Skip to content

Latest commit

 

History

History
257 lines (181 loc) · 45.9 KB

README.md

File metadata and controls

257 lines (181 loc) · 45.9 KB
Raw

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.

Major Updates

01/08/2024 Deprecated the experimental namespace

01/02/2024 Moved the legacy static_map to cuco::legacy namespace

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 3.23.1 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 11.5+
  • C++17
  • 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:

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 .. # configure
make # build
ctest --test-dir tests # run tests

Binaries will be built into:

  • build/tests/
  • build/benchmarks/
  • build/examples/

Build Script:

Alternatively, you can use the build script located at ci/build.sh. Calling this script with no arguments will trigger a full build which will be located at build/local.

cd $CUCO_ROOT
ci/build.sh # configure and build
ctest --test-dir build/local/tests # run tests

For a comprehensive list of all available options along with descriptions and examples, you can use the option ci/build.sh -h.

Code Formatting

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.

Pre-commit hook

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

Caveats

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.

Documentation

Doxygen is used to generate HTML pages from the C++/CUDA comments in the source code.

The example

The following example covers most of the Doxygen block comment and tag styles for documenting C++/CUDA code in cuCollections.

/**
 * @file source_file.cpp
 * @brief Description of source file contents
 *
 * Longer description of the source file contents.
 */

/**
 * @brief Short, one sentence description of the class.
 *
 * Longer, more detailed description of the class.
 *
 * A detailed description must start after a blank line.
 *
 * @tparam T Short description of each template parameter
 * @tparam U Short description of each template parameter
 */
template <typename T, typename U>
class example_class {

  void get_my_int();            ///< Simple members can be documented like this
  void set_my_int( int value ); ///< Try to use descriptive member names

  /**
   * @brief Short, one sentence description of the member function.
   *
   * A more detailed description of what this function does and what
   * its logic does.
   *
   * @param[in]     first  This parameter is an input parameter to the function
   * @param[in,out] second This parameter is used both as an input and output
   * @param[out]    third  This parameter is an output of the function
   *
   * @return The result of the complex function
   */
  T complicated_function(int first, double* second, float* third)
  {
      // Do not use doxygen-style block comments
      // for code logic documentation.
  }

 private:
  int my_int;                ///< An example private member variable
};

Doxygen style check

cuCollections also uses Doxygen as a documentation linter. To check the Doxygen style locally, run

./ci/pre-commit/doxygen.sh

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_set

cuco::static_set is a fixed-size container that stores unique elements in no particular order. See the Doxygen documentation in static_set.cuh for more detailed information.

Examples:

static_map

cuco::static_map is a fixed-size hash table using open addressing with linear probing. See the Doxygen documentation in static_map.cuh for more detailed information.

Examples:

static_multimap

cuco::static_multimap is a fixed-size hash table that supports storing equivalent keys. It uses double hashing by default and supports switching to linear probing. See the Doxygen documentation in static_multimap.cuh for more detailed information.

Examples:

static_multiset

cuco::static_multiset is a fixed-size container that supports storing equivalent keys. It uses double hashing by default and supports switching to linear probing. See the Doxygen documentation in static_multiset.cuh for more detailed information.

Examples:

dynamic_map

cuco::dynamic_map links together multiple cuco::static_maps to provide a hash table that can grow as key-value pairs are inserted. It currently only provides host-bulk APIs. See the Doxygen documentation in dynamic_map.cuh for more detailed information.

Examples:

hyperloglog

cuco::hyperloglog implements the well-established HyperLogLog++ algorithm for approximating the count of distinct items in a multiset/stream.

Examples:

bloom_filter

cuco::bloom_filter implements a Blocked Bloom Filter for approximate set membership queries.

Examples: