[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/libcudacxx/test/support/MoveOnly.h

@@ -0,0 +1,99 @@
+//===----------------------------------------------------------------------===//
+//
+// Part of the LLVM Project, 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) 2023 NVIDIA CORPORATION & AFFILIATES
+//
+//===----------------------------------------------------------------------===//
+
+#ifndef MOVEONLY_H
+#define MOVEONLY_H
+
+#include <cuda/std/cstddef>
+
+#include "test_macros.h"
+// #include <functional>
+
+class MoveOnly
+{
+  int data_;
+
+public:
+  TEST_FUNC constexpr MoveOnly(int data = 1)
+      : data_(data)
+  {}
+
+  MoveOnly(const MoveOnly&)            = delete;
+  MoveOnly& operator=(const MoveOnly&) = delete;
+
+  TEST_FUNC constexpr MoveOnly(MoveOnly&& x)
+      : data_(x.data_)
+  {
+    x.data_ = 0;
+  }
+  TEST_FUNC constexpr MoveOnly& operator=(MoveOnly&& x)
+  {
+    data_   = x.data_;
+    x.data_ = 0;
+    return *this;
+  }
+
+  TEST_FUNC constexpr int get() const
+  {
+    return data_;
+  }
+
+  TEST_FUNC friend constexpr bool operator==(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ == y.data_;
+  }
+  TEST_FUNC friend constexpr bool operator!=(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ != y.data_;
+  }
+  TEST_FUNC friend constexpr bool operator<(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ < y.data_;
+  }
+  TEST_FUNC friend constexpr bool operator<=(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ <= y.data_;
+  }
+  TEST_FUNC friend constexpr bool operator>(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ > y.data_;
+  }
+  TEST_FUNC friend constexpr bool operator>=(const MoveOnly& x, const MoveOnly& y)
+  {
+    return x.data_ >= y.data_;
+  }
+
+#if TEST_STD_VER > 2017 && _LIBCUDACXX_HAS_SPACESHIP_OPERATOR()
+  TEST_FUNC friend constexpr auto operator<=>(const MoveOnly&, const MoveOnly&) = default;
+#endif // TEST_STD_VER > 2017 && _LIBCUDACXX_HAS_SPACESHIP_OPERATOR()
+
+  TEST_FUNC constexpr MoveOnly operator+(const MoveOnly& x) const
+  {
+    return MoveOnly(data_ + x.data_);
+  }
+  TEST_FUNC constexpr MoveOnly operator*(const MoveOnly& x) const
+  {
+    return MoveOnly(data_ * x.data_);
+  }
+
+  template <class T>
+  void operator,(T const&) = delete;
+};
+
+/*
+template <>
+struct cuda::std::hash<MoveOnly>
+{
+    using argument_type = MoveOnly;
+    using result_type = size_t;
+    TEST_FUNC constexpr size_t operator()(const MoveOnly& x) const {return x.get();}
+};
+*/
+
+#endif // MOVEONLY_H