scholarly journals Learning-Directed Dynamic Voltage and Frequency Scaling Scheme with Adjustable Performance for Single-Core and Multi-Core Embedded and Mobile Systems

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3068 ◽  
Author(s):  
Yen-Lin Chen ◽  
Ming-Feng Chang ◽  
Chao-Wei Yu ◽  
Xiu-Zhi Chen ◽  
Wen-Yew Liang
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Mobile Systems ◽  
Processing Unit ◽  
Frequency Scaling ◽  
Performance Loss ◽  
Central Processing ◽  
Savings Rate ◽  
Dynamic Voltage ◽  
And Performance

Dynamic voltage and frequency scaling (DVFS) is a well-known method for saving energy consumption. Several DVFS studies have applied learning-based methods to implement the DVFS prediction model instead of complicated mathematical models. This paper proposes a lightweight learning-directed DVFS method that involves using counter propagation networks to sense and classify the task behavior and predict the best voltage/frequency setting for the system. An intelligent adjustment mechanism for performance is also provided to users under various performance requirements. The comparative experimental results of the proposed algorithms and other competitive techniques are evaluated on the NVIDIA JETSON Tegra K1 multicore platform and Intel PXA270 embedded platforms. The results demonstrate that the learning-directed DVFS method can accurately predict the suitable central processing unit (CPU) frequency, given the runtime statistical information of a running program, and achieve an energy savings rate up to 42%. Through this method, users can easily achieve effective energy consumption and performance by specifying the factors of performance loss.

Balancing Power And Performance In HPC Clouds

2020 ◽  
Vol 63 (6) ◽  
pp. 880-899
Author(s):  
Lixia Chen ◽  
Jian Li ◽  
Ruhui Ma ◽  
Haibing Guan ◽  
Hans-Arno Jacobsen
Keyword(s):  
Energy Consumption ◽  
High Performance ◽  
Virtual Machines ◽  
Support Vector ◽  
Frequency Scaling ◽  
Vm Placement ◽  
Placement Problem ◽  
Dynamic Voltage ◽  
And Performance ◽  
Save Energy

Abstract With energy consumption in high-performance computing clouds growing rapidly, energy saving has become an important topic. Virtualization provides opportunities to save energy by enabling one physical machine (PM) to host multiple virtual machines (VMs). Dynamic voltage and frequency scaling (DVFS) is another technology to reduce energy consumption. However, in heterogeneous cloud environments where DVFS may be applied at the chip level or the core level, it is a great challenge to combine these two technologies efficiently. On per-core DVFS servers, cloud managers should carefully determine VM placements to minimize performance interference. On full-chip DVFS servers, cloud managers further face the choice of whether to combine VMs with different characteristics to reduce performance interference or to combine VMs with similar characteristics to take better advantage of DVFS. This paper presents a novel mechanism combining a VM placement algorithm and a frequency scaling method. We formulate this VM placement problem as an integer programming (IP) to find appropriate placement configurations, and we utilize support vector machines to select suitable frequencies. We conduct detailed experiments and simulations, showing that our scheme effectively reduces energy consumption with modest impact on performance. Particularly, the total energy delay product is reduced by up to 60%.

scholarly journals Determination of Optimum Envelope of Religious Buildings in Terms of Thermal Comfort and Energy Consumption: Mosque Cases

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6597
Author(s):  
Ahmet Bircan Atmaca ◽  
Gülay Zorer Gedik ◽  
Andreas Wagner
Keyword(s):  
Thermal Properties ◽  
Energy Consumption ◽  
Thermal Comfort ◽  
Thermal Insulation ◽  
Energy Savings ◽  
Gain Factor ◽  
Building Envelope ◽  
Comfort Level ◽  
Humid Climate ◽  
Savings Rate

Mosques are quite different from other building types in terms of occupant type and usage schedule. For this reason, they should be evaluated differently from other building types in terms of thermal comfort and energy consumption. It is difficult and probably not even necessary to create homogeneous thermal comfort in mosques’ entire usage area, which has large volumes and various areas for different activities. Nevertheless, energy consumption should be at a minimum level. In order to ensure that mosques are minimally affected by outdoor climatic changes, the improvement of the properties of the building envelope should have the highest priority. These optimal properties of the building envelope have to be in line with thermal comfort in mosques. The proposed method will be a guide for designers and occupants in the design process of new mosques or the use of existing mosques. The effect of the thermal properties of the building envelope on energy consumption was investigated to ensure optimum energy consumption together with an acceptable thermal comfort level. For this purpose, a parametric simulation study of the mosques was conducted by varying optical and thermal properties of the building envelope for a temperature humid climate zone. The simulation results were analyzed and evaluated according to current standards, and an appropriate envelope was determined. The results show that thermal insulation improvements in the roof dome of buildings with a large volume contributed more to energy savings than in walls and foundations. The use of double or triple glazing in transparent areas is an issue that should be considered together with the solar energy gain factor. Additionally, an increasing thickness of thermal insulation in the building envelope contributed positively to energy savings. However, the energy savings rate decreased after a certain thickness. The proposed building envelope achieved a 33% energy savings compared to the base scenario.

SeisNoise.jl: Ambient Seismic Noise Cross Correlation on the CPU and GPU in Julia

2020 ◽  
Vol 92 (1) ◽  
pp. 517-527
Author(s):  
Timothy Clements ◽  
Marine A. Denolle
Keyword(s):  
Seismic Noise ◽  
High Performance ◽  
Cross Correlation ◽  
Graphic Processing Unit ◽  
Ambient Seismic Noise ◽  
Processing Unit ◽  
Central Processing ◽  
And Performance ◽  
Noise Cross Correlation ◽  
Performance Computing

Abstract We introduce SeisNoise.jl, a library for high-performance ambient seismic noise cross correlation, written entirely in the computing language Julia. Julia is a new language, with syntax and a learning curve similar to MATLAB (see Data and Resources), R, or Python and performance close to Fortran or C. SeisNoise.jl is compatible with high-performance computing resources, using both the central processing unit and the graphic processing unit. SeisNoise.jl is a modular toolbox, giving researchers common tools and data structures to design custom ambient seismic cross-correlation workflows in Julia.

scholarly journals Energy Audit and Analysis of an Institutional Building under Subtropical Climate

2018 ◽  
Vol 8 (2) ◽  
pp. 845 ◽  
Author(s):  
Yazed Yasin Ghadi ◽  
Ali M. Baniyounes
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Environmental Parameters ◽  
Subtropical Climate ◽  
University Campus ◽  
Energy Usage ◽  
Climate Conditions ◽  
Heating And Cooling ◽  
And Performance ◽  
Heating And Cooling Load

<p>Evaluation and estimation of energy consumption are essential in order to classify the amount of energy used and the way it is utilized in building. Hence, the possibility of any energy savings potential and energy savings opportunities can be identified. The intention of this article is to study and evaluate energy usage pattern of the Central Queensland University campus’ buildings, Queensland, Australia. This article presents the field survey results from the audit of an office building and performance-related measurements of the indoor environmental parameters, for instance, indoor air temperature, humidity and energy consumption concerned to the indoor heating and cooling load. Monthly observed energy usage information was employed to investigate influence of the climate conditions on energy usage.</p>

scholarly journals A Design Strategy for Energy-Efficient Rural Houses in Severe Cold Regions

2020 ◽  
Vol 17 (18) ◽  
pp. 6481
Author(s):  
Wente Pan ◽  
Hongyuan Mei
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Efficient ◽  
Urban Areas ◽  
Energy Savings ◽  
Rapid Development ◽  
Low Energy ◽  
Cold Regions ◽  
Rural Buildings ◽  
Savings Rate

In the past decade, Chinese urban areas have seen rapid development, and rural areas are becoming the next construction hotspot. The development of rural buildings in China has lagged behind urban development, and there is a lack of energy-efficient rural buildings. Rural houses in severe cold regions have the characteristics of large energy exchange, a long heating cycle, and low construction costs. Energy consumption is a crucial issue for rural houses in severe cold regions. How to balance the energy efficiency and building cost become a crucial problem. To solve this problem, we investigate the energy consumption of rural housing in cold regions, using Longquan Village in Heilongjiang Province, northeast China, as a case study. A low-energy design framework is established that considers the spatial layout, building type, enclosure system, and heating system. With the support of project funds, a demonstration house is constructed, and the energy savings performance of the building is investigated during the heating period. The results indicate that the energy savings rate of the demonstration house is 66%. The demonstration building enables local residents to learn construction methods for low-energy houses and promotes energy efficiency.

scholarly journals Accurate Energy and Performance Prediction for Frequency-Scaled GPU Kernels

Computation ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 37
Author(s):  
Kaijie Fan ◽  
Biagio Cosenza ◽  
Ben Juurlink
Keyword(s):  
Energy Consumption ◽  
Performance Prediction ◽  
High Performance ◽  
Pareto Set ◽  
Large Set ◽  
Balance Performance ◽  
Multi Objective ◽  
Dynamic Voltage ◽  
And Performance ◽  
Performance Computing

Energy optimization is an increasingly important aspect of today’s high-performance computing applications. In particular, dynamic voltage and frequency scaling (DVFS) has become a widely adopted solution to balance performance and energy consumption, and hardware vendors provide management libraries that allow the programmer to change both memory and core frequencies manually to minimize energy consumption while maximizing performance. This article focuses on modeling the energy consumption and speedup of GPU applications while using different frequency configurations. The task is not straightforward, because of the large set of possible and uniformly distributed configurations and because of the multi-objective nature of the problem, which minimizes energy consumption and maximizes performance. This article proposes a machine learning-based method to predict the best core and memory frequency configurations on GPUs for an input OpenCL kernel. The method is based on two models for speedup and normalized energy predictions over the default frequency configuration. Those are later combined into a multi-objective approach that predicts a Pareto-set of frequency configurations. Results show that our approach is very accurate at predicting extema and the Pareto set, and finds frequency configurations that dominate the default configuration in either energy or performance.

Energy losses and DVFS effectiveness vs technology scaling

2015 ◽  
Vol 32 (3) ◽  
pp. 158-163
Author(s):  
Piotr Kocanda ◽  
Andrzej Kos
Keyword(s):  
Energy Consumption ◽  
Energy Conservation ◽  
Complete Analysis ◽  
Energy Losses ◽  
Cmos Circuits ◽  
Frequency Scaling ◽  
Content Type ◽  
Technology Scaling ◽  
Dynamic Voltage ◽  
Static Energy

Purpose – This article aims to present complete analysis of energy losses in complementary metal-oxide semiconductor (CMOS) circuits and the effectiveness of dynamic voltage and frequency scaling (DVFS) as a method of energy conservation in CMOS circuits in variety of technologies. Energy efficiency in CMOS devices is an issue of highest importance with still continuing technology scaling. There are powerful tools for energy conservation in form of dynamic voltage scaling (DVS) and dynamic frequency scaling (DFS). Design/methodology/approach – Using analytical equations and Spice models of various technologies, energy losses are calculated and effectiveness of DVS and DFS is evaluated for every technology. Findings – Test showed that new dedicated technology for low static energy consumption can be as economical as older technologies. The dynamic voltage and frequency scaling are most effective when there is a dominance of dynamic energy losses in circuit. In case when static energy losses are comparable to dynamic energy losses, use of dynamic voltage frequency scaling can even lead to increased energy consumption. Originality/value – This paper presents complete analysis of energy losses in CMOS circuits and effectiveness of mentioned methods of energy conservation in CMOS circuits in six different technologies.

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