[CCCL] Add missing CCCL components: c2h, nvbench_helper, cmake, cudax, AGENTS.md

Added 863 files from NVIDIA/cccl sparse checkout:
- c2h/ (27 files): Catch2 test helpers — generators, validators, runner
- nvbench_helper/ (10 files): Benchmark harness utilities
- cmake/ (29 files): CMake presets and build helpers
- cudax/ (794 files): Experimental CUDA extensions
- AGENTS.md: NVIDIA's official AI agent instructions for CCCL
- CMakePresets.json: Standardized build configurations
- cccl-version.json: Version tracking

Also added CCCL_ASSET_MAP.md mapping all 4295 CCCL files to
competition value and PRD items.

cccl_upstream now covers 100% of competition-critical assets:
- 27 tuning headers (SM80/90/100 benchmark data)
- 32 dispatch headers (algorithm implementations)
- 60 Thrust examples (correctness verification)
- 217 CUB Catch2 tests (regression matrix)
- 153 CUB benchmarks (parameter space search)
- 18 CUB examples (API verification)
- 27 test helpers + benchmark harness
- 794 cudax experimental extensions

cccl_upstream/cudax/examples/stf/03-temporary-data.cu

@@ -0,0 +1,69 @@
+//===----------------------------------------------------------------------===//
+//
+// 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 This example illustrates how we can create temporary data from shapes, and use them in tasks
+ */
+
+#include <cuda/experimental/stf.cuh>
+
+using namespace cuda::experimental::stf;
+
+int main()
+{
+  const int n = 4096;
+  int X[n];
+  int Y[n];
+
+  for (size_t i = 0; i < n; i++)
+  {
+    X[i] = 3 * i;
+    Y[i] = 2 * i - 3;
+  }
+
+  context ctx;
+
+  auto lX = ctx.logical_data(X);
+  auto lY = ctx.logical_data(Y);
+
+  // Select an odd number
+  int niter = 19;
+  assert(niter % 2 == 1);
+
+  for (int iter = 0; iter < niter; iter++)
+  {
+    // We here define a temporary vector with the same shape as X, for which there is no existing copy
+    // This data handle has a limited scope, so that it is automatically destroyed at each iteration of the loop
+    auto tmp = ctx.logical_data(lX.shape());
+
+    ctx.task(lY.rw(), lX.rw(), tmp.write())->*[](cudaStream_t s, auto sY, auto sX, auto sTMP) {
+      // We swap X and Y using TMP as temporary buffer
+      // TMP = X
+      cuda_safe_call(
+        cudaMemcpyAsync(sTMP.data_handle(), sX.data_handle(), n * sizeof(int), cudaMemcpyDeviceToDevice, s));
+      // X = Y
+      cuda_safe_call(cudaMemcpyAsync(sX.data_handle(), sY.data_handle(), n * sizeof(int), cudaMemcpyDeviceToDevice, s));
+      // Y = TMP
+      cuda_safe_call(
+        cudaMemcpyAsync(sY.data_handle(), sTMP.data_handle(), n * sizeof(int), cudaMemcpyDeviceToDevice, s));
+    };
+  }
+
+  ctx.finalize();
+
+  // We have exchanged an odd number of times, so they must be inverted
+  for (size_t i = 0; i < n; i++)
+  {
+    assert(X[i] == 2 * i - 3);
+    assert(Y[i] == 3 * i);
+  }
+}