seunghwak / cuCollections

cuCollections

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.

Development Status

cuCollections is still under heavy development. Users should expect breaking changes and refactoring to be common.

Getting cuCollections

cuCollections is header only and can be incorporated manually into your project by downloading the headers and placing them into your source tree.

Adding cuCollections to a CMake Project

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.

Requirements

• nvcc 10.2+
• C++14
• Volta+
  • Pascal is partially supported. Any data structures that require blocking algorithms are not supported. See libcu++ documentation for more details.

Dependencies

cuCollections depends on the following libraries:

• libcu++
• CUB

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.

Building cuCollections

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/

Data Structures

We plan to add many GPU-accelerated, concurrent data structures to cuCollections. As of now, the two flagships are variants of hash tables.

static_map

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.

dynamic_map

cuco::dynamic_map links together multiple cuco::static_maps 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.