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4 Annals of Computer Science and Information Systems

4 2020

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A Reactive Search-Based Algorithm for Scheduling Multiprocessor Tasks on Two Dedicated Processors

100%

Aïder M. , Baatout F. Z. , Hifi M.

tom Vol. 21

257--261

In this paper, we propose a reactive search-based algorithm for solving the problem of scheduling multiprocessor tasks on two dedicated processors. An instance of the problem is characterized by a set of tasks divided into three subsets and two processors, where some tasks can be executed either on one processor or two processors. The goal of the problem is to determine the scheduling of all tasks minimizing the execution of the last assigned task. The proposed reactive search starts with a starting greedy solution. Next, a series of local operators combined with a tabu list are introduced in order to intensify the search process. The method is also reinforced with a drop and rebuild operator that is applied for diversifying the search process. Finally, the performance of the proposed method is evaluated on a set of benchmark instances, where its provided results are compared to those achieved by a recent method available in the literature. Encouraging results have been reached.

Parallel implementation of a PIC simulation algorithm using OpenMP

67%

Suciu A. , Hangan A. , Marginean A. , Joldos M. , Voitcu G. , Echim M.

tom Vol. 21

381--385

Particle-in-cell (PIC) simulations are focusing on the individual trajectories of a very large number of particles in self-consistent and external electric and magnetic fields; they are widely used in the study of plasma jets, for example. The main disadvantage of PIC simulations is the large simulation runtime,which often requires a parallel implementation of the algorithm. The current paper focuses on a PIC1d3v simulation algorithm and describes the successful implementation of a parallel version of it on a multi-core architecture, using OpenMP, with very promising experimental and theoretical results.

Efficient Computation of RNA Partition Functions Using McCaskill’s Algorithm

67%

Zhao C. , Sahni S.

tom Vol. 21

449--452

We develop efficient single- and multi-core algorithms to compute partition functions for RNA sequences. Our algorithms, which are based on McCaskill's algorithm, are benchmarked against state-of-the-art fast algorithms obtained using the parallelizing source-to-source compilers PLUTO and TRACO. On our Intel I9 computational platform, our best single core algorithm takes up to 81.2% less time than the single core algorithm resulting from PLUTO, which is faster than that obtained from TRACO. Our best multi-core algorithm takes up to 84.7% less time than the multi-core algorithm obtained using TRACO when run with 20 threads (our I9 has 10 cores and supports hyperthreading); the TRACO multi-core algorithm is faster than the PLUTO one.

Testbed for thermal and performance analysis in MPSoC systems

67%

Sojka M. , Benedikt O. , Hanzálek Z. , Zaykov P.

tom Vol. 21

683--692

Many modern computing platforms in the safety-critical domains are based on heterogeneous Multiprocessor System-on-Chip (MPSoC). Such computing platforms are expected to guarantee high-performance within a strict thermal envelope. This paper introduces a testbed for thermal and performance analysis. The testbed allows the users to develop advanced scheduling and resource allocation techniques aiming at finding an optimal trade-off between the peak temperature and the achieved performance. This paper presents a new, open-source Thermobench tool for data collection and analysis of user-defined workloads. Furthermore, a methodology for shortening the time needed for the data collection is proposed. Experiments show that a significant amount of time can be saved. Specifically, time reduction from 60 minutes to 15 minutes is achieved with the i.MX8 MPSoC from NXP while running a set of user-defined benchmarks that stress CPU, GPU, and different levels of the memory hierarchy.