34 citations · 37 across the 3 of their papers we have counts for
5 papers
HYPE: Massive Hypergraph Partitioning with Neighborhood Expansion
Christian Mayer, Ruben Mayer, Sukanya Bhowmik +2
Many important real-world applications-such as social networks or distributed data bases-can be modeled as hypergraphs. In such a model, vertices represent entities-such as users o…
Q-Graph: Preserving Query Locality in Multi-Query Graph Processing
Christian Mayer, Ruben Mayer, Jonas Grunert +2
Arising user-centric graph applications such as route planning and personalized social network analysis have initiated a shift of paradigms in modern graph processing systems towar…
ADWISE: Adaptive Window-based Streaming Edge Partitioning for High-Speed Graph Processing
Christian Mayer, Ruben Mayer, Muhammad Adnan Tariq +4
In recent years, the graph partitioning problem gained importance as a mandatory preprocessing step for distributed graph processing on very large graphs. Existing graph partitioni…
The TensorFlow Partitioning and Scheduling Problem: It's the Critical Path!
Ruben Mayer, Christian Mayer, Larissa Laich
State-of-the-art data flow systems such as TensorFlow impose iterative calculations on large graphs that need to be partitioned on heterogeneous devices such as CPUs, GPUs, and TPU…
StreamLearner: Distributed Incremental Machine Learning on Event Streams: Grand Challenge
Christian Mayer, Ruben Mayer, Majd Abdo
Today, massive amounts of streaming data from smart devices need to be analyzed automatically to realize the Internet of Things. The Complex Event Processing (CEP) paradigm promise…