[CCCL] Add missing CCCL components: c2h, nvbench_helper, cmake, cudax, AGENTS.md

Added 863 files from NVIDIA/cccl sparse checkout:
- c2h/ (27 files): Catch2 test helpers — generators, validators, runner
- nvbench_helper/ (10 files): Benchmark harness utilities
- cmake/ (29 files): CMake presets and build helpers
- cudax/ (794 files): Experimental CUDA extensions
- AGENTS.md: NVIDIA's official AI agent instructions for CCCL
- CMakePresets.json: Standardized build configurations
- cccl-version.json: Version tracking

Also added CCCL_ASSET_MAP.md mapping all 4295 CCCL files to
competition value and PRD items.

cccl_upstream now covers 100% of competition-critical assets:
- 27 tuning headers (SM80/90/100 benchmark data)
- 32 dispatch headers (algorithm implementations)
- 60 Thrust examples (correctness verification)
- 217 CUB Catch2 tests (regression matrix)
- 153 CUB benchmarks (parameter space search)
- 18 CUB examples (API verification)
- 27 test helpers + benchmark harness
- 794 cudax experimental extensions

cccl_upstream/cudax/test/common/group_testing.cuh

@@ -0,0 +1,103 @@
+//===----------------------------------------------------------------------===//
+//
+// 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) 2026 NVIDIA CORPORATION & AFFILIATES.
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef COMMON_GROUP_CUH
+#define COMMON_GROUP_CUH
+
+#include <cuda/barrier>
+#include <cuda/std/cstddef>
+#include <cuda/std/type_traits>
+#include <cuda/warp>
+
+#include <cuda/experimental/group.cuh>
+
+#include "testing.cuh"
+
+namespace
+{
+template <class T, cuda::std::size_t Id>
+__device__ T global_barriers_storage;
+
+//! @brief Returns reference to an array of N cuda::barrier objects with suitable thread scope for level allocated in
+//!        suitable address space (shared or device memory). Id parameter can be used to create unique object.
+template <cuda::std::size_t N, cuda::std::size_t Id = 0, class Level>
+__device__ auto& get_barriers(const Level& level) noexcept
+{
+  constexpr auto scope = cudax::__minimum_required_scope_for<Level>();
+
+  using Barrier         = cuda::barrier<scope>;
+  using BarriersStorage = cuda::std::aligned_storage_t<N * sizeof(Barrier), alignof(Barrier)>;
+
+  if constexpr (scope >= cuda::thread_scope_block)
+  {
+    __shared__ BarriersStorage shared_barriers_storage;
+    return reinterpret_cast<Barrier(&)[N]>(shared_barriers_storage);
+  }
+  else
+  {
+    return reinterpret_cast<Barrier(&)[N]>(global_barriers_storage<BarriersStorage, Id>);
+  }
+}
+
+struct ThreadsInWarpMappingResult
+{
+  __device__ static constexpr ::cuda::std::size_t static_group_count()
+  {
+    return 1;
+  }
+
+  __device__ unsigned group_count() const
+  {
+    return 1;
+  }
+
+  __device__ unsigned group_rank() const
+  {
+    return 0;
+  }
+
+  __device__ static constexpr ::cuda::std::size_t static_unit_count()
+  {
+    return 32;
+  }
+
+  __device__ unsigned unit_count() const
+  {
+    return 32;
+  }
+
+  __device__ unsigned unit_rank() const
+  {
+    return cuda::gpu_thread.rank_as<unsigned>(cuda::warp);
+  }
+
+  __device__ cuda::device::lane_mask lane_mask() const noexcept
+  {
+    return cuda::device::lane_mask::all();
+  }
+
+  __device__ bool is_valid() const
+  {
+    return true;
+  }
+
+  __device__ static constexpr bool is_always_exhaustive() noexcept
+  {
+    return true;
+  }
+
+  __device__ static constexpr bool is_always_contiguous() noexcept
+  {
+    return true;
+  }
+};
+} // namespace
+
+#endif // COMMON_GROUP_CUH