[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/stf/logical_gates_composition.cu

@@ -0,0 +1,73 @@
+//===----------------------------------------------------------------------===//
+//
+// 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 Composition of boolean operations applied on logical data
+ */
+
+#include <cuda/experimental/stf.cuh>
+
+using namespace cuda::experimental::stf;
+
+// z = AND(x,y)
+logical_data<slice<int>> AND(context& ctx, logical_data<slice<int>> x, logical_data<slice<int>> y)
+{
+  assert(x.shape().size() == y.shape().size());
+
+  auto z = ctx.logical_data(x.shape());
+
+  std::string symbol = "(" + x.get_symbol() + " & " + y.get_symbol() + ")";
+  z.set_symbol(symbol);
+
+  ctx.parallel_for(z.shape(), x.read(), y.read(), z.write()).set_symbol("AND")->*
+    [] __device__(size_t i, auto dx, auto dy, auto dz) {
+      dz(i) = dx(i) & dy(i);
+    };
+
+  return z;
+}
+
+// y = NOT(x)
+logical_data<slice<int>> NOT(context& ctx, logical_data<slice<int>> x)
+{
+  auto y = ctx.logical_data(x.shape());
+
+  std::string symbol = "( !" + x.get_symbol() + ")";
+  y.set_symbol(symbol);
+
+  ctx.parallel_for(y.shape(), x.read(), y.write()).set_symbol("NOT")->*[] __device__(size_t i, auto dx, auto dy) {
+    dy(i) = ~dx(i);
+  };
+
+  return y;
+}
+
+int main()
+{
+  const size_t n = 12;
+
+  int X[n], Y[n], Z[n];
+
+  context ctx;
+
+  auto lX = ctx.logical_data(X);
+  auto lY = ctx.logical_data(Y);
+  auto lZ = ctx.logical_data(Z);
+
+  lX.set_symbol("X");
+  lY.set_symbol("Y");
+  lZ.set_symbol("Z");
+
+  auto lB = AND(ctx, AND(ctx, lX, lY), AND(ctx, lX, lZ));
+  auto lC = AND(ctx, NOT(ctx, AND(ctx, lB, NOT(ctx, lY))), lX);
+
+  ctx.finalize();
+}