[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/concurrency_test.cu

@@ -1,98 +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.cuh>
-
-/*
- * The goal of this test is to ensure that using read access modes actually
- * results in concurrent tasks
- */
-
-using namespace cuda::experimental::stf;
-
-/**
- * @brief Call `__nanosleep` (potentially repeatedly) to sleep `nanoseconds` nanoseconds. Supports sleep times longer
- * than 4 billion nanoseconds (i.e. 4 seconds).
- *
- * @param nanoseconds how many nanoseconds to sleep
- * @return void
- */
-__global__ void nano_sleep(unsigned long long nanoseconds)
-{
-#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 700)
-  static constexpr auto m = std::numeric_limits<unsigned int>::max();
-  for (;;)
-  {
-    if (nanoseconds > m)
-    {
-      __nanosleep(m);
-      nanoseconds -= m;
-    }
-    else
-    {
-      __nanosleep(static_cast<unsigned int>(nanoseconds));
-      break;
-    }
-  }
-#else
-  const clock_t end = clock() + nanoseconds / (1000000000ULL / CLOCKS_PER_SEC);
-  while (clock() < end)
-  {
-    // busy wait
-  }
-#endif
-}
-
-void run(context& ctx, int NTASKS, int ms)
-{
-  int dummy[1];
-  auto handle = ctx.logical_data(dummy);
-
-  ctx.task().add_deps(handle.rw())->*[](cudaStream_t stream) {
-    nano_sleep<<<1, 1, 0, stream>>>(0);
-  };
-
-  for (int iter = 0; iter < 10; iter++)
-  {
-    for (int k = 0; k < NTASKS; k++)
-    {
-      ctx.task().add_deps(handle.read())->*[&](cudaStream_t stream) {
-        nano_sleep<<<1, 1, 0, stream>>>(ms * 1000ULL * 1000ULL);
-      };
-    }
-
-    ctx.task().add_deps(handle.rw())->*[&](cudaStream_t stream) {
-      nano_sleep<<<1, 1, 0, stream>>>(0);
-    };
-  }
-
-  ctx.finalize();
-}
-
-int main(int argc, char** argv)
-{
-  int NTASKS = 256;
-  int ms     = 40;
-
-  if (argc > 1)
-  {
-    NTASKS = atoi(argv[1]);
-  }
-
-  if (argc > 2)
-  {
-    ms = atoi(argv[2]);
-  }
-
-  context ctx;
-  run(ctx, NTASKS, ms);
-  ctx = graph_ctx();
-  run(ctx, NTASKS, ms);
-}