In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

Hypergraphs are a generalization of graphs where edges (aka nets) are allowed to connect
more than two vertices. They have a similarly wide range of applications as graphs. This …

Partitioning a graph into blocks of" roughly equal" weight while cutting only few edges is a
fundamental problem in computer science with a wide range of applications. In particular …

We present a shared-memory parallelization of flow-based refinement, which is considered
the most powerful iterative improvement technique for hypergraph partitioning at the …

We present new refinement heuristics for the balanced graph partitioning problem that break
with an age-old rule. Traditionally, local search only permits moves that keep the block sizes …

Balanced hypergraph partitioning is a classic NP-hard optimization problem that is a
fundamental tool in such diverse disciplines as VLSI circuit design, route planning, sharding …

Balanced hypergraph partitioning is an NP-hard problem with many applications, eg,
optimizing communication in distributed data placement problems. The goal is to place all …

Minimizing wire-lengths is one of the most important objectives in circuit design. The process
involves initially placing the logical units (cells) of a circuit onto a physical layout, and …

We investigate the efficacy of greedy heuristics for the judicious hypergraph partitioning
problem. In contrast to balanced partitioning problems, the goal of judicious hypergraph …

Addressing the challenges of processing massive graphs, which are prevalent in diverse
fields such as social, biological, and technical networks, we introduce HeiStreamE and …