[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/test/stf/interface/scal.cu

@@ -1,71 +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.
-//
-//===----------------------------------------------------------------------===//
-
-#include <cuda/experimental/__stf/graph/graph_ctx.cuh>
-#include <cuda/experimental/__stf/stream/stream_ctx.cuh>
-
-using namespace cuda::experimental::stf;
-
-template <typename T>
-__global__ void scal(size_t n, T a, T* x)
-{
-  int tid      = blockIdx.x * blockDim.x + threadIdx.x;
-  int nthreads = gridDim.x * blockDim.x;
-
-  for (size_t ind = tid; ind < n; ind += nthreads)
-  {
-    x[ind] = a * x[ind];
-  }
-}
-
-double x_init(int i)
-{
-  return cos((double) i);
-}
-
-template <typename Ctx>
-void run()
-{
-  Ctx ctx;
-  const int n = 4096;
-  double X[n];
-
-  for (int ind = 0; ind < n; ind++)
-  {
-    X[ind] = x_init(ind);
-  }
-
-  auto handle_X = ctx.logical_data(X);
-
-  double alpha = 2.0;
-  int niter    = 4;
-  for (int iter = 0; iter < niter; iter++)
-  {
-    ctx.task(handle_X.rw())->*[&](cudaStream_t s, auto sX) {
-      scal<<<16, 128, 0, s>>>(sX.size(), alpha, sX.data_handle());
-    };
-  }
-
-  // Ask to use Y on the host
-  ctx.host_launch(handle_X.read())->*[&](auto sX) {
-    for (int ind = 0; ind < n; ind++)
-    {
-      EXPECT(fabs(sX(ind) - pow(alpha, niter) * (x_init(ind))) < 0.00001);
-    }
-  };
-
-  ctx.finalize();
-}
-
-int main()
-{
-  run<stream_ctx>();
-  run<graph_ctx>();
-}