[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/test/stf/cpp/concurrency_test.cu

@@ -0,0 +1,98 @@
+//===----------------------------------------------------------------------===//
+//
+// 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.
+//
+//===----------------------------------------------------------------------===//
+
+#include <cuda/experimental/stf.cuh>
+
+/*
+ * The goal of this test is to ensure that using read access modes actually
+ * results in concurrent tasks
+ */
+
+using namespace cuda::experimental::stf;
+
+/**
+ * @brief Call `__nanosleep` (potentially repeatedly) to sleep `nanoseconds` nanoseconds. Supports sleep times longer
+ * than 4 billion nanoseconds (i.e. 4 seconds).
+ *
+ * @param nanoseconds how many nanoseconds to sleep
+ * @return void
+ */
+__global__ void nano_sleep(unsigned long long nanoseconds)
+{
+#if defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 700)
+  static constexpr auto m = std::numeric_limits<unsigned int>::max();
+  for (;;)
+  {
+    if (nanoseconds > m)
+    {
+      __nanosleep(m);
+      nanoseconds -= m;
+    }
+    else
+    {
+      __nanosleep(static_cast<unsigned int>(nanoseconds));
+      break;
+    }
+  }
+#else
+  const clock_t end = clock() + nanoseconds / (1000000000ULL / CLOCKS_PER_SEC);
+  while (clock() < end)
+  {
+    // busy wait
+  }
+#endif
+}
+
+void run(context& ctx, int NTASKS, int ms)
+{
+  int dummy[1];
+  auto handle = ctx.logical_data(dummy);
+
+  ctx.task().add_deps(handle.rw())->*[](cudaStream_t stream) {
+    nano_sleep<<<1, 1, 0, stream>>>(0);
+  };
+
+  for (int iter = 0; iter < 10; iter++)
+  {
+    for (int k = 0; k < NTASKS; k++)
+    {
+      ctx.task().add_deps(handle.read())->*[&](cudaStream_t stream) {
+        nano_sleep<<<1, 1, 0, stream>>>(ms * 1000ULL * 1000ULL);
+      };
+    }
+
+    ctx.task().add_deps(handle.rw())->*[&](cudaStream_t stream) {
+      nano_sleep<<<1, 1, 0, stream>>>(0);
+    };
+  }
+
+  ctx.finalize();
+}
+
+int main(int argc, char** argv)
+{
+  int NTASKS = 256;
+  int ms     = 40;
+
+  if (argc > 1)
+  {
+    NTASKS = atoi(argv[1]);
+  }
+
+  if (argc > 2)
+  {
+    ms = atoi(argv[2]);
+  }
+
+  context ctx;
+  run(ctx, NTASKS, ms);
+  ctx = graph_ctx();
+  run(ctx, NTASKS, ms);
+}