10 citations · 17 across the 6 of their papers we have counts for
6 papers
Efficient Stepping Algorithms and Implementations for Parallel Shortest Paths
Xiaojun Dong, Yan Gu, Yihan Sun +1
In this paper, we study the single-source shortest-path (SSSP) problem with positive edge weights, which is a notoriously hard problem in the parallel context. In practice, the …
Compilation Techniques for Graph Algorithms on GPUs
Ajay Brahmakshatriya, Yunming Zhang, Changwan Hong +3
The performance of graph programs depends highly on the algorithm, the size and structure of the input graphs, as well as the features of the underlying hardware. No single set of…
Optimizing Ordered Graph Algorithms with GraphIt
Yunming Zhang, Ajay Brahmakshatriya, Xinyi Chen +4
Many graph problems can be solved using ordered parallel graph algorithms that achieve significant speedup over their unordered counterparts by reducing redundant work. This paper…
GraphIt: A High-Performance DSL for Graph Analytics
Yunming Zhang, Mengjiao Yang, Riyadh Baghdadi +3
The performance bottlenecks of graph applications depend not only on the algorithm and the underlying hardware, but also on the size and structure of the input graph. Programmers m…
Tiramisu: A Polyhedral Compiler for Expressing Fast and Portable Code
Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane +6
This paper introduces Tiramisu, a polyhedral framework designed to generate high performance code for multiple platforms including multicores, GPUs, and distributed machines. Tiram…
Making Caches Work for Graph Analytics
Yunming Zhang, Vladimir Kiriansky, Charith Mendis +2
Modern hardware systems are heavily underutilized when running large-scale graph applications. While many in-memory graph frameworks have made substantial progress in optimizing th…