[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/libcudacxx/test/maintenance/std-to-cuda

@@ -0,0 +1,16 @@
+#!/usr/bin/env bash
+
+set -euo pipefail
+
+root_dir=$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)
+
+stdlib_headers=$(<"${root_dir}/maintenance/stdlib-headers")
+# shellcheck disable=SC2001
+header_replacements=$(echo "${stdlib_headers}" | sed 's#<\(.*\)>#-e s:<\1>:<cuda/std/\1>:g#')
+
+find "${root_dir}/test" -name "*.cpp" |
+while read -r file
+do
+    sed -i "${file}" "${header_replacements}"
+    perl -pi -e 's/((?<!cuda::))std::/\1cuda::std::/g' "${file}"
+done