[INFRA] Import NVIDIA/CCCL upstream as optimization reference library

CCCL (CUDA C++ Core Libraries) provides:
- CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk)
- Thrust: high-level parallel algorithms (transform_reduce, sort, scan)
- libcudacxx: CUDA C++ standard library (atomics, barriers, memory)
- cudax: experimental features (memory resources, allocators)
- Tuning policies: per-SM hardware-specific algorithm parameters

Competition optimization vectors mapped to CCCL:
- Output TPS (83% weight): warp_reduce, block_reduce, device_topk
- Input TPS (14% weight): device_scan, block_load, prefetch
- Cache TPS (3% weight): prefix caching strategy patterns
- Memory (0.9 util): pooled/cached/buddy allocators

Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only)
License: Apache-2.0

cccl_upstream/cudax/examples/vector.cuh

@@ -0,0 +1,159 @@
+//===----------------------------------------------------------------------===//
+//
+// Part of CUDA Experimental 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) 2024 NVIDIA CORPORATION & AFFILIATES.
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef _CUDAX__CONTAINER_VECTOR
+#define _CUDAX__CONTAINER_VECTOR
+
+#include <cuda/__cccl_config>
+
+#if defined(_CCCL_IMPLICIT_SYSTEM_HEADER_GCC)
+#  pragma GCC system_header
+#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_CLANG)
+#  pragma clang system_header
+#elif defined(_CCCL_IMPLICIT_SYSTEM_HEADER_MSVC)
+#  pragma system_header
+#endif // no system header
+
+#include <thrust/device_vector.h>
+#include <thrust/host_vector.h>
+
+#include <cuda/__stream/stream_ref.h>
+#include <cuda/std/__type_traits/maybe_const.h>
+#include <cuda/std/span>
+
+#include <cuda/experimental/__detail/utility.cuh>
+#include <cuda/experimental/__launch/param_kind.cuh>
+
+#include <cstdio>
+
+namespace cuda::experimental
+{
+using ::cuda::std::span;
+using ::thrust::device_vector;
+using ::thrust::host_vector;
+
+template <typename _Ty>
+class vector
+{
+public:
+  vector() = default;
+  explicit vector(size_t __n)
+      : __h_(__n)
+  {}
+
+  _Ty& operator[](size_t __i) noexcept
+  {
+    __dirty_ = true;
+    return __h_[__i];
+  }
+
+  const _Ty& operator[](size_t __i) const noexcept
+  {
+    return __h_[__i];
+  }
+
+private:
+  void sync_host_to_device([[maybe_unused]] ::cuda::stream_ref __str, __detail::__param_kind __p) const
+  {
+    if (__dirty_)
+    {
+      if (__p == __detail::__param_kind::_out)
+      {
+        // There's no need to copy the data from host to device if the data is
+        // only going to be written to. We can just allocate the device memory.
+        __d_.resize(__h_.size());
+      }
+      else
+      {
+        // TODO: use a memcpy async here
+        __d_ = __h_;
+      }
+      __dirty_ = false;
+    }
+  }
+
+  void sync_device_to_host(::cuda::stream_ref __str, __detail::__param_kind __p) const
+  {
+    if (__p != __detail::__param_kind::_in)
+    {
+      // TODO: use a memcpy async here
+      __str.sync(); // wait for the kernel to finish executing
+      __h_ = __d_;
+    }
+  }
+
+  template <__detail::__param_kind _Kind>
+  class __action //: private __detail::__immovable
+  {
+    using __cv_vector = ::cuda::std::__maybe_const<_Kind == __detail::__param_kind::_in, vector>;
+
+  public:
+    explicit __action(::cuda::stream_ref __str, __cv_vector& __v)
+        : __str_(__str)
+        , __v_(__v)
+    {
+      __v_.sync_host_to_device(__str_, _Kind);
+    }
+
+    __action(__action&&) = delete;
+
+    ~__action()
+    {
+      try
+      {
+        __v_.sync_device_to_host(__str_, _Kind);
+      }
+      catch (const ::std::exception& e)
+      {
+        static_cast<void>(
+          ::fprintf(stderr, "Exception occurred during host to device synchronization: %s\n", e.what()));
+      }
+      catch (...)
+      {
+        static_cast<void>(::fprintf(stderr, "Unknown exception occurred during host to device synchronization\n"));
+      }
+    }
+
+    ::cuda::std::span<_Ty> transformed_argument() const
+    {
+      return {__v_.__d_.data().get(), __v_.__d_.size()};
+    }
+
+  private:
+    ::cuda::stream_ref __str_;
+    __cv_vector& __v_;
+  };
+
+  [[nodiscard]] friend __action<__detail::__param_kind::_inout>
+  transform_launch_argument(::cuda::stream_ref __str, vector& __v)
+  {
+    return __action<__detail::__param_kind::_inout>{__str, __v};
+  }
+
+  [[nodiscard]] friend __action<__detail::__param_kind::_in>
+  transform_launch_argument(::cuda::stream_ref __str, const vector& __v)
+  {
+    return __action<__detail::__param_kind::_in>{__str, __v};
+  }
+
+  template <__detail::__param_kind _Kind>
+  [[nodiscard]] friend __action<_Kind>
+  transform_launch_argument(::cuda::stream_ref __str, __detail::__box<vector, _Kind> __b)
+  {
+    return __action<_Kind>{__str, __b.__val};
+  }
+
+  mutable host_vector<_Ty> __h_;
+  mutable device_vector<_Ty> __d_{};
+  mutable bool __dirty_ = true;
+};
+} // namespace cuda::experimental
+
+#endif