[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/cpp/CMakeLists.txt

@@ -0,0 +1,20 @@
+file(
+  GLOB test_srcs
+  RELATIVE "${CMAKE_CURRENT_LIST_DIR}"
+  CONFIGURE_DEPENDS
+  *.cu
+  *.cpp
+)
+
+foreach (thrust_target IN LISTS THRUST_TARGETS)
+  thrust_get_target_property(config_device ${thrust_target} DEVICE)
+  if (NOT config_device STREQUAL "CPP")
+    continue()
+  endif()
+
+  foreach (test_src IN LISTS test_srcs)
+    get_filename_component(test_name "${test_src}" NAME_WLE)
+    string(PREPEND test_name "cpp.")
+    thrust_add_test(test_target ${test_name} "${test_src}" ${thrust_target})
+  endforeach()
+endforeach()