7 citations · 8 across the 10 of their papers we have counts for
13 papers
BuffCut: Prioritized Buffered Streaming Graph Partitioning
Linus Baumgärtner, Adil Chhabra, Marcelo Fonseca Faraj +1
Streaming graph partitioners enable resource-efficient and massively scalable partitioning, but one-pass assignment heuristics are highly sensitive to stream order and often yield…
Buffered Streaming Edge Partitioning
Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz +1
Addressing the challenges of processing massive graphs, which are prevalent in diverse fields such as social, biological, and technical networks, we introduce HeiStreamE and Freigh…
Engineering Weighted Connectivity Augmentation Algorithms
Marcelo Fonseca Faraj, Ernestine Großmann, Felix Joos +2
Increasing the connectivity of a graph is a pivotal challenge in robust network design. The weighted connectivity augmentation problem is a common version of the problem that takes…
Open Problems in (Hyper)Graph Decomposition
Deepak Ajwani, Rob H. Bisseling, Katrin Casel +26
Large networks are useful in a wide range of applications. Sometimes problem instances are composed of billions of entities. Decomposing and analyzing these structures helps us gai…
Streaming, Local, and Multi-Level (Hyper)Graph Decomposition
Marcelo Fonseca Faraj
(Hyper)Graph decomposition is a family of problems that aim to break down large (hyper)graphs into smaller sub(hyper)graphs for easier analysis. The importance of this lies in its…
FREIGHT: Fast Streaming Hypergraph Partitioning
Kamal Eyubov, Marcelo Fonseca Faraj, Christian Schulz
Partitioning the vertices of a (hyper)graph into k roughly balanced blocks such that few (hyper)edges run between blocks is a key problem for large-scale distributed processing. A…
Faster Local Motif Clustering via Maximum Flows
Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz
Local clustering aims to identify a cluster within a given graph that includes a designated seed node or a significant portion of a group of seed nodes. This cluster should be well…
Scalable Multilevel and Memetic Signed Graph Clustering
Felix Hausberger, Marcelo Fonseca Faraj, Christian Schulz
In this study, we address the complex issue of graph clustering in signed graphs, which are characterized by positive and negative weighted edges representing attraction and repuls…
More Recent Advances in (Hyper)Graph Partitioning
Ümit V. Çatalyürek, Karen D. Devine, Marcelo Fonseca Faraj +8
In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms. We survey trends of the last decade in practical…
Local Motif Clustering via (Hyper)Graph Partitioning
Adil Chhabra, Marcelo Fonseca Faraj, Christian Schulz
A widely-used operation on graphs is local clustering, i.e., extracting a well-characterized community around a seed node without the need to process the whole graph. Recently loca…
Recursive Multi-Section on the Fly: Shared-Memory Streaming Algorithms for Hierarchical Graph Partitioning and Process Mapping
Marcelo Fonseca Faraj, Christian Schulz
Partitioning a graph into balanced blocks such that few edges run between blocks is a key problem for large-scale distributed processing. A current trend for partitioning huge grap…
Buffered Streaming Graph Partitioning
Marcelo Fonseca Faraj, Christian Schulz
Partitioning graphs into blocks of roughly equal size is widely used when processing large graphs. Currently there is a gap in the space of available partitioning algorithms. On th…
High-Quality Hierarchical Process Mapping
Marcelo Fonseca Faraj, Alexander van der Grinten, Henning Meyerhenke +2
Partitioning graphs into blocks of roughly equal size such that few edges run between blocks is a frequently needed operation when processing graphs on a parallel computer. When a…