Modeling of Applications and Hardware to Explore Task Mapping and Scheduling Strategies on a Heterogeneous Micro-Server System

Zaourar, Lilia; Ait, Massinissa; Philippe, Jean-Marc

doi:10.1109/ipdpsw.2017.123

Cited by 7 publications

(6 citation statements)

References 22 publications

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“…pthread, OpenMP, OpenCL). A complete mathematical formulation of tasks mapping on heterogeneous system problem is available in [13]. In this work, two straightforward mapping strategies were developed for the experiments.…”

Section: Mapping Problemmentioning

confidence: 99%

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Application Topology Definition and Tasks Mapping for Efficient Use of Heterogeneous Resources

Trabelsi

Cudennec

Bennour

2020

Euro-Par 2019: Parallel Processing Workshops

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Nowadays, high-performance computing (HPC) not only faces challenges to reach computing performance, it also has to take in consideration the energy consumption. In this context, heterogeneous architectures are expected to tackle this challenge by proposing a mix of HPC and low-power nodes. There is a significant research effort to define methods for exploiting such computing platforms and find a trade-off between computing performance and energy consumption. To this purpose, the topology of the application and the mapping of tasks onto physical resources are of major importance. In this paper we propose an iterative approach based on the exploration of logical topologies and mappings. These solutions are executed onto the heterogeneous platform and evaluated. Based on these results a Pareto front is built, allowing users to select the most relevant configurations of the application according to the current goals and constraints. Experiments have been conducted on a heterogeneous micro-server using a video processing application running on top of a software-distributed shared memory and deployed over a mix of Intel i7 and Arm Cortex A15 processors. Results show that some counterintuitive solutions found by the exploration approach perform better than classical configurations.

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Section: Mapping Problemmentioning

confidence: 99%

“…In [10] an iterative algorithm is proposed for the mapping problem on heterogeneous computing platforms with load balancing as a goal. In [13] the authors model both task scheduling and mapping in a heterogeneous system as a bi-objective optimization problem between energy consumption and system performance.…”

Section: Related Workmentioning

confidence: 99%

Application Topology Definition and Tasks Mapping for Efficient Use of Heterogeneous Resources

Trabelsi

Cudennec

Bennour

2020

Euro-Par 2019: Parallel Processing Workshops

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show abstract

“…In addition, we consider in this work communication cost between tasks and processing elements. Preliminary results on modeling applications and heterogeneous platforms have been presented in [6], we focus in this work on tasks chain to determine a performance guarantee algorithm.…”

Section: Related Workmentioning

confidence: 99%

“…Each edge e i,j ∈ E represents a precedence constraint between two tasks t i and t j and refers to the volume of communication from t i to t j denoted by Ct i,j if they are not assigned to the same processing element. Communication cost between each pair of processing elements (PE k , PE l ) is denoted by Cm k,l with Cm k,l Max i execut i,k , ∀i ∈{1, 2,...,n} and ∀k, l ∈{1, 2,...,m} as in [6].…”

Section: M O D E Lmentioning

confidence: 99%

Approximation Algorithm for Scheduling a Chain of Tasks on Heterogeneous Systems

Ait

Zaourar

Munier

2018

Lecture Notes in Computer Science

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This paper presents an efficient approximation algorithm to solve the task scheduling problem on heterogeneous platform for the particular case of the linear chain of tasks. The objective is to minimize both the total execution time (makespan) and the total energy consumed by the system. For this purpose, we introduce a constraint on the energy consumption during execution. Our goal is to provides an algorithm with a performance guarantee. Two algorithms have been proposed; the first provides an optimal solution for preemptive scheduling. This solution is then used in the second algorithm to provide an approximate solution for non-preemptive scheduling. Numerical evaluations demonstrate that the proposed algorithm achieves a close-to-optimal performance compared to exact solution obtained by CPLEX for small instances. For large instances, CPLEX is struggling to provide a feasible solution, whereas our approach takes less than a second to produce a solution for an instance of 10000 tasks.

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“…We associate it with the value ct i,j which represents the communication delay between t i and t j if they are executed on two different resource types. The exact formula to evaluate ct i,j which takes into consideration latencies and available bandwidth between processors is provided in [28]. We denote by (i) (resp.…”

Section: Problem Definitionmentioning

confidence: 99%

Approximation Algorithm for Scheduling Applications on Hybrid Multi-core Machines with Communications Delays

Ait

Zaourar

Munier

2018

2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)

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This paper presents an efficient algorithm with performance guarantee (approximation algorithm) to solve task scheduling problem on hybrid platform. The underlying platform architecture in this work is composed by two types of resources CPU and GPU, often called hybrid parallel multicore platforms. We consider here for each type of resource identical nodes with communications delays. We focus in finding a generic approach to schedule applications presented by DAG (Directed Acyclic Graph) that minimizes makespan by considering communication delay between processors and tasks. A 6-approximation scheduling algorithm is proposed and evaluated in comparison to exact solutions and to another method. We demonstrate that the proposed algorithm achieves a close-to-optimal performance. Finally, our algorithm has been experimented on a large number of instances. These tests assess the good practical behavior of the algorithms with respect to the state-of-the-art solutions whenever these exist.

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Modeling of Applications and Hardware to Explore Task Mapping and Scheduling Strategies on a Heterogeneous Micro-Server System

Cited by 7 publications

References 22 publications

Application Topology Definition and Tasks Mapping for Efficient Use of Heterogeneous Resources

Application Topology Definition and Tasks Mapping for Efficient Use of Heterogeneous Resources

Approximation Algorithm for Scheduling a Chain of Tasks on Heterogeneous Systems

Approximation Algorithm for Scheduling Applications on Hybrid Multi-core Machines with Communications Delays

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