feat(cccl): integrate missing CCCL directories — python/, ci/, .agent/, docs/, test/

Sparse-checkout from NVIDIA/cccl main branch to complete cccl_upstream:

Added:
- python/cuda_cccl/ (226 files) — Python bindings for device-level algorithms
  Critical for muh toolchain: cuda.compute.reduce_into, scan, radix_sort, etc.
  Includes 204 .py files with full test coverage for all 27 algorithms
- ci/ (163 files) — Build/test infrastructure
  build_cub.sh, test_cub.sh, build_and_test_targets.sh, matrix.yaml
  Directly maps to our [INFRA-CI] and [INFRA-BUILD] items
- .agent/skills/ (7 files) — NVIDIA's own agent skills for CCCL
  cccl-style/SKILL.md, cccl-test/SKILL.md, sass-diff/SKILL.md
- docs/ (491 files) — Official CCCL documentation
  CI references, CMake guides, Python compute docs, libcudacxx PTX docs
- test/ (12 files) — Top-level integration tests (cuda_smoke, stdpar)
- Root configs: .clang-format, .clang-tidy, CONTRIBUTING.md, pyproject.toml
- CLAUDE.md symlink → AGENTS.md (NVIDIA's standard)

cccl_upstream now mirrors full NVIDIA/cccl structure:
  Before: 42M (cub + thrust + libcudacxx + cudax + c + examples + benchmarks)
  After:  53M (+python +ci +docs +.agent +test +configs)

This completes the CCCL base needed for:
- [muh-bench] items: ci/util/build_and_test_targets.sh for targeted builds
- [CCCL-verify] items: python/cuda_cccl/tests/ as reference implementations
- [CCCL-test] items: ci/test_cub.sh, ci/test_thrust.sh
- Agent workflow: .agent/skills/ for consistent style and test patterns

cccl_upstream/python/cuda_cccl/benchmarks/compute/host/test_host_pytest_benchmark.py

@@ -0,0 +1,95 @@
+# Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. ALL RIGHTS RESERVED.
+#
+# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+from __future__ import annotations
+
+import pytest
+from host_benchmark_cases import (
+    CALL_CASES,
+    CASES,
+    HostBenchmarkCase,
+    patch_wrapper_to_skip_native_compute,
+    synchronize,
+)
+
+import cuda.compute as cc
+
+pytest.importorskip("pytest_benchmark")
+
+BUILD_TIME_ROUNDS = 10
+ONESHOT_ROUNDS = 20
+ONESHOT_ITERATIONS = 100
+TWOSHOT_ROUNDS = 20
+TWOSHOT_ITERATIONS = 1000
+
+
+def _case_params(cases: list[HostBenchmarkCase]) -> list[pytest.ParameterSet]:
+    params = []
+    for case in cases:
+        marks = []
+        if case.skip_reason is not None:
+            marks.append(pytest.mark.skip(reason=case.skip_reason))
+        params.append(pytest.param(case, id=case.name, marks=marks))
+    return params
+
+
+@pytest.mark.benchmark(group="cuda.compute.host.build_time")
+@pytest.mark.parametrize("case", _case_params(CASES))
+def test_build_time(benchmark, case: HostBenchmarkCase):
+    state = case.setup()
+    synchronize()
+
+    def setup() -> None:
+        cc.clear_all_caches()
+
+    def build():
+        return case.make_wrapper(state)
+
+    benchmark.pedantic(
+        build,
+        setup=setup,
+        rounds=BUILD_TIME_ROUNDS,
+        iterations=1,
+        warmup_rounds=0,
+    )
+
+
+@pytest.mark.benchmark(group="cuda.compute.host.oneshot_cached")
+@pytest.mark.parametrize("case", _case_params(CALL_CASES))
+def test_oneshot_cached_host_overhead(benchmark, case: HostBenchmarkCase):
+    cc.clear_all_caches()
+    state = case.setup()
+    wrapper = case.make_wrapper(state)
+    patch_wrapper_to_skip_native_compute(wrapper, case.noop_return_kind)
+    synchronize()
+
+    def call() -> None:
+        case.oneshot(state)
+
+    benchmark.pedantic(
+        call,
+        rounds=ONESHOT_ROUNDS,
+        iterations=ONESHOT_ITERATIONS,
+        warmup_rounds=0,
+    )
+
+
+@pytest.mark.benchmark(group="cuda.compute.host.twoshot_call")
+@pytest.mark.parametrize("case", _case_params(CALL_CASES))
+def test_twoshot_call_host_overhead(benchmark, case: HostBenchmarkCase):
+    cc.clear_all_caches()
+    state = case.setup()
+    wrapper = case.make_wrapper(state)
+    patch_wrapper_to_skip_native_compute(wrapper, case.noop_return_kind)
+    synchronize()
+
+    def call() -> None:
+        case.twoshot(state, wrapper)
+
+    benchmark.pedantic(
+        call,
+        rounds=TWOSHOT_ROUNDS,
+        iterations=TWOSHOT_ITERATIONS,
+        warmup_rounds=0,
+    )