[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/cuda/stream_per_thread.cu

@@ -0,0 +1,22 @@
+#include <thrust/execution_policy.h>
+#include <thrust/system/cuda/detail/util.h>
+
+#include <thread>
+
+#include <unittest/unittest.h>
+
+void verify_stream()
+{
+  auto exec   = thrust::device;
+  auto stream = thrust::cuda_cub::stream(exec);
+  ASSERT_EQUAL(stream, cudaStreamPerThread);
+}
+
+void TestPerThreadDefaultStream()
+{
+  verify_stream();
+
+  std::thread t(verify_stream);
+  t.join();
+}
+DECLARE_UNITTEST(TestPerThreadDefaultStream);