activity
20242026
most citedNonlinear spectral clustering with C++ GraphBLAS

1 citations · 1 across the 3 of their papers we have counts for

collaborators

9 papers

cs.DC2026

Elasticity in Parallel Sparse Triangular Solve

Raphael S. Steiner, Christos K. Matzoros, Pál András Papp +2

We introduce stale synchronous parallel as a mode of execution in parallel sparse triangular linear system solve and present a general directed-acyclic-graph scheduler capable of p…

cs.DC20261 cited

Nonlinear spectral clustering with C++ GraphBLAS

Dimosthenis Pasadakis, Olaf Schenk, Verner Vlacic +1

Nonlinear reformulations of the spectral clustering method have gained a lot of recent attention due to their increased numerical benefits and their solid mathematical background.…

cs.DC2026

Replication in Graph Partitioning and Scheduling Problems

Pál András Papp, Toni Böhnlein, A. N. Yzelman

The efficient parallel execution of complex computations requires balancing the workload across processors while minimizing the communication between them. This inherent trade-off…

cs.DC2025

The Impact of Partial Computations on the Red-Blue Pebble Game

Pál András Papp, Aleksandros Sobczyk, A. N. Yzelman

We study an extension of the well-known red-blue pebble game (RBP) with partial computation steps, inspired by the recent work of Sobczyk. While the original RBP assumes that we ne…

cs.DS2025

Symmetry-breaking symmetry in directed spectral partitioning

Dimosthenis Pasadakis, Raphael S. Steiner, Pál András Papp +2

We break the symmetry in classical spectral bi-partitioning in order to incentivise the alignment of directed cut edges. We use this to generate acyclic bi-partitions and furthermo…

cs.DC2025

Multiprocessor Scheduling with Memory Constraints: Fundamental Properties and Finding Optimal Solutions

Pál András Papp, Toni Böhnlein, A. N. Yzelman

We study the problem of scheduling a general computational DAG on multiple processors in a 2-level memory hierarchy. This setting is a natural generalization of several prominent m…