[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/standalone-launches.cu

@@ -1,77 +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 This test illustrates how we can use multiple reserved::launch in a single task on different pieces of data
- */
-
-#include <cuda/experimental/stf.cuh>
-
-using namespace cuda::experimental::stf;
-
-int X0(int i)
-{
-  return i * i + 12;
-}
-
-int main()
-{
-  stream_ctx ctx;
-
-  const int N = 16;
-  int X[N], Y[N], Z[N];
-
-  for (size_t ind = 0; ind < N; ind++)
-  {
-    X[ind] = X0(ind);
-    Y[ind] = 0;
-    Z[ind] = 0;
-  }
-
-  auto handle_X = ctx.logical_data(X, {N});
-  auto handle_Y = ctx.logical_data(Y, {N});
-  auto handle_Z = ctx.logical_data(Z, {N});
-
-  ctx.task(handle_X.read(), handle_Y.write(), handle_Z.write())
-      ->*[](cudaStream_t s, slice<const int> x, slice<int> y, slice<int> z) {
-            std::vector<cudaStream_t> streams;
-            streams.push_back(s);
-            auto spec = par(1024);
-            reserved::launch(spec, exec_place::current_device(), streams, std::tuple{x, y})
-                ->*[] _CCCL_DEVICE(auto t, slice<const int> x, slice<int> y) {
-                      size_t tid      = t.rank();
-                      size_t nthreads = t.size();
-                      for (size_t ind = tid; ind < N; ind += nthreads)
-                      {
-                        y(ind) = 2 * x(ind);
-                      }
-                    };
-
-            reserved::launch(spec, exec_place::current_device(), streams, std::tuple{y, z})
-                ->*[] _CCCL_DEVICE(auto t, slice<int> y, slice<int> z) {
-                      size_t tid      = t.rank();
-                      size_t nthreads = t.size();
-                      for (size_t ind = tid; ind < N; ind += nthreads)
-                      {
-                        z(ind) = 3 * y(ind);
-                      }
-                    };
-          };
-
-  ctx.finalize();
-
-  for (size_t ind = 0; ind < N; ind++)
-  {
-    assert(Y[ind] == 2 * X[ind]);
-    assert(Z[ind] == 3 * Y[ind]);
-  }
-}