scholarly journals Optimizing Instruction Scheduling and Register Allocation for Register-File-Connected Clustered VLIW Architectures

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Haijing Tang ◽  
Xu Yang ◽  
Siye Wang ◽  
Yanjun Zhang

Clustering has become a common trend in very long instruction words (VLIW) architecture to solve the problem of area, energy consumption, and design complexity. Register-file-connected clustered (RFCC) VLIW architecture uses the mechanism of global register file to accomplish the inter-cluster data communications, thus eliminating the performance and energy consumption penalty caused by explicit inter-cluster data move operations in traditional bus-connected clustered (BCC) VLIW architecture. However, the limit number of access ports to the global register file has become an issue which must be well addressed; otherwise the performance and energy consumption would be harmed. In this paper, we presented compiler optimization techniques for an RFCC VLIW architecture called Lily, which is designed for encryption systems. These techniques aim at optimizing performance and energy consumption for Lily architecture, through appropriate manipulation of the code generation process to maintain a better management of the accesses to the global register file. All the techniques have been implemented and evaluated. The result shows that our techniques can significantly reduce the penalty of performance and energy consumption due to access port limitation of global register file.

2009 ◽  
Vol 31 (1) ◽  
pp. 127-132
Author(s):  
Zhi-Xiong ZHOU ◽  
Hu HE ◽  
Xu YANG ◽  
Yan-Jun ZHANG ◽  
Yi-He SUN

Author(s):  
Filipe Lins ◽  
Lucas Tambara ◽  
Fernanda Lima Kastensmidt ◽  
Paolo Rech

Metaheuristic algorithms are recognized for developing new algorithms and optimizing various aspects in Wireless Sensor Networks (WSNs). Evaluating a multitude of possible modes is required, in most complicated problems, to obtain an exact solution. Metaheuristic algorithms can obtain solutions in acceptable time constraints. These algorithms play an operational role in solving such problems by optimizing the different metrics such as coverage rate and energy consumption of the networks. These metrics have valuable impact on network lifetime as well. This systematic review focuses on the published work from 2010 to 2020 in metaheuristic optimization in WSN. Furthermore, the systematic review will answer multiple questions that will be discussed in the methodology section.


Author(s):  
Jaime Gomez ◽  
Cristina Cachero

The mostly “creative” authoring process used to develop many Web applications during the last years has already proven unsuccessful to tackle, with its increasing complexity, both in terms of user and technical requirements. This fact has nurtured a mushrooming of proposals, most based on conceptual models, that aim at facilitating the development, maintenance and assessment of Web applications, thus improving the reliability of the Web development process. In this chapter, we will show how traditional software engineering approaches can be extended to deal with the Web idiosyncrasy, taking advantage of proven successful notation and techniques for common tasks, while adding models and constructs needed to capture the nuances of the Web environment. In this context, our proposal, the Object-Oriented Hypermedia (OO-H) Method, developed at University of Alicante, provides a set of new views that extend UML to provide a Web interface model. A code generation process is able to, departing from such diagrams and their associated tagged values, generate a Web interface capable of connecting to underlying business modules.


2018 ◽  
Vol 7 (4.19) ◽  
pp. 1030
Author(s):  
S. K. Sonkar ◽  
M. U.Kharat

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization.  For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.  


Information ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 108 ◽  
Author(s):  
Abdul Shah ◽  
Haidawati Nasir ◽  
Muhammad Fayaz ◽  
Adidah Lajis ◽  
Asadullah Shah

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique is to maintain a balance between user comfort and energy requirements, such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gaps in the literature are due to advancements in technology, the drawbacks of optimization algorithms, and the introduction of new optimization algorithms. Further, many newly proposed optimization algorithms have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. Detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes.


2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Dingjun Chen ◽  
Sihan Li ◽  
Junjie Li ◽  
Shaoquan Ni ◽  
Xiaolong Liu

Timetable optimization techniques offer opportunity for saving energy and hence reducing operational costs for high-speed rail services. The existing energy-saving timetable optimization is mainly concentrated on the train running state adjustment and the running time redistribution between two stations. Not only the adjustment space of timetables is limited, but also it is hard for the train to reach the optimized running state in reality, and it is difficult to get feasible timetable with running time redistribution between two stations for energy-saving. This paper presents a high-speed railway energy-saving timetable based on stop schedule optimization. Under the constraints of safety interval and stop rate, with the objective of minimizing the increasing energy consumption of train stops and the shortest travel time of trains, the high-speed railway energy-saving timetable optimization model is established. The fuzzy mathematics programming method is used to design an efficient algorithm. The proposed model and algorithm are demonstrated in the actual operation data of Beijing-Shanghai high-speed railway. The results show that the total operating energy consumption of the train is reduced by 3.7%, and the total travel time of the train is reduced by 11 minutes.


Robotica ◽  
2012 ◽  
Vol 31 (4) ◽  
pp. 623-641 ◽  
Author(s):  
Hadi Kalani ◽  
Alireza Akbarzadeh ◽  
Hossein Bahrami

SUMMARYThis paper provides a general framework based on statistical design and Simulated Annealing (SA) optimization techniques for the development, analysis, and performance evaluation of forthcoming snake robot designs. A planar wheeled snake robot is considered, and the effect of its key design parameters on its performance while moving in serpentine locomotion is investigated. The goal is to minimize energy consumption and maximize distance traveled. Key kinematic and dynamic parameters as well as their corresponding range of values are identified. Derived dynamic and kinematic equations of n-link snake robot are used to perform simulation. Experimental design methodology is used for design characterization. Data are collected as per full factorial design. For both energy consumption and distance traveled, logarithmic, linear, and curvilinear regression models are generated and the best models are selected. Using analysis of variance, ANOVA, effects of parameters on performance of robots are determined. Next, using SA, optimum parameter levels of robots with different number of links to minimize energy consumption and maximize distance traveled are determined. Both single and multi-criteria objectives are considered. Webots and Matlab SimMechanics software are used to validate theoretical results. For the mathematical model and the selected range of values considered, results indicate that the proposed approach is quite effective and efficient in optimization of robot performance. This research extends the present knowledge in this field by identifying additional parameters having significant effect on snake robot performance.


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