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
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muh-bot
14
cccl_upstream/test/cuda_smoke/CMakeLists.txt
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14
cccl_upstream/test/cuda_smoke/CMakeLists.txt
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# Simple smoke test verifying the CUDA runtime is functional (device visible,
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# kernel launch + managed-memory round-trip work). Invoked explicitly from CI
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# via ci/build_common.sh before GPU test presets run. Not registered in CTest
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# (GPU-only; CPU test presets such as thrust-cpu would pick it up otherwise).
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#
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# Declare CUDA inside this subproject only so the root project() can stay
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# CXX-only (external consumers via add_subdirectory(cccl) see no change).
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project(CCCL_CUDA_SMOKE LANGUAGES CUDA)
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cccl_get_catch2()
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cccl_add_executable(${CCCL_CUDA_SMOKE_TARGET} SOURCES cuda_runtime_smoke.cu)
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target_link_libraries(${CCCL_CUDA_SMOKE_TARGET} PRIVATE Catch2::Catch2WithMain)
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184
cccl_upstream/test/cuda_smoke/cuda_runtime_smoke.cu
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cccl_upstream/test/cuda_smoke/cuda_runtime_smoke.cu
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//===----------------------------------------------------------------------===//
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//
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// Part of CUDA C++ Core Libraries, under the Apache License v2.0 with
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// LLVM Exceptions. See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#include <cuda_runtime.h>
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#include <catch2/catch_test_macros.hpp>
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#define CUDART_REQUIRE(call) REQUIRE((call) == cudaSuccess)
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__global__ void increment_kernel(int* p, int n)
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{
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int idx = static_cast<int>(blockIdx.x * blockDim.x + threadIdx.x);
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if (idx < n)
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{
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p[idx] += 1;
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}
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}
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TEST_CASE("CUDA device is available", "[cuda_smoke]")
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{
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int device_count = 0;
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CUDART_REQUIRE(cudaGetDeviceCount(&device_count));
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REQUIRE(device_count > 0);
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CUDART_REQUIRE(cudaSetDevice(0));
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cudaDeviceProp props{};
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CUDART_REQUIRE(cudaGetDeviceProperties(&props, 0));
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REQUIRE(props.name[0] != '\0');
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REQUIRE(cudaGetLastError() == cudaSuccess);
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}
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TEST_CASE("cudaMallocManaged round-trip works", "[cuda_smoke][managed_memory]")
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{
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(void) cudaGetLastError(); // clear any pre-existing error state
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int managed_supported = 0;
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CUDART_REQUIRE(cudaDeviceGetAttribute(&managed_supported, cudaDevAttrManagedMemory, 0));
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if (!managed_supported)
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{
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SKIP("Device does not support managed memory (cudaDevAttrManagedMemory == 0).");
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}
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constexpr int n = 256;
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int* p = nullptr;
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CUDART_REQUIRE(cudaMallocManaged(&p, n * sizeof(int)));
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for (int i = 0; i < n; ++i) // host write
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{
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p[i] = i;
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}
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CUDART_REQUIRE(cudaDeviceSynchronize());
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increment_kernel<<<4, 64>>>(p, n); // device transform
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CUDART_REQUIRE(cudaGetLastError());
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CUDART_REQUIRE(cudaDeviceSynchronize());
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for (int i = 0; i < n; ++i) // host read-back
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{
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REQUIRE(p[i] == i + 1);
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}
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CUDART_REQUIRE(cudaFree(p));
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REQUIRE(cudaGetLastError() == cudaSuccess);
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}
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// smoke test for GPU memory allocation/deallocation
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TEST_CASE("cudaMalloc/cudaFree round-trip works", "[cuda_smoke][device_memory]")
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{
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(void) cudaGetLastError();
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constexpr int n = 256;
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int* d_ptr = nullptr;
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CUDART_REQUIRE(cudaMalloc(&d_ptr, n * sizeof(int)));
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REQUIRE(d_ptr != nullptr);
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int h_ins[n];
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for (int i = 0; i < n; ++i)
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{
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h_ins[i] = i;
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}
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CUDART_REQUIRE(cudaMemcpy(d_ptr, h_ins, n * sizeof(int), cudaMemcpyHostToDevice));
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increment_kernel<<<4, 64>>>(d_ptr, n);
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CUDART_REQUIRE(cudaGetLastError());
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CUDART_REQUIRE(cudaDeviceSynchronize());
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int h_outs[n];
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CUDART_REQUIRE(cudaMemcpy(h_outs, d_ptr, n * sizeof(int), cudaMemcpyDeviceToHost));
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for (int i = 0; i < n; ++i)
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{
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REQUIRE(h_outs[i] == i + 1);
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}
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CUDART_REQUIRE(cudaFree(d_ptr));
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REQUIRE(cudaGetLastError() == cudaSuccess);
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}
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// smoke test for pinned host memory
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TEST_CASE("cudaMallocHost round-trip works", "[cuda_smoke][pinned_memory]")
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{
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(void) cudaGetLastError();
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constexpr int n = 256;
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int* h_pinned = nullptr;
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CUDART_REQUIRE(cudaMallocHost(&h_pinned, n * sizeof(int)));
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REQUIRE(h_pinned != nullptr);
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int* d_ptr = nullptr;
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CUDART_REQUIRE(cudaMalloc(&d_ptr, n * sizeof(int)));
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REQUIRE(d_ptr != nullptr);
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for (int i = 0; i < n; ++i)
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{
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h_pinned[i] = i;
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}
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CUDART_REQUIRE(cudaMemcpy(d_ptr, h_pinned, n * sizeof(int), cudaMemcpyHostToDevice));
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increment_kernel<<<4, 64>>>(d_ptr, n);
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CUDART_REQUIRE(cudaGetLastError());
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CUDART_REQUIRE(cudaDeviceSynchronize());
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CUDART_REQUIRE(cudaMemcpy(h_pinned, d_ptr, n * sizeof(int), cudaMemcpyDeviceToHost));
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for (int i = 0; i < n; ++i)
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{
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REQUIRE(h_pinned[i] == i + 1);
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}
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CUDART_REQUIRE(cudaFree(d_ptr));
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CUDART_REQUIRE(cudaFreeHost(h_pinned));
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REQUIRE(cudaGetLastError() == cudaSuccess);
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}
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// smoke test for mapped pinned host memory
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TEST_CASE("cudaHostAlloc mapped (zero-copy) works", "[cuda_smoke][pinned_memory][mapped]")
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{
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(void) cudaGetLastError();
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int can_map = 0;
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CUDART_REQUIRE(cudaDeviceGetAttribute(&can_map, cudaDevAttrCanMapHostMemory, 0));
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if (!can_map)
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{
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SKIP("Device cannot map host memory (cudaDevAttrCanMapHostMemory == 0).");
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}
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constexpr int n = 256;
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int* h_mapped = nullptr;
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CUDART_REQUIRE(cudaHostAlloc(&h_mapped, n * sizeof(int), cudaHostAllocMapped));
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REQUIRE(h_mapped != nullptr);
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for (int i = 0; i < n; ++i)
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{
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h_mapped[i] = i;
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}
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int* d_view = nullptr;
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CUDART_REQUIRE(cudaHostGetDevicePointer(&d_view, h_mapped, 0));
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REQUIRE(d_view != nullptr);
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increment_kernel<<<4, 64>>>(d_view, n);
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CUDART_REQUIRE(cudaGetLastError());
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CUDART_REQUIRE(cudaDeviceSynchronize());
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for (int i = 0; i < n; ++i)
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{
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REQUIRE(h_mapped[i] == i + 1);
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}
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CUDART_REQUIRE(cudaFreeHost(h_mapped));
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REQUIRE(cudaGetLastError() == cudaSuccess);
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}
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