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project_6/cccl_upstream/examples/cudax/CMakeLists.txt
EngineX CI 56fd68e7dd [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
2026-07-30 09:35:51 +00:00

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CMake

# SPDX-FileCopyrightText: Copyright (c) 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
cmake_minimum_required(VERSION 3.18 FATAL_ERROR)
project(CUDAX_SAMPLES CUDA CXX)
# This example uses the CMake Package Manager (CPM) to simplify fetching CCCL from GitHub
# For more information, see https://github.com/cpm-cmake/CPM.cmake
include(cmake/CPM.cmake)
# We define these as variables so they can be overridden in CI to pull from a PR instead of CCCL `main`
# In your project, these variables are unnecessary and you can just use the values directly
set(
CCCL_REPOSITORY
"https://github.com/NVIDIA/cccl"
CACHE STRING
"Git repository to fetch CCCL from"
)
set(CCCL_TAG "main" CACHE STRING "Git tag/branch to fetch from CCCL repository")
# This will automatically clone CCCL from GitHub and make the exported cmake targets available
CPMAddPackage(
NAME CCCL
GIT_REPOSITORY "${CCCL_REPOSITORY}"
GIT_TAG ${CCCL_TAG}
GIT_SHALLOW ON
# The following is required to make the `CCCL::cudax` target available:
OPTIONS "CCCL_ENABLE_UNSTABLE ON"
)
# Default to building for the GPU on the current system
if (NOT DEFINED CMAKE_CUDA_ARCHITECTURES)
set(CMAKE_CUDA_ARCHITECTURES native)
endif()
add_library(cudax_samples_interface INTERFACE)
target_link_libraries(cudax_samples_interface INTERFACE CCCL::CCCL CCCL::cudax)
if ("MSVC" STREQUAL "${CMAKE_CXX_COMPILER_ID}")
# mdspan on windows only works in C++20 mode
target_compile_features(cudax_samples_interface INTERFACE cxx_std_20)
if (MSVC_TOOLSET_VERSION LESS 143)
# winbase.h(9572): warning C5105: macro expansion producing 'defined' has undefined behavior
target_compile_options(
cudax_samples_interface
INTERFACE
$<$<COMPILE_LANGUAGE:CXX>:/wd5105>
$<$<COMPILE_LANG_AND_ID:CUDA,NVIDIA>:-Xcompiler=/wd5105>
)
endif()
endif()
# The vector_add sample demonstrates a simple CUDA kernel that adds two vectors
add_executable(vector_add vector_add/vector_add.cu)
target_link_libraries(vector_add PUBLIC cudax_samples_interface)
# This is only relevant for internal testing and not needed by end users.
include(CTest)
enable_testing()
add_test(NAME vector_add COMMAND vector_add)