename Iterator, typename T>
+__global__ void sequence_kernel(ExecutionPolicy exec, Iterator first, Iterator last, T init, T step)
+{
+  thrust::sequence(exec, first, last, init, step);
+}
+
+template <typename ExecutionPolicy>
+void TestSequenceDevice(ExecutionPolicy exec)
+{
+  thrust::device_vector<int> v(5);
+
+  sequence_kernel<<<1, 1>>>(exec, v.begin(), v.end());
+  {
+    cudaError_t const err = cudaDeviceSynchronize();
+    ASSERT_EQUAL(cudaSuccess, err);
+  }
+
+  thrust::device_vector<int> ref{0, 1, 2, 3, 4};
+  ASSERT_EQUAL(v, ref);
+
+  sequence_kernel<<<1, 1>>>(exec, v.begin(), v.end(), 10);
+  {
+    cudaError_t const err = cudaDeviceSynchronize();
+    ASSERT_EQUAL(cudaSuccess, err);
+  }
+
+  ref = {10, 11, 12, 13, 14};
+  ASSERT_EQUAL(v, ref);
+
+  sequence_kernel<<<1, 1>>>(exec, v.begin(), v.end(), 10, 2);
+  {
+    cudaError_t const err = cudaDeviceSynchronize();
+    ASSERT_EQUAL(cudaSuccess, err);
+  }
+
+  ref = {10, 12, 14, 16, 18};
+  ASSERT_EQUAL(v, ref);
+}
+
+void TestSequenceDeviceSeq()
+{
+  TestSequenceDevice(thrust::seq);
+}
+DECLARE_UNITTEST(TestSequenceDeviceSeq);
+
+void TestSequenceDeviceDevice()
+{
+  TestSequenceDevice(thrust::device);
+}
+DECLARE_UNITTEST(TestSequenceDeviceDevice);
+#endif
+
+void TestSequenceCudaStreams()
+{
+  using Vector = thrust::device_vector<int>;
+
+  Vector v(5);
+
+  cudaStream_t s;
+  cudaStreamCreate(&s);
+
+  thrust::sequence(thrust::cuda::par.on(s), v.begin(), v.end());
+  cudaStreamSynchronize(s);
+
+  Vector ref{0, 1, 2, 3, 4};
+  ASSERT_EQUAL(v, ref);
+
+  thrust::sequence(thrust::cuda::par.on(s), v.begin(), v.end(), 10);
+  cudaStreamSynchronize(s);
+
+  ref = {10, 11, 12, 13, 14};
+  ASSERT_EQUAL(v, ref);
+
+  thrust::sequence(thrust::cuda::par.on(s), v.begin(), v.end(), 10, 2);
+  cudaStreamSynchronize(s);
+
+  ref = {10, 12, 14, 16, 18};
+  ASSERT_EQUAL(v, ref);
+
+  cudaStreamDestroy(s);
+}
+DECLARE_UNITTEST(TestSequenceCudaStreams);