[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/cub/test/link_a.cu

@@ -0,0 +1,11 @@
+#include <cub/cub.cuh>
+
+void a()
+{
+  printf("a() called\n");
+
+  cub::DoubleBuffer<unsigned int> d_keys;
+  cub::DoubleBuffer<cub::NullType> d_values;
+  size_t temp_storage_bytes = 0;
+  cub::DeviceRadixSort::SortPairs(nullptr, temp_storage_bytes, d_keys, d_values, 1024);
+}