[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/thrust/examples/arbitrary_transformation.cu

@@ -0,0 +1,93 @@
+#include <thrust/detail/config.h>
+
+#include <thrust/device_vector.h>
+#include <thrust/for_each.h>
+#include <thrust/iterator/zip_iterator.h>
+#include <thrust/zip_function.h>
+
+#include <iostream>
+
+// This example shows how to implement an arbitrary transformation of
+// the form output[i] = F(first[i], second[i], third[i], ... ).
+// In this example, we use a function with 3 inputs and 1 output.
+//
+// Iterators for all four vectors (3 inputs + 1 output) are "zipped"
+// into a single sequence of tuples with the zip_iterator.
+//
+// The arbitrary_functor receives a tuple that contains four elements,
+// which are references to values in each of the four sequences. When we
+// access the tuple 't' with the get() function,
+//      get<0>(t) returns a reference to A[i],
+//      get<1>(t) returns a reference to B[i],
+//      get<2>(t) returns a reference to C[i],
+//      get<3>(t) returns a reference to D[i].
+//
+// In this example, we can implement the transformation,
+//      D[i] = A[i] + B[i] * C[i];
+// by invoking arbitrary_functor() on each of the tuples using for_each.
+//
+// If we are using a functor that is not designed for zip iterators by taking a
+// tuple instead of individual arguments we can adapt this function using the
+// zip_function adaptor (C++11 only).
+//
+// Note that we could extend this example to implement functions with an
+// arbitrary number of input arguments by zipping more sequence together.
+// With the same approach we can have multiple *output* sequences, if we
+// wanted to implement something like
+//      D[i] = A[i] + B[i] * C[i];
+//      E[i] = A[i] + B[i] + C[i];
+//
+// The possibilities are endless! :)
+
+struct arbitrary_functor1
+{
+  template <typename Tuple>
+  __host__ __device__ void operator()(Tuple t)
+  {
+    // D[i] = A[i] + B[i] * C[i];
+    cuda::std::get<3>(t) = cuda::std::get<0>(t) + cuda::std::get<1>(t) * cuda::std::get<2>(t);
+  }
+};
+
+struct arbitrary_functor2
+{
+  __host__ __device__ void operator()(const float& a, const float& b, const float& c, float& d)
+  {
+    // D[i] = A[i] + B[i] * C[i];
+    d = a + b * c;
+  }
+};
+
+int main()
+{
+  // allocate and initialize
+  thrust::device_vector<float> A{3, 4, 0, 8, 2};
+  thrust::device_vector<float> B{6, 7, 2, 1, 8};
+  thrust::device_vector<float> C{2, 5, 7, 4, 3};
+  thrust::device_vector<float> D1(5);
+
+  // apply the transformation
+  thrust::for_each(thrust::make_zip_iterator(A.begin(), B.begin(), C.begin(), D1.begin()),
+                   thrust::make_zip_iterator(A.end(), B.end(), C.end(), D1.end()),
+                   arbitrary_functor1());
+
+  // print the output
+  std::cout << "Tuple functor" << '\n';
+  for (size_t i = 0; i < A.size(); i++)
+  {
+    std::cout << A[i] << " + " << B[i] << " * " << C[i] << " = " << D1[i] << '\n';
+  }
+
+  // apply the transformation using zip_function
+  thrust::device_vector<float> D2(5);
+  thrust::for_each(thrust::make_zip_iterator(A.begin(), B.begin(), C.begin(), D2.begin()),
+                   thrust::make_zip_iterator(A.end(), B.end(), C.end(), D2.end()),
+                   thrust::make_zip_function(arbitrary_functor2()));
+
+  // print the output
+  std::cout << "N-ary functor" << '\n';
+  for (size_t i = 0; i < A.size(); i++)
+  {
+    std::cout << A[i] << " + " << B[i] << " * " << C[i] << " = " << D2[i] << '\n';
+  }
+}