[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/cpp/redundant_data.cu

@@ -1,86 +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 Ensure we can use the same logical data multiple time in a task
- */
-
-#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 diff_cnt(int n, T* x, T* y, int* delta)
-{
-  int tid      = blockIdx.x * blockDim.x + threadIdx.x;
-  int nthreads = gridDim.x * blockDim.x;
-
-  for (int ind = tid; ind < n; ind += nthreads)
-  {
-    if (y[ind] != x[ind])
-    {
-      atomicAdd(delta, 1);
-    }
-  }
-}
-
-template <typename Ctx, typename T>
-void compare_two_vectors(Ctx& ctx, logical_data<T>& a, logical_data<T>& b, int& delta)
-{
-  auto delta_cnt = ctx.logical_data(make_slice(&delta, 1));
-  const auto n   = a.shape().extent(0);
-
-  // Count the number of differences
-  ctx.task(a.read(), b.read(), delta_cnt.rw())->*[=](cudaStream_t stream, auto da, auto db, auto ddelta) {
-    diff_cnt<<<16, 128, 0, stream>>>(static_cast<int>(n), da.data_handle(), db.data_handle(), ddelta.data_handle());
-  };
-
-  // Read that value on the host
-  ctx.host_launch(delta_cnt.read())->*[&](auto /*unused*/) {};
-}
-
-static const size_t N = 12;
-
-template <class Ctx>
-void run(double (&X)[N], double (&Y)[N])
-{
-  Ctx ctx;
-  auto handle_X = ctx.logical_data(X);
-  auto handle_Y = ctx.logical_data(Y);
-
-  int ret1 = 0, ret2 = 0;
-
-  compare_two_vectors(ctx, handle_X, handle_Y, ret1);
-  compare_two_vectors(ctx, handle_X, handle_X, ret2);
-
-  ctx.finalize();
-
-  // After sync, we can inspect the returned values.
-  // First two vectors are different
-  assert(ret1 > 0);
-  // Other two vectors are equal
-  assert(ret2 == 0);
-}
-
-int main()
-{
-  double X[N], Y[N];
-
-  for (size_t ind = 0; ind < N; ind++)
-  {
-    X[ind] = 1.0 * ind;
-    Y[ind] = 2.0 * ind - 3.0;
-  }
-
-  run<stream_ctx>(X, Y);
-  run<graph_ctx>(X, Y);
-}