[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/examples/ccclrt/kernel_launch_patterns/common.cuh

@@ -0,0 +1,66 @@
+//===----------------------------------------------------------------------===//
+//
+// Part of libcu++, the C++ Standard Library for your entire system,
+// under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES.
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef COMMON_CUH
+#define COMMON_CUH
+
+#include <cuda/std/algorithm>
+#include <cuda/std/cstddef>
+#include <cuda/std/string_view>
+
+#include <stdio.h>
+
+class KernelName
+{
+  static constexpr cuda::std::size_t max_size = 128;
+
+  char name_[max_size]; // The name buffer.
+
+public:
+  __host__ __device__ KernelName(cuda::std::string_view name)
+  {
+    assert(name.size() < max_size);
+
+    // Copy the name.
+    cuda::std::copy_n(name.data(), name.size(), name_);
+
+    // Zero terminate the string.
+    name_[name.size()] = '\0';
+  }
+
+  // Returns the stored name.
+  __host__ __device__ const char* get() const
+  {
+    return name_;
+  }
+};
+
+__device__ void say_hello(uint3 from_tindex, const KernelName& kernel_name)
+{
+  const auto this_tindex = cuda::gpu_thread.index(cuda::block);
+
+  printf("[%u, %u]: Hello from thread [%u, %u] launched as %s!\n",
+         this_tindex.x,
+         this_tindex.y,
+         from_tindex.x,
+         from_tindex.y,
+         kernel_name.get());
+
+  // Wait for all threads in block to print the output.
+  __syncthreads();
+
+  // Print additional new line once.
+  if (this_tindex.x == 0 && this_tindex.y == 0)
+  {
+    printf("\n");
+  }
+}
+
+#endif // COMMON_CUH