Examples | Doxygen Documentation (TODO) |
---|
cuCollections
(cuco
) is an open-source, header-only library of GPU-accelerated, concurrent data structures.
Similar to how Thrust and CUB provide STL-like, GPU accelerated algorithms and primitives, cuCollections
provides STL-like concurrent data structures. cuCollections
is not a one-to-one, drop-in replacement for STL data structures like std::unordered_map
. Instead, it provides functionally similar data structures tailored for efficient use with GPUs.
cuCollections
is still under heavy development. Users should expect breaking changes and refactoring to be common.
cuCollections
is header only and can be incorporated manually into your project by downloading the headers and placing them into your source tree.
cuCollections
is designed to make it easy to include within another CMake project.
The CMakeLists.txt
exports a cuco
target that can be linked1
into a target to setup include directories, dependencies, and compile flags necessary to use cuCollections
in your project.
We recommend using CMake Package Manager (CPM) to fetch cuCollections
into your project.
With CPM, getting cuCollections
is easy:
cmake_minimum_required(VERSION 3.14 FATAL_ERROR)
include(path/to/CPM.cmake)
CPMAddPackage(
NAME cuco
GITHUB_REPOSITORY NVIDIA/cuCollections
GIT_TAG dev
OPTIONS
"BUILD_TESTS OFF"
"BUILD_BENCHMARKS OFF"
"BUILD_EXAMPLES OFF"
)
target_link_libraries(my_library cuco)
This will take care of downloading cuCollections
from GitHub and making the headers available in a location that can be found by CMake. Linking against the cuco
target will provide everything needed for cuco
to be used by the my_library
target.
1: cuCollections
is header-only and therefore there is no binary component to "link" against. The linking terminology comes from CMake's target_link_libraries
which is still used even for header-only library targets.
nvcc 11+
- C++17
- Volta+
- Pascal is partially supported. Any data structures that require blocking algorithms are not supported. See libcu++ documentation for more details.
cuCollections
depends on the following libraries:
No action is required from the user to satisfy these dependencies. cuCollections
's CMake script is configured to first search the system for these libraries, and if they are not found, to automatically fetch them from GitHub.
Since cuCollections
is header-only, there is nothing to build to use it.
To build the tests, benchmarks, and examples:
cd $CUCO_ROOT
mkdir -p build
cd build
cmake ..
make
Binaries will be built into:
build/tests/
build/gbenchmarks/
build/examples/
By default, cuCollections
uses pre-commit.ci
along with mirrors-clang-format
to automatically format the C++/CUDA files in a pull request.
Users should enable the Allow edits by maintainers
option to get auto-formatting to work.
Optionally, you may wish to setup a pre-commit
hook to automatically run clang-format
when you make a git commit. This can be done by installing pre-commit
via conda
or pip
:
conda install -c conda-forge pre_commit
pip install pre-commit
and then running:
pre-commit install
from the root of the cuCollections
repository. Now code formatting will be run each time you commit changes.
You may also wish to manually format the code:
pre-commit run clang-format --all-files
mirrors-clang-format
guarantees the correct version of clang-format
and avoids version mismatches.
Users should NOT use clang-format
directly on the command line to format the code.
We plan to add many GPU-accelerated, concurrent data structures to cuCollections
. As of now, the two flagships are variants of hash tables.
cuco::static_map
is a fixed-size hash table using open addressing with linear probing.
It provides both host, bulk APIs (example) as well as device APIs for individual operations (example (TODO)).
See the Doxygen documentation in static_map.cuh
for more detailed information.
cuco::dynamic_map
links together multiple cuco::static_map
s to provide a hash table that can grow as keys are inserted.
It currently only provides host, bulk APIs (example (TODO)).
See the Doxygen documentation in dynamic_map.cuh
for more detailed information.