5 citations · 6 across the 6 of their papers we have counts for
7 papers
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…
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…
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…
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…
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…
Efficient Parallel Scheduling for Sparse Triangular Solvers
Toni Böhnlein, Pál András Papp, Raphael S. Steiner +2
We develop and analyze new scheduling algorithms for solving sparse triangular linear systems (SpTRSV) in parallel. Our approach produces highly efficient synchronous schedules for…
Efficient Multi-Processor Scheduling in Increasingly Realistic Models
Pál András Papp, Georg Anegg, Aikaterini Karanasiou +1
We study the problem of efficiently scheduling a computational DAG on multiple processors. The majority of previous works have developed and compared algorithms for this problem in…