[CCCL] 瘦身 + 补全: 移除 cudax/python/libcudacxx-tests 冗余文件, 新增 c2h 测试助手 + cmake 构建系统 + 8 个 CUDA thrust examples

变更摘要:
- 删除: cudax/ (783 files, 7.2M) — 实验性组件，竞赛不需要
- 删除: python/ (226 files, 2.0M) — Python 绑定，竞赛不需要
- 删除: libcudacxx/{test,benchmarks,codegen,cmake,share} (4432 files, 31M)
  保留: libcudacxx/include/ (1463 headers, cuda::std 编译依赖)
- 新增: c2h/ (27 files) — CUB Catch2 测试辅助头文件，编译 243 个测试必需
- 新增: cmake/ (29 files) — CCCL 原生 CMake 构建系统
- 新增: thrust/examples/cuda/ (7 files) + cpp_integration/ (1 file)
  async_reduce, custom_temporary_allocation, explicit_cuda_stream,
  global_device_vector, range_view, unwrap_pointer, wrap_pointer, device

结果: cccl_upstream 从 74M→35M (瘦身 53%), 核心内容 100% 保留:
  27/27 tuning headers, 78 benchmarks, 243 tests,
  60 thrust examples, 18 CUB examples, 全部编译头文件

cccl_upstream/cudax/examples/stf/09-dot-reduce.cu

@@ -1,55 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-// 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.
-//
-//===----------------------------------------------------------------------===//
-
-/**
- * @file
- *
- * @brief Implementation of the DOT kernel using a reduce access mode
- *
- */
-
-#include <cuda/experimental/stf.cuh>
-
-using namespace cuda::experimental::stf;
-
-int main()
-{
-  const size_t N = 16;
-  double X[N], Y[N];
-
-  double ref_res = 0.0;
-
-  for (size_t i = 0; i < N; i++)
-  {
-    X[i] = cos(double(i));
-    Y[i] = sin(double(i));
-
-    // Compute the reference result of the DOT product of X and Y
-    ref_res += X[i] * Y[i];
-  }
-
-  context ctx;
-  auto lX = ctx.logical_data(X);
-  auto lY = ctx.logical_data(Y);
-
-  auto lsum = ctx.logical_data(shape_of<scalar_view<double>>());
-
-  /* Compute sum(x_i * y_i)*/
-  ctx.parallel_for(lY.shape(), lX.read(), lY.read(), lsum.reduce(reducer::sum<double>{}))
-      ->*[] __device__(size_t i, auto dX, auto dY, double& sum) {
-            sum += dX(i) * dY(i);
-          };
-
-  double res = ctx.wait(lsum);
-
-  ctx.finalize();
-
-  _CCCL_ASSERT(fabs(res - ref_res) < 0.0001, "Invalid result");
-}