31 citations · 104 across the 17 of their papers we have counts for
5 papers · 1 filter
Boosting Graph Embedding on a Single GPU
Amro Alabsi Aljundi, Taha Atahan Akyıldız, Kamer Kaya
Graphs are ubiquitous, and they can model unique characteristics and complex relations of real-life systems. Although using machine learning (ML) on graphs is promising, their raw…
GOSH: Embedding Big Graphs on Small Hardware
Taha Atahan Akyildiz, Amro Alabsi Aljundi, Kamer Kaya
In graph embedding, the connectivity information of a graph is used to represent each vertex as a point in a d-dimensional space. Unlike the original, irregular structural informat…
Boosting Parallel Influence-Maximization Kernels for Undirected Networks with Fusing and Vectorization
Gokhan Gokturk, Kamer Kaya
Influence maximization (IM) is the problem of finding a seed vertex set which is expected to incur the maximum influence spread on a graph. It has various applications in practice…
Greed is Good: Optimistic Algorithms for Bipartite-Graph Partial Coloring on Multicore Architectures
Mustafa Kemal Taş, Kamer Kaya, Erik Saule
In parallel computing, a valid graph coloring yields a lock-free processing of the colored tasks, data points, etc., without expensive synchronization mechanisms. However, coloring…
GPU accelerated maximum cardinality matching algorithms for bipartite graphs
Mehmet Deveci, Kamer Kaya, Bora Ucar +1
We design, implement, and evaluate GPU-based algorithms for the maximum cardinality matching problem in bipartite graphs. Such algorithms have a variety of applications in computer…