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20242026
most citedEfficient Multi-Processor Scheduling in Increasingly Realistic Models

5 citations · 6 across the 6 of their papers we have counts for

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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.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

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…

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.DC2025

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…

cs.DC2024★ 5 cited

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…