[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/cudax_stf/CMakeLists.txt

@@ -0,0 +1,62 @@
+# SPDX-FileCopyrightText: Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+cmake_minimum_required(VERSION 3.18 FATAL_ERROR)
+
+project(CUDAX_SAMPLES CUDA CXX)
+
+# This example uses the CMake Package Manager (CPM) to simplify fetching CCCL from GitHub
+# For more information, see https://github.com/cpm-cmake/CPM.cmake
+include(cmake/CPM.cmake)
+
+# We define these as variables so they can be overridden in CI to pull from a PR instead of CCCL `main`
+# In your project, these variables are unnecessary and you can just use the values directly
+set(
+  CCCL_REPOSITORY
+  "https://github.com/NVIDIA/cccl"
+  CACHE STRING
+  "Git repository to fetch CCCL from"
+)
+set(CCCL_TAG "main" CACHE STRING "Git tag/branch to fetch from CCCL repository")
+
+# This will automatically clone CCCL from GitHub and make the exported cmake targets available
+CPMAddPackage(
+  NAME CCCL
+  GIT_REPOSITORY "${CCCL_REPOSITORY}"
+  GIT_TAG ${CCCL_TAG}
+  # The following is required to make the `CCCL::cudax` target available:
+  OPTIONS "CCCL_ENABLE_UNSTABLE ON"
+)
+
+# Default to building for the GPU on the current system
+if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
+  set(CMAKE_CUDA_ARCHITECTURES native)
+endif()
+
+# If you're building an executable
+add_executable(simple_stf simple_stf.cu)
+
+target_link_libraries(simple_stf PUBLIC cuda)
+
+if (CMAKE_CUDA_COMPILER)
+  target_compile_options(
+    simple_stf
+    PUBLIC
+      $<$<COMPILE_LANG_AND_ID:CUDA,NVIDIA>:--expt-relaxed-constexpr>
+      $<$<COMPILE_LANG_AND_ID:CUDA,NVIDIA>:--extended-lambda>
+  )
+endif()
+
+target_link_libraries(simple_stf PRIVATE CCCL::CCCL CCCL::cudax)

cccl_upstream/examples/cudax_stf/simple_stf.cu

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+//===----------------------------------------------------------------------===//
+//
+// Part of CUDASTF 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) 2022-2024 NVIDIA CORPORATION & AFFILIATES.
+//
+//===----------------------------------------------------------------------===//
+
+#include <cuda/experimental/stf.cuh>
+
+#include <cstdio>
+
+using namespace cuda::experimental::stf;
+
+int main()
+{
+  context ctx;
+
+  int array[128];
+  for (size_t i = 0; i < 128; i++)
+  {
+    array[i] = i;
+  }
+
+  auto A = ctx.logical_data(array);
+
+  ctx.parallel_for(A.shape(), A.rw())->*[] __device__(size_t i, auto a) {
+    a(i) += 4;
+  };
+
+  ctx.finalize();
+
+  for (size_t i = 0; i < 128; i++)
+  {
+    printf("array[%ld] = %d\n", i, array[i]);
+  }
+  return 0;
+}