[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/examples/fill_copy_sequence.cu

@@ -0,0 +1,33 @@
+#include <thrust/copy.h>
+#include <thrust/device_vector.h>
+#include <thrust/fill.h>
+#include <thrust/host_vector.h>
+#include <thrust/sequence.h>
+
+#include <iostream>
+
+int main()
+{
+  // initialize all ten integers of a device_vector to 1
+  thrust::device_vector<int> D(10, 1);
+
+  // set the first seven elements of a vector to 9
+  thrust::fill(D.begin(), D.begin() + 7, 9);
+
+  // initialize a host_vector with the first five elements of D
+  thrust::host_vector<int> H(D.begin(), D.begin() + 5);
+
+  // set the elements of H to 0, 1, 2, 3, ...
+  thrust::sequence(H.begin(), H.end());
+
+  // copy all of H back to the beginning of D
+  thrust::copy(H.begin(), H.end(), D.begin());
+
+  // print D
+  for (size_t i = 0; i < D.size(); i++)
+  {
+    std::cout << "D[" << i << "] = " << D[i] << '\n';
+  }
+
+  return 0;
+}