[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/cudax/examples/cub_reduce.cu

@@ -0,0 +1,53 @@
+//===----------------------------------------------------------------------===//
+//
+// Part of CUDA Experimental in CUDA C++ Core Libraries,
+// 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) 2025 NVIDIA CORPORATION & AFFILIATES.
+//
+//===----------------------------------------------------------------------===//
+
+// Example of using `cub::DeviceReduce::Reduce` with cudax environment.
+
+#include <cub/device/device_reduce.cuh>
+
+#include <cuda/experimental/container.cuh>
+#include <cuda/experimental/memory_resource.cuh>
+#include <cuda/experimental/stream.cuh>
+
+#include <iostream>
+
+namespace cudax = cuda::experimental;
+
+int main()
+{
+  constexpr int num_items = 50000;
+
+  // A CUDA stream on which to execute the reduction
+  cuda::stream stream{cuda::devices[0]};
+  cuda::device_memory_pool_ref mr = cuda::device_default_memory_pool(cuda::devices[0]);
+
+  // Allocate input and output, but do not zero initialize output (`cuda::no_init`)
+  auto d_in  = cuda::make_buffer<int>(stream, mr, num_items, 1);
+  auto d_out = cuda::make_buffer<float>(stream, mr, 1, cuda::no_init);
+
+  // An environment we use to pass all necessary information to CUB
+  cudax::env_t<cuda::mr::device_accessible> env{mr, stream};
+  auto error = cub::DeviceReduce::Reduce(d_in.begin(), d_out.begin(), num_items, cuda::std::plus{}, 0, env);
+  if (error != cudaSuccess)
+  {
+    std::cerr << "cub::DeviceReduce::Reduce failed: " << cudaGetErrorString(error) << "\n";
+    exit(EXIT_FAILURE);
+  }
+
+  auto h_out = cuda::make_buffer<float>(stream, cuda::pinned_default_memory_pool(), d_out);
+
+  stream.sync();
+
+  if (h_out.get_unsynchronized(0) != num_items)
+  {
+    std::cerr << "Result verification failed: " << h_out.get_unsynchronized(0) << " != " << num_items << "\n";
+    exit(EXIT_FAILURE);
+  }
+}