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At sub-nanometre technology, temperature is one of the important design parameters to be taken care of during the target implementation for the circuit for its long term and reliable operation. High device package density leads to high power density that generates high temperatures. The temperature of a chip is directly proportional to the power de...
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... power profile, the power dissipation information of each module is given. The floorplan information and power profile are given as input to the HotSpot tool for generating the temperature profile. Based on floorplan information and power profile given, the HotSpot tool generates the temperature profile for each module in degree centigrades (°C). Fig. 5 shows the schematic flow-diagram of temperature generation using HotSpot tool. For an example case, the floorplan information and power profile of "rd53" benchmark circuit is shown in Fig. 6 and Fig. 7, respectively. The corresponding floorplan generation is shown in Fig. 8. The temperature profile generation using HotSpot tool using ...
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... power profile, the power dissipation information of each module is given. The floorplan information and power profile are given as input to the HotSpot tool for generating the temperature profile. Based on floorplan information and power profile given, the HotSpot tool generates the temperature profile for each module in degree centigrades (°C). Fig. 5 shows the schematic flow-diagram of temperature generation using HotSpot tool. For an example case, the floorplan information and power profile of "rd53" benchmark circuit is shown in Fig. 6 and Fig. 7, respectively. The corresponding floorplan generation is shown in Fig. 8. The temperature profile generation using HotSpot tool using ...
Citations
... To maximize resource use, a multi-objective scientific formula minimizes three goals. The NSGA-II [18] method is strengthened, the quality and distribution regularity of the solution set is improved, and the solving effective input variable polarity for the Mixed Polarity Reed-Muller (MPRM) expansion such that area, power, and temperature can be optimized simultaneously. The particle swarm optimization (PSO) algorithm is a metaheuristic optimization technique inspired by the social behavior of bird flocks and fish schools. ...
Cloud computing provides consumers and organizations with shared pools of resources for data storage and processing and its optimization is essential as 98% of the allocated resources have been utilized only 86% of 98%. Hence, we carry out optimization to automatically allocate resources. In a cloud data center, Virtual machine placement is essential, and choosing the optimal physical machine to host the virtual machine is a critical step. The efficacy of the Virtual machine placement strategy has a considerable impact on cloud computing efficiency. Today, cloud computing optimization is needed for business goals and competition in the digital landscape for cost reduction (20–28%) and Energy consumption (16–22%), improving performance (30–42%) and scaling (12–14%) to meet changing business needs. Virtual machine placement optimization problems are a class of problems that arise in cloud computing when allocating resources to virtual machines across a set of physical machines or hosts. The goal is to optimize resource utilization (12–16%) while satisfying various constraints, such as performance requirements, availability, and energy efficiency than non-metaheuristic optimization techniques. Several virtual machine placement optimization problems include placement, consolidation, migration, and scheduling. Virtualization facilitated by virtual machine placement and migration meets the ever-increasing demands of a dynamic workload by transferring virtual machines inside cloud data center. Many resource management goals, including power efficiency, load balancing, fault tolerance, and system maintenance, are aided by virtual machine placement and migration. To propose a multi-objective Mayfly virtual machine placement algorithm with a massive cloud data center with different and multi-dimensional resources to handle these issues. A multi-objective, dynamic virtual machine placement strategy simultaneously reduces resource wastage, overcommitment ratio, migration time, service level agreement violation, and energy consumption. This paper presents a dynamic, multi-objective virtual machine placement strategy in cloud data centers based on overcommitment resource allocation to influence Virtual machine Physical machine mapping and achieved an increase in the range of 12.5–14.89% in allocation than the existing works. We validated our method by conducting a performance evaluation study using the CloudSim tool. The experimental results demonstrate that this article improves resource usage while reducing energy consumption, makespan, over-commitment, and physical machine overload.
... Landscape Lighting Design. Interactive genetic algorithm has been widely used in different fields, and its application prospect is relatively good [27,28]. The radial basis function and calculation process of interactive genetic algorithm have good operability. ...
There are many problems in the practical application of landscape lighting design. In order to solve these problems more specifically, based on the relevant theories of interactive genetic algorithm, radial basis function and hesitation degree are introduced into genetic algorithm. Through the analysis and processing of the data to get the optimized interactive genetic algorithm, the algorithm can analyze and optimize the landscape lighting design. Based on this model, the lighting design can be predicted and analyzed, and the prediction result is relatively good. Relevant studies show that the interactive genetic algorithm can be divided into three typical change stages according to the different results of intensity calculation, of which the first stage mainly presents the trend of gradual decline. The fluctuation phenomenon is obvious in the second paragraph. The third paragraph shows a gradual increasing trend of change. The corresponding relationship between the two fitness functions is obvious. With the increase of experts in independent variables, the corresponding fitness values show a trend of gradual decline on the whole. Through the calculation and analysis of five different indicators of landscape lighting by using interactive genetic algorithm, it can be seen that electrification has a relatively small impact on landscape lighting. The results of intelligent and environmental protection calculation are relatively high, and the corresponding range of change is relatively large, which shows that these two indicators are very important for improving the lighting design level of landscape. Finally, the model is verified by comparing data and model curves. Interactive genetic algorithm is very important to improve the lighting design of landscape, and the optimization model can be widely used in other fields.
... With the continuous development of artificial intelligence technology, many practical multi-objective optimization problems have been solved by evolutionary algorithm, such as route network optimization with large airlines [2], temperature sensing circuit synthesis [4], etc. With the need of practical application, more and more researchers begin to further study the special multi-objective optimization problems such as high-dimensional multi-objective, multimodal multi-objective. ...
... Schematic spaces farthest-candidate approach through formula(3), and the crossover operation is carried out through formula(4), repeated N times, so the size of the new species group P 1 is N.Then, in lines 9-12, N solutions are selected as the next generation based on non-dominant sorting and the farthest-candidate approach between two spaces until the number of evaluations is greater than Gmax * T , the algorithm enters the local search phase. In line 14, the population is clustered, lines 15-21 mutate the individuals in each cluster individually, half of the individuals in distant clusters are pools of variation, mutation and crossover operations are performed on the solution in the pool by formulas(6), and (4). ...
The problem that multiple Pareto solution sets correspond to the same Pareto front is called multimodal multi-objective optimization problem. Solving all Pareto solution sets in this kind of problem can provide decision makers with more convenient and accurate choices. However, the traditional multi-objective optimization algorithm often ignores the distribution of solutions in the decision space when solving such problems, resulting in poor diversity of Pareto solution sets.To solve this problem, a two-stage search algorithm framework is proposed. This framework divides the optimization process into two parts: global search and local search to balance the search ability of the algorithm. When searching globally, locate as many approximate locations with the optimal solution as possible, providing a good population distribution for subsequent local searches. In local search, DBSCAN clustering method with adaptive neighborhood radius is used to divide the population into several subpopulations, so as to enhance the local search ability with the algorithm. At the same time, an individual selection mechanism based on the farthest-candidate approach with two spaces is proposed to keep the diversity of the population in the objective space and decision space. The algorithm is compared with five state-of-the-art algorithms on 22 multimodal and multi-objective optimization test functions. The experimental results indicate that the proposed algorithm can search more Pareto solution sets while maintaining the diversity of solutions in the objective space.
... This device can be used to communicate during business hours and at a lower cost. FSO has a number of benefits, including high bandwidth and the lack of a spectrum licence [26][27][28][29][30][31][32][33][34][35][36]. ...
... G represents the number of channels used in the medium. As the channels gets increased, BER improved significantly [34,35,36]. Fig. 10 demonstrates the In-pulse amplitude computation for every frame, the frequency is measured in every amplitude phases. ...
The optical communication system is preferred over microwave and radio frequency communication systems because of license free operation. Simulative analysis of 10gbps bandwidth using different optical communication channels have been performed in this paper. The different modulation formats of QAM and PSK have been compared for its performances under all the three optical channels OWC, FSO, and LOS-FSO which are an unguided form of optical communication. The optical channels under these modulation formats are extensively used in Digital Video Broadcasting Communication. The parameters such as Q-factor, BER and Eye height can be obtained by varying the wavelengths in the range of 850 nm 1064 nm, 1330 nm and 1550 nm. From the design and performance analysis, the system with the maximum Q-factor and minimum BER can be found for the wavelength of 1064 nm. Ó 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
... It begins with two interesting health-related works: the first one, reviews different approaches that can help fight COVID-19 [5] and the second one, tries to solve an optimal control problem of cancer treatment using an artificial neural network [6]. It continues with algorithms that can help in industrial processes such as reducing the temperature of electronic circuits [7] or carrying out chromium layer thickness forecast [8]. Radically changing the subject, the next paper proposes a method to identify the most influential nodes in social networks that can be the source of rumor spreading [9]. ...
... Dash and Pradhan [7] propose a multi-objective heuristic approach to select an efficient input variable polarity for simultaneous optimization of area, power and temperature in chips. The idea of the work is to achieve temperature minimization at the logic level instead of at the physical level, reducing the cooling cost of circuits. ...
The International Journal of Interactive Multimedia and Artificial Intelligence - IJIMAI (ISSN 1989 - 1660) provides an interdisciplinary forum in which scientists and professionals can share their research results and report new advances on Artificial Intelligence (AI) tools or tools that use AI with interactive multimedia techniques.
The optimization algorithms when used in real engineering problems involving high fidelity numeric simulations often require a large number of numerical assessments to achieve a good approximation of the optimal solution. The computational time needed to find this solution may be unfeasible in these problems. The metamodel assisted algorithms have been used to accelerate optimization problems using different strategies to find the optimum. For single objective problems, CORS (Constrained Optimization using Response Surfaces) was developed with basis on the iterative generation of distance constraints to explore and exploit the design space, such that convergence to a global optimum is mathematically guaranteed. In this paper, a multi-objective optimization strategy based on metamodel construction using radial basis functions, MO-CORS, is presented. It takes the advantage of the CORS strategy in multi-objective problems to perform the effective detection of the non-dominated set extreme points, for the subsequent filling of empty spaces between these extremes. Metamodels are used strategically in an iterative sampling process to guide the search for better solutions and to determine where in the domain the next objective function evaluations should be performed. The evaluations carried out on the expensive functions also allow improving metamodel construction in the promising regions at each iteration. Results obtained in test problems and in aerodynamic problems applications show that the developed algorithm is an effective tool to accelerate single and multi-objective optimization problems and that the use of the CORS strategy inside MO-CORS was relevant in helping it to attain solutions not found by other optimization algorithms.
