[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/cpp_integration/device.cu

@@ -0,0 +1,17 @@
+#include <thrust/copy.h>
+#include <thrust/device_vector.h>
+#include <thrust/sort.h>
+
+#include "device.h"
+
+void sort_on_device(thrust::host_vector<int>& h_vec)
+{
+  // transfer data to the device
+  thrust::device_vector<int> d_vec = h_vec;
+
+  // sort data on the device
+  thrust::sort(d_vec.begin(), d_vec.end());
+
+  // transfer data back to host
+  thrust::copy(d_vec.begin(), d_vec.end(), h_vec.begin());
+}