[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/zip_iterator_reduce.cu

@@ -0,0 +1,49 @@
+#include <thrust/iterator/zip_iterator.h>
+#include <thrust/reduce.h>
+
+#include <unittest/unittest.h>
+
+using namespace unittest;
+
+template <typename Tuple>
+struct TuplePlus
+{
+  _CCCL_HOST_DEVICE Tuple operator()(Tuple x, Tuple y) const
+  {
+    return cuda::std::make_tuple(
+      cuda::std::get<0>(x) + cuda::std::get<0>(y), cuda::std::get<1>(x) + cuda::std::get<1>(y));
+  }
+}; // end SumTuple
+
+template <typename T>
+struct TestZipIteratorReduce
+{
+  void operator()(const size_t n)
+  {
+    thrust::host_vector<T> h_data0 = unittest::random_samples<T>(n);
+    thrust::host_vector<T> h_data1 = unittest::random_samples<T>(n);
+
+    thrust::device_vector<T> d_data0 = h_data0;
+    thrust::device_vector<T> d_data1 = h_data1;
+
+    using Tuple = cuda::std::tuple<T, T>;
+
+    // run on host
+    Tuple h_result = thrust::reduce(
+      thrust::make_zip_iterator(h_data0.begin(), h_data1.begin()),
+      thrust::make_zip_iterator(h_data0.end(), h_data1.end()),
+      cuda::std::make_tuple<T, T>(0, 0),
+      TuplePlus<Tuple>());
+
+    // run on device
+    Tuple d_result = thrust::reduce(
+      thrust::make_zip_iterator(d_data0.begin(), d_data1.begin()),
+      thrust::make_zip_iterator(d_data0.end(), d_data1.end()),
+      ::cuda::std::make_tuple<T, T>(0, 0),
+      TuplePlus<Tuple>());
+
+    ASSERT_EQUAL(cuda::std::get<0>(h_result), cuda::std::get<0>(d_result));
+    ASSERT_EQUAL(cuda::std::get<1>(h_result), cuda::std::get<1>(d_result));
+  }
+};
+VariableUnitTest<TestZipIteratorReduce, IntegralTypes> TestZipIteratorReduceInstance;