[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/launch_sum.cu

@@ -1,81 +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 A reduction kernel written using launch
- */
-
-#include <cuda/experimental/stf.cuh>
-
-using namespace cuda::experimental::stf;
-
-double X0(int i)
-{
-  return sin((double) i);
-}
-
-int main()
-{
-  context ctx;
-
-  const size_t N = 128 * 1024 * 1024;
-
-  std::vector<double> X(N);
-  double sum = 0.0;
-
-  double ref_sum = 0.0;
-
-  for (size_t ind = 0; ind < N; ind++)
-  {
-    X[ind] = sin((double) ind);
-    ref_sum += X[ind];
-  }
-
-  auto lX   = ctx.logical_data(&X[0], {N});
-  auto lsum = ctx.logical_data(&sum, {1});
-
-  auto number_devices = 1; //
-  auto where          = exec_place::repeat(exec_place::device(0), number_devices);
-
-  auto spec = par<16>(con<32>());
-
-  ctx.launch(spec, where, lX.read(), lsum.rw())->*[] _CCCL_DEVICE(auto th, auto x, auto sum) {
-    // Each thread computes the sum of elements assigned to it
-    double local_sum = 0.0;
-    for (size_t i = th.rank(); i < x.size(); i += th.size())
-    {
-      local_sum += x(i);
-    }
-
-    auto ti = th.inner();
-
-    __shared__ double block_sum[th.static_width(1)];
-    block_sum[ti.rank()] = local_sum;
-
-    for (size_t s = ti.size() / 2; s > 0; s /= 2)
-    {
-      ti.sync();
-      if (ti.rank() < s)
-      {
-        block_sum[ti.rank()] += block_sum[ti.rank() + s];
-      }
-    }
-
-    if (ti.rank() == 0)
-    {
-      atomicAdd(&sum(0), block_sum[0]);
-    }
-  };
-
-  ctx.finalize();
-
-  EXPECT(fabs(sum - ref_sum) < 0.0001);
-}