Scheduling Strategies for Partially-Replicable Task Chains on Two Types of Resources

The arrival of heterogeneous (or hybrid) multicore architectures on parallel platforms has brought new performance opportunities for applications and efficiency opportunities to systems. They have also increased the challenges related to thread scheduling, as tasks’ execution times will vary depending if they are placed in big (performance) cores or little (efficient) ones. In this paper, we focus on the challenges heterogeneous multicore problems bring to partially-replicable task chains, such as the ones that implement digital communication standards in Software-Defined Radio (SDR). Our objective is to maximize the throughput of these task chains while also minimizing their power consumption. We model this problem as a pipelined workflow scheduling problem using pipelined and replicated parallelism on two types of resources whose objectives are to minimize the period and to use as many little cores as necessary. We propose two greedy heuristics (FERTAC and 2CATAC) and one optimal dynamic programming (HeRAD) solution to the problem. We evaluate our solutions and compare the quality of their schedules (in period and resource utilization) and their execution times using synthetic task chains and an implementation of the DVB-S2 communication standard running on StreamPU. Our results demonstrate the benefits and drawbacks of the different proposed solutions. On average, FERTAC and 2CATAC achieve near-optimal solutions, with periods that are less than 10% worse than the optimal (HeRAD) using fewer than 2 extra cores. These three scheduling strategies now enable programmers and users of StreamPU to transparently make use of heterogeneous multicore processors and achieve throughputs that differ from their theoretical maximums by less than 8% on average.

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Publication Details

Published
2025-06-03
DOI
https://doi.org/10.1109/ipdpsw66978.2025.00140
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Scheduling Strategies for Partially-Replicable Task Chains on Two Types of Resources

Denis Barthou, Christophe Jégo, Laércio Lima Pilla, Adrien Cassagne et al.
Distributed and Parallel Computing Systems
article

Scheduling Strategies for Partially-Replicable Task Chains on Two Types of Resources

Denis Barthou, Christophe Jégo, Laércio Lima Pilla, Adrien Cassagne, Diane Orhan, Yacine Idouar
article en

Abstract

The arrival of heterogeneous (or hybrid) multicore architectures on parallel platforms has brought new performance opportunities for applications and efficiency opportunities to systems. They have also increased the challenges related to thread scheduling, as tasks’ execution times will vary depending if they are placed in big (performance) cores or little (efficient) ones. In this paper, we focus on the challenges heterogeneous multicore problems bring to partially-replicable task chains, such as the ones that implement digital communication standards in Software-Defined Radio (SDR). Our objective is to maximize the throughput of these task chains while also minimizing their power consumption. We model this problem as a pipelined workflow scheduling problem using pipelined and replicated parallelism on two types of resources whose objectives are to minimize the period and to use as many little cores as necessary. We propose two greedy heuristics (FERTAC and 2CATAC) and one optimal dynamic programming (HeRAD) solution to the problem. We evaluate our solutions and compare the quality of their schedules (in period and resource utilization) and their execution times using synthetic task chains and an implementation of the DVB-S2 communication standard running on StreamPU. Our results demonstrate the benefits and drawbacks of the different proposed solutions. On average, FERTAC and 2CATAC achieve near-optimal solutions, with periods that are less than 10% worse than the optimal (HeRAD) using fewer than 2 extra cores. These three scheduling strategies now enable programmers and users of StreamPU to transparently make use of heterogeneous multicore processors and achieve throughputs that differ from their theoretical maximums by less than 8% on average.

Centre National de la Recherche Scientifique (FR), Université de Bordeaux (FR), Sorbonne Université (FR), Sorbonne Paris Cité (FR), Centre de Recherches sur la Cognition et l'Apprentissage (FR), Laboratoire Bordelais de Recherche en Informatique (FR), Laboratoire de l'Intégration du Matériau au Système (FR), LIP6 (FR), Institut Polytechnique de Bordeaux (FR)
Agence Nationale de la Recherche
Openalex Percentile: Top 98%
Distributed and Parallel Computing Systems
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