Synergically Rebalancing Parallel Execution via DCT and Turbo Boosting

Author(s):  
Sandro M. Marques ◽  
Thiarles S. Medeiros ◽  
Fabio D. Rossi ◽  
Marcelo C. Luizelli ◽  
Antonio Carlos S. Beck ◽  
...  
Keyword(s):  
2017 ◽  
Vol 2 (1) ◽  
pp. 27-32
Author(s):  
Botchkaryov. A. ◽  

The way of functional coordination of methods of organization adaptive data collection processes and methods of spatial self-organization of mobile agents by parallel execution of the corresponding data collection processes and the process of motion control of a mobile agent using the proposed protocol of their interaction and the algorithm of parallel execution planning is proposed. The method allows to speed up the calculations in the decision block of the mobile agent by an average of 40.6%. Key words: functional coordination, adaptive data collection process, spatial self-organization, mobile agents


Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.


2021 ◽  
Vol 179 (2) ◽  
pp. 93-111
Author(s):  
Ludwik Czaja

Cause-effect structures are objects of a formal system devised for modeling, testing and verifying properties of tasks, where parallel execution of actions is the most characteristic feature. This is an algebraic system called a quasi-semiring. In this paper elementary cause-effect structures, a system behaviourally equivalent to 1-safe Petri nets, are extended by the following features: weighted edges, multi-valued nodes having capacities (counterpart of place/transition Petri nets), inhibitors and a model of time. The extensions are accomplished by modifying the notion of state and semantics, but leaving unchanged structure of the quasi-semiring expressions.


2021 ◽  
Vol 11 (2) ◽  
pp. 25
Author(s):  
Evelina Forno ◽  
Alessandro Salvato ◽  
Enrico Macii ◽  
Gianvito Urgese

SpiNNaker is a neuromorphic hardware platform, especially designed for the simulation of Spiking Neural Networks (SNNs). To this end, the platform features massively parallel computation and an efficient communication infrastructure based on the transmission of small packets. The effectiveness of SpiNNaker in the parallel execution of the PageRank (PR) algorithm has been tested by the realization of a custom SNN implementation. In this work, we propose a PageRank implementation fully realized with the MPI programming paradigm ported to the SpiNNaker platform. We compare the scalability of the proposed program with the equivalent SNN implementation, and we leverage the characteristics of the PageRank algorithm to benchmark our implementation of MPI on SpiNNaker when faced with massive communication requirements. Experimental results show that the algorithm exhibits favorable scaling for a mid-sized execution context, while highlighting that the performance of MPI-PageRank on SpiNNaker is bounded by memory size and speed limitations on the current version of the hardware.


1983 ◽  
Vol 11 (3) ◽  
pp. 349-355 ◽  
Author(s):  
Shinji Umeyama ◽  
Koichiro Tamura

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