[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/scalar_div.cu

@@ -1,124 +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;
-
-static __global__ void scalar_div(const double* a, const double* b, double* c)
-{
-  *c = (*a) / (*b);
-}
-
-static __global__ void scalar_minus(const double* a, double* res)
-{
-  *res = -(*a);
-}
-
-/**
- * This class is an example of class to issue tasks when accessing a scalar
- * value.
- *
- * This is not meant to be the most efficient approach, but this is
- * supposedly convenient.
- *
- */
-template <typename Ctx>
-class scalar
-{
-public:
-  scalar(Ctx* ctx, bool is_tmp = false)
-      : ctx(ctx)
-  {
-    size_t s = sizeof(double);
-
-    if (is_tmp)
-    {
-      // There is no physical backing for this temporary vector
-      h_addr = NULL;
-    }
-    else
-    {
-      h_addr = (double*) malloc(s);
-      cuda_safe_call(cudaHostRegister(h_addr, s, cudaHostRegisterPortable));
-    }
-
-    data_place d = is_tmp ? data_place::invalid() : data_place::host();
-    handle       = ctx->logical_data(make_slice(h_addr), d);
-  }
-
-  // Copy constructor
-  scalar(const scalar& a)
-      : ctx(a.ctx)
-  {
-    h_addr = NULL;
-    handle = ctx->logical_data(make_slice((double*) nullptr));
-
-    ctx->task(handle.write(), a.handle.read())->*[](cudaStream_t stream, auto dst, auto src) {
-      // There are likely much more efficient ways.
-      cuda_safe_call(
-        cudaMemcpyAsync(dst.data_handle(), src.data_handle(), sizeof(double), cudaMemcpyDeviceToDevice, stream));
-    };
-  }
-
-  scalar operator/(scalar const& rhs) const
-  {
-    // Submit a task that computes this/rhs
-    scalar res(ctx);
-
-    ctx->task(handle.read(), rhs.handle.read(), res.handle.write())
-        ->*[](cudaStream_t stream, auto x, auto y1, auto result) {
-              scalar_div<<<1, 1, 0, stream>>>(x.data_handle(), y1.data_handle(), result.data_handle());
-            };
-
-    return res;
-  }
-
-  scalar operator-() const
-  {
-    // Submit a task that computes -s
-    scalar res(ctx);
-    ctx->task(handle.read(), res.handle.write())->*[](cudaStream_t stream, auto x, auto result) {
-      scalar_minus<<<1, 1, 0, stream>>>(x.data_handle(), result.data_handle());
-    };
-
-    return res;
-  }
-
-  Ctx* ctx;
-  mutable logical_data<slice<double, 0>> handle;
-  double* h_addr;
-};
-
-template <typename Ctx>
-void run()
-{
-  Ctx ctx;
-  scalar a(&ctx);
-  scalar b(&ctx);
-
-  *a.h_addr = 42.0;
-  *b.h_addr = 12.3;
-
-  scalar c = (-a) / b;
-
-  ctx.host_launch(c.handle.read())->*[](auto x) {
-    EXPECT(fabs(*x.data_handle() - (-42.0) / 12.3) < 0.001);
-  };
-
-  ctx.finalize();
-}
-
-int main()
-{
-  run<stream_ctx>();
-  run<graph_ctx>();
-}