Task Assignment for Multiple-Application Workload with Streaming Ones in MPSoC Using Shared Memory

2012 ◽  
Vol 263-266 ◽  
pp. 1781-1785
Author(s):  
Qi Zuo
Keyword(s):  
Shared Memory ◽  
Large Scale ◽  
Task Assignment ◽  
Streaming Application ◽  
Streaming Applications ◽  
Multiple Application ◽  
Memory Contention ◽  
Assignment Strategy ◽  
Overall Performance ◽  
On Chip

Large scale Multi-Processor System-on-a-chip (MPSoC) based on Network on Chip (NoC) can support multiple applications running simultaneously. When the multiple-application workload includes streaming applications processing massive data, the communication concentrated on shared memory can't be ignored. In this paper, we propose a task assignment strategy for multiple-application workload which includes one streaming application on a NoC-based MPSoC. The proposed algorithm first assigns the streaming application centering the multi-port shared memory, and then assigns the other applications minimizing external communication congestion. By adopting the proposed algorithm, the memory-contention tasks are assigned to the PEs close to the shared memory and the overall congestion is minimized. This allows the system to provide better overall performance.

Dynamic Dependent Tasks Assignment for Grid Computing

2011 ◽  
Vol 3 (2) ◽  
pp. 44-58 ◽  
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

scholarly journals Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Jie Chen ◽  
Kai Xiao ◽  
Kai You ◽  
Xianguo Qing ◽  
Fang Ye ◽  
...  
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Task Assignment ◽  
Search And Rescue ◽  
Small Scale ◽  
Assignment Strategy ◽  
Negotiation Mechanism ◽  
Decoupling Algorithm ◽  
Task Assignment Problem ◽  
Multi Uav

For the large-scale search and rescue (S&R) scenarios, the centralized and distributed multi-UAV multitask assignment algorithms for multi-UAV systems have the problems of heavy computational load and massive communication burden, which make it hard to guarantee the effectiveness and convergence speed of their task assignment results. To address this issue, this paper proposes a hierarchical task assignment strategy. Firstly, a model decoupling algorithm based on density clustering and negotiation mechanism is raised to decompose the large-scale task assignment problem into several nonintersection and complete small-scale task assignment problems, which effectively reduces the required computational amount and communication cost. Then, a cluster head selection method based on multiattribute decision is put forward to select the cluster head for each UAV team. These cluster heads will communicate with the central control station about the latest assignment information to guarantee the completion of S&R mission. At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. Simulation results and analyses comprehensively verify the feasibility and effectiveness of the proposed hierarchical task assignment strategy in large-scale S&R scenarios with dispersed clustering targets.

Dynamic Dependent Tasks Assignment for Grid Computing

2013 ◽  
pp. 58-73
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

Dynamic Dependent Tasks Assignment for Grid Computing

2012 ◽  
pp. 551-565
Author(s):  
Meriem Meddeber ◽  
Belabbas Yagoubi
Keyword(s):  
Resource Management ◽  
Grid Computing ◽  
Large Scale ◽  
Task Assignment ◽  
Considerable Effect ◽  
Distributed Applications ◽  
Grid Middleware ◽  
Assignment Strategy ◽  
Transfer Cost ◽  
Dependent Tasks

A computational grid is a widespread computing environment that provides huge computational power for large-scale distributed applications. One of the most important issues in such an environment is resource management. Task assignment as a part of resource management has a considerable effect on the grid middleware performance. In grid computing, task execution time is dependent on the machine to which it is assigned, and task precedence constraints are represented by a directed acyclic graph. This paper proposes a hybrid assignment strategy of dependent tasks in Grids which integrate static and dynamic assignment technologies. Grid computing is considered a set of clusters formed by a set of computing elements and a cluster manager. The main objective is to arrive at a method of task assignment that could achieve minimum response time and reduce the transfer cost, inducing by the tasks transfer respecting the dependency constraints.

scholarly journals Placing Multimode Streaming Applications on Dynamically Partially Reconfigurable Architectures

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
S. Wildermann ◽  
J. Angermeier ◽  
E. Sibirko ◽  
J. Teich
Keyword(s):  
System On Chip ◽  
Reconfigurable Architectures ◽  
Reconfigurable Systems ◽  
Partial Reconfiguration ◽  
Runtime Support ◽  
Streaming Application ◽  
Streaming Applications ◽  
On Chip ◽  
Novel Algorithm

By means of partial reconfiguration, parts of the hardware can be dynamically exchanged at runtime. This allows that streaming application running in different modes of the systems can share resources. In this paper, we discuss the architectural issues to design such reconfigurable systems. For being able to reduce reconfiguration time, this paper furthermore proposes a novel algorithm to aggregate several streaming applications into a single representation, called merge graph. The paper also proposes an algorithm to place streaming application at runtime which not only considers the placement and communication constraints, but also allows to place merge tasks. In a case study, we implement the proposed algorithm as runtime support on an FPGA-based system on chip. Furthermore, experiments show that reconfiguration time can be considerably reduced by applying our approach.

scholarly journals Modelling and pH Control in Raceway and Thin-Layer Photobioreactors for Wastewater Treatment

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1099
Author(s):  
María José Rodríguez-Torres ◽  
Ainoa Morillas-España ◽  
José Luis Guzmán ◽  
Francisco Gabriel Acién
Keyword(s):  
Wastewater Treatment ◽  
Thin Layer ◽  
Large Scale ◽  
Control Period ◽  
Ph Control ◽  
Thin Layers ◽  
Control Algorithms ◽  
Treatment Processes ◽  
Overall Performance ◽  
Reduction Of Co2

One of the most critical variables in microalgae-related processes is the pH; it directly determines the overall performance of the production system especially when coupling with wastewater treatment. In microalgae-related wastewater treatment processes, the adequacy of pH has a large impact on the microalgae/bacteria consortium already developing on these systems. For cost-saving reasons, the pH is usually controlled by classical On/Off control algorithms during the daytime period, typically with the dynamics of the system and disturbances not being considered in the design of the control system. This paper presents the modelling and pH control in open photobioreactors, both raceway and thin-layer, using advanced controllers. In both types of photobioreactors, a classic control was implemented and compared with a Proportional–Integral (PI) control, also the operation during only the daylight period and complete daily time was evaluated. Thus, three major variables already studied include (i) the type of reactors (thin-layers and raceways), (ii) the type of control algorithm (On/Off and PI), and (iii) the control period (during the daytime and throughout the daytime and nighttime). Results show that the pH was adequately controlled in both photobioreactors, although each type requires different control algorithms, the pH control being largely improved when using PI controllers, with the controllers allowing us to reduce the total costs of the process with the reduction of CO2 injections. Moreover, the control during the complete daily cycle (including night) not only not increases the amount of CO2 to be injected, otherwise reducing it, but also improves the overall performance of the production process. Optimal pH control systems here developed are highly useful to develop robust large-scale microalgae-related wastewater treatment processes.

scholarly journals Nanolaser-based emulators of spin Hamiltonians

Nanophotonics ◽  
2020 ◽  
Vol 9 (13) ◽  
pp. 4193-4198 ◽  
Author(s):  
Midya Parto ◽  
William E. Hayenga ◽  
Alireza Marandi ◽  
Demetrios N. Christodoulides ◽  
Mercedeh Khajavikhan
Keyword(s):  
Large Scale ◽  
Optimization Problems ◽  
Exchange Interactions ◽  
Np Hard ◽  
Spin Models ◽  
Geometric Frustration ◽  
Spin Hamiltonians ◽  
Hard Problems ◽  
On Chip ◽  
Classical Spin Models

AbstractFinding the solution to a large category of optimization problems, known as the NP-hard class, requires an exponentially increasing solution time using conventional computers. Lately, there has been intense efforts to develop alternative computational methods capable of addressing such tasks. In this regard, spin Hamiltonians, which originally arose in describing exchange interactions in magnetic materials, have recently been pursued as a powerful computational tool. Along these lines, it has been shown that solving NP-hard problems can be effectively mapped into finding the ground state of certain types of classical spin models. Here, we show that arrays of metallic nanolasers provide an ultra-compact, on-chip platform capable of implementing spin models, including the classical Ising and XY Hamiltonians. Various regimes of behavior including ferromagnetic, antiferromagnetic, as well as geometric frustration are observed in these structures. Our work paves the way towards nanoscale spin-emulators that enable efficient modeling of large-scale complex networks.

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