Single-Source Shortest Path (SSSP) implementation in modern C++ for 2022 IPDPS workshop on Graphs, Architectures, Programming, and Learning (GrAPL 2022) submission. For a more complete implementation of the ideas presented in the paper, please refer to the on-going work of graph analytics on GPUs at gunrock/essentials.
System | Version | Status |
---|---|---|
Ubuntu | Ubuntu 20.04 | |
Windows | Windows Server 2019 |
C++20
for linux (requiresgcc/g++-10.1
or higher),C++23
for windows.cmake
version3.22.2
.tbb
library for execution policies (automatically fetched usingcmake
).
This code base makes use of modern C++ features such as ranges
, execution_policy
, and lambda expressions to implement the essential components for parallel graph analytics. We focus on a simple implementation of Single-Source Shortest Path (SSSP), but the concepts can easily be extended to support other graph algorithms such as Breadth-First Search with minor changes to the lambda expression during traversal.
[&](vertex_t const& src, // source
vertex_t const& dst, // destination
edge_t const& edge, // edge
weight_t const& weight // weight
) {
weight_t new_d = distances[src] + weight;
weight_t curr_d = atomic::min(&distances[dst], new_d, m_locks[dst]);
return new_d < curr_d;
};
[&](vertex_t const& src, // source
vertex_t const& dst, // destination
edge_t const& edge, // edge
weight_t const& weight // weight
) {
// If the neighbor is not visited, update the distance. Returning false
// here means that the neighbor is not added to the output frontier, and
// instead an invalid vertex is added in its place. These invalides (-1 in
// most cases) can be removed using a filter operator or uniquify.
if (distances[dst] != std::numeric_limits<vertex_t>::max())
return false;
else
return (atomic::cas(
&distances[dst], std::numeric_limits<vertex_t>::max(),
iteration + 1) == std::numeric_limits<vertex_t>::max(), m_locks[dst]);
};
Before building this project, make sure your system/compiler supports C++20 and cmake.
git clone https://github.com/gunrock/essentials-cpp.git
cd essentials-cpp
mkdir build && cd build
cmake ..
make
bin/sssp ../datasets/chesapeake/chesapeake.mtx
Thank you for citing our work.
@InProceedings{ Osama:2022:EOP,
author = {Muhammad Osama and Serban D. Porumbescu and John D.
Owens},
title = {Essentials of Parallel Graph Analytics},
booktitle = {Proceedings of the Workshop on Graphs, Architectures,
Programming, and Learning},
year = 2022,
series = {GrAPL 2022},
month = may
}