scholarly journals The Implications of Ferroelectric FET Device Models to the Design of Computing-in-Memory Architectures

2021 ◽  
Vol 16 (1) ◽  
pp. 1-8
Author(s):  
Dayane Reis ◽  
Michael Niemier ◽  
Xiaobo Sharon Hu
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Data Transfer ◽  
Energy Reduction ◽  
Memory Cells ◽  
Arithmetic Operations ◽  
Memory Architectures ◽  
Level Performance ◽  
Performance Computing ◽  
Significant Application

Data transfer between a processor and memory frequently represents a bottleneck with respect to improving application-level performance. Computing-in-memory (CiM), where logic and arithmetic operations are performed in memory, could significantly reduce both energy consumption and computational overheads associated with data transfer. This work presents a revisited study of FeFET-CiM, a CiM architecture capable of performing Boolean ((N)AND, (N)OR, X(N)OR, INV) as well as arithmetic (ADD) operations between words in memory. In this study, we employ two types of FeFET-based memory cells in the CiM architecture. Namely, the 2T+1FeFET and the 1-FeFET memory cells. The use of these two types of memory cells in the FeFET-CiM architecture is enabled by two distinct models for FeFET devices. The FeFET-CiM architecture based on 2T+1FeFETs (1FeFETs) offers an average speedup of ∼2.5X (∼1.1X) and energy reduction of ∼1.7X (∼1.4X) when compared to a SRAM baseline across 12 benchmark programs. Despite smaller speedups and energy savings enabled by 1FeFET-CiM when compared to 2T+1FeFET-CiM, 1FeFET memory arrays may offer up to ∼5.3X density improvements when compared to conventional 6T-SRAM arrays. Furthermore, 1FeFET-CiM offers significant application-level improvements when compared to a counterpart STT-CiM architecture.

INTRA-APPLICATION ENERGY REDUCTION FOR MICROPROCESSOR LOW-POWER DESIGN

2009 ◽  
Vol 18 (01) ◽  
pp. 181-198 ◽  
Author(s):  
XIAO XIN XIA ◽  
TENG TIOW TAY
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Sampling Method ◽  
Energy Savings ◽  
Low Power Design ◽  
Energy Reduction ◽  
Software Optimization ◽  
Application Identification ◽  
Instructions Per Cycle ◽  
Important Design

Energy consumption is one of the most important design constraints for modern microprocessors, and designers have proposed many energy-saving techniques. Looking beyond the traditional hardware low-power designs, software optimization is becoming a significant strategy for the microprocessor to lower its energy consumption. This paper describes an intra-application identification and reconfiguration mechanism for microprocessor energy reduction. Our mechanism employs a statistical sampling method during training runs to identify code sections among application that have appropriate IPC (Instructions per Cycle) values and could make contributions to program runtime energy reduction, and then profiles them to dynamically scale the voltage and frequency of the microprocessor at appropriate points during execution. In our simulation, our approach achieves energy savings by an average of 39% with minor performance degradation, compared to a processor running at a fixed voltage and speed.

Energy-Oriented Maintenance Decision-Making for Sustainable Manufacturing Based on Energy Saving Window

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
Tangbin Xia ◽  
Lifeng Xi ◽  
Shichang Du ◽  
Lei Xiao ◽  
Ershun Pan
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Energy Savings ◽  
Sustainable Manufacturing ◽  
Green Manufacturing ◽  
Energy Reduction ◽  
Efficient Manner ◽  
Line Energy ◽  
Industrial Enterprises ◽  
Attribute Model

In recent years, the industry's responsibility to join in sustainable manufacturing becomes huge, while innovating sustainability has been a new trend. Industrial enterprises are pursuing energy reduction to meet future needs for sustainable globalization and government legislations for green manufacturing. To run a manufacturing line in an energy-efficient manner, an energy-oriented maintenance methodology is developed. At the machine layer, the multi-attribute model (MAM) method is extended by modeling the energy attribute. Preventive maintenance (PM) intervals of each machine are dynamically scheduled according to the machine deterioration, maintenance effects, and environmental conditions. At the system layer, a novel energy saving window (ESW) policy is proposed to reduce energy for the whole line. Energy consumption interactivities, batch production characteristics, and system-layer maintenance opportunities are comprehensively considered. Real-time choice of PM adjustments is scheduled by comparing the energy savings of advanced PM and delayed PM. The results prove the energy reduction achieved by this MAM-ESW methodology. It effectively utilizes standby power, reduces energy consumption, avoids manufacturing breakdown, and decreases scheduling complexity. Furthermore, this energy-oriented maintenance framework can be applied not only in the automotive industry but also for a broader range of manufacturing domains such as the aerospace, semiconductor, and chemical industries.

scholarly journals An Exhaustive Search Energy Optimization Method for Residential Building Envelope in Different Climatic Zones of Kazakhstan

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 633
Author(s):  
Mirzhan Kaderzhanov ◽  
Shazim Ali Memon ◽  
Assemgul Saurbayeva ◽  
Jong R. Kim
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Residential Buildings ◽  
Average Energy ◽  
Optimization Method ◽  
Building Envelope ◽  
Energy Reduction ◽  
Estimation Model ◽  
Total Energy Consumption ◽  
Energy Estimation

Nowadays, the residential sector of Kazakhstan accounts for about 30% of the total energy consumption. Therefore, it is essential to analyze the energy estimation model for residential buildings in Kazakhstan so as to reduce energy consumption. This research is aimed to develop the Overall Thermal Transfer Value (OTTV) based Building Energy Simulation Model (BESM) for the reduction of energy consumption through the envelope of residential buildings in seven cities of Kazakhstan. A brute force optimization method was adopted to obtain the optimal envelope configuration varying window-to-wall ratio (WWR), the angle of a pitched roof, the depth of the overhang shading system, the thermal conductivity, and the thicknesses of wall composition materials. In addition, orientation-related analyses of the optimized cases were conducted. Finally, the economic evaluation of the base and optimized cases were presented. The results showed that an average energy reduction for heating was 6156.8 kWh, while for cooling it was almost 1912.17 kWh. The heating and cooling energy savings were 16.59% and 16.69%, respectively. The frontage of the building model directed towards the south in the cold season and north in the hot season demonstrated around 21% and 32% of energy reduction, respectively. The energy cost savings varied between 9657 to 119,221 ₸ for heating, 9622 to 36,088 ₸ for cooling.

scholarly journals Achieving an 80% reduction in Ontario residential heating energy consumption by 2030: a tiered framework and preliminary implementation strategy

2021 ◽  
Author(s):  
Amanda Jacqueline Yip
Keyword(s):  
Energy Consumption ◽  
Perceived Risk ◽  
Implementation Strategy ◽  
Energy Savings ◽  
Residential Buildings ◽  
Climate Change Impacts ◽  
Energy Reduction ◽  
Energy Prices ◽  
Residential Heating ◽  
Heating Energy Consumption

The increasing prevalence of climate change impacts and rising energy prices has highlighted the need to achieve deep energy savings now. To accomplish this, stricter prescriptive performance requirements for residential buildings are needed. The intent of this work is to develop a framework and policy implementation strategy to achieve an 80% reduction in Ontario residential heating energy consumption by 2030. A tiered framework of consumption targets was developed using OBC 2012 SB-12 requirements as a baseline and sample compliance packages created for each tier. Construction costs for the baseline and each tier compliance package were estimated and simple payback periods determined. Impacts of fuel escalation rates on payback periods were also considered. Significant cost premiums were found between the baseline consumption and overall 80% heating energy reduction target. Lack of experience and perceived risk were found to be the greatest barriers to achieving the overall energy reduction target. A preliminary strategy and supporting policy tools was developed, taking into consideration the observed barriers to adoption.

scholarly journals Evaluating the Energy Consumption of Mobile Data Transfer—From Technology Development to Consumer Behaviour and Life Cycle Thinking

2018 ◽  
Vol 10 (7) ◽  
pp. 2494 ◽  
Author(s):  
Hanna Pihkola ◽  
Mikko Hongisto ◽  
Olli Apilo ◽  
Mika Lasanen
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Mobile Networks ◽  
Energy Demand ◽  
Consumer Behaviour ◽  
Energy Use ◽  
Energy Savings ◽  
Data Transfer ◽  
Life Cycle Thinking ◽  
Mobile Data

Mobile data consumption in Finland is among the highest in the world. The increase in mobile data usage has been rapid and continual future growth is foreseen. Simultaneously, consumer behaviour is changing. While new end-user devices are more and more energy-efficient and energy consumption per transferred gigabyte has significantly decreased, people spend more time and consume more data via their mobile devices than ever before. Does the increased usage outweigh the energy savings that have been achieved? What options are available for tackling increasing energy demand? And should consumers have a role to play in this discussion? This paper examines the current and future trends that results from the energy consumption of mobile data transfer and mobile networks in Finland. The findings presented in this paper are based on a top-down energy intensity estimate and publicly available data, which was employed to construct an illustrative trend (kWh/gigabyte) for the energy consumption of transmitted mobile data for the years 2010–2017. In addition, energy consumption related to mobile data transfer is discussed from a life cycle perspective, considering both direct and indirect energy use. Finally, the challenges in conducting such assessments are examined.

scholarly journals Achieving an 80% reduction in Ontario residential heating energy consumption by 2030: a tiered framework and preliminary implementation strategy

2021 ◽  
Author(s):  
Amanda Jacqueline Yip
Keyword(s):  
Energy Consumption ◽  
Perceived Risk ◽  
Implementation Strategy ◽  
Energy Savings ◽  
Residential Buildings ◽  
Climate Change Impacts ◽  
Energy Reduction ◽  
Energy Prices ◽  
Residential Heating ◽  
Heating Energy Consumption

The increasing prevalence of climate change impacts and rising energy prices has highlighted the need to achieve deep energy savings now. To accomplish this, stricter prescriptive performance requirements for residential buildings are needed. The intent of this work is to develop a framework and policy implementation strategy to achieve an 80% reduction in Ontario residential heating energy consumption by 2030. A tiered framework of consumption targets was developed using OBC 2012 SB-12 requirements as a baseline and sample compliance packages created for each tier. Construction costs for the baseline and each tier compliance package were estimated and simple payback periods determined. Impacts of fuel escalation rates on payback periods were also considered. Significant cost premiums were found between the baseline consumption and overall 80% heating energy reduction target. Lack of experience and perceived risk were found to be the greatest barriers to achieving the overall energy reduction target. A preliminary strategy and supporting policy tools was developed, taking into consideration the observed barriers to adoption.

scholarly journals Toward Building Energy Reduction Through Solar Energy Systems Retrofit Options: An Equest Model

2018 ◽  
Vol 8 (1) ◽  
pp. 53-60
Author(s):  
M. Javad Dehghani ◽  
P. McManamon ◽  
A. Ataei
Keyword(s):  
Energy Consumption ◽  
Solar System ◽  
Energy Savings ◽  
Building Energy ◽  
Energy Reduction ◽  
Office Building ◽  
Combined System ◽  
Total Energy Consumption ◽  
Photovoltaic Array ◽  
Efficiency Measures

Abstract Office buildings are responsible for a great portion of total energy consumption. In this study, solar system based retrofitting measures such as daylighting control system (DCS), Trombe wall (TW) and photovoltaic (PV) systems are modeled to an office building located in Dayton, Ohio, United States. An energy modeling tool, eQuest is utilized to analyze the economic and environmental impacts of the proposed single retrofitting measures along with the combined measure to identify the optimized building energy reduction opportunity. Compared to the baseline energy consumption, adopting single energy efficiency measures such as PV, DCS, TW, and overhangs/fins to windows results in about 25, 10, 9, 1 percentages of energy reduction respectively. In terms of economic perspectives, overhang and fins provide the best simply payback time around 1 year. Other solar system based retrofitting measures such as TW, DCS and PV can provide economic simple payback with 1.5, 2.5, and 12 years respectively. PV turned out to be the most costly options although it provides the largest energy savings which lead to the largest CO2 reductions. Adopting the combined system along with 50 kW photovoltaic array to the rooftop results in 45 percent office building energy reduction.

Saving Primary Energy Consumption Through Exergy Analysis of Combine Distillation and Power Plant

2012 ◽  
Vol 9 (2) ◽  
pp. 65
Author(s):  
Alhassan Salami Tijani ◽  
Nazri Mohammed ◽  
Werner Witt
Keyword(s):  
Energy Consumption ◽  
Power Plant ◽  
Heat Pump ◽  
Heat Recovery ◽  
Energy Savings ◽  
Primary Energy ◽  
Heat Pumps ◽  
Saturated Steam ◽  
Distillation Unit ◽  
Primary Energy Consumption

Industrial heat pumps are heat-recovery systems that allow the temperature ofwaste-heat stream to be increased to a higher, more efficient temperature. Consequently, heat pumps can improve energy efficiency in industrial processes as well as energy savings when conventional passive-heat recovery is not possible. In this paper, possible ways of saving energy in the chemical industry are considered, the objective is to reduce the primary energy (such as coal) consumption of power plant. Particularly the thermodynamic analyses ofintegrating backpressure turbine ofa power plant with distillation units have been considered. Some practical examples such as conventional distillation unit and heat pump are used as a means of reducing primary energy consumption with tangible indications of energy savings. The heat pump distillation is operated via electrical power from the power plant. The exergy efficiency ofthe primary fuel is calculated for different operating range ofthe heat pump distillation. This is then compared with a conventional distillation unit that depends on saturated steam from a power plant as the source of energy. The results obtained show that heat pump distillation is an economic way to save energy if the temperaturedifference between the overhead and the bottom is small. Based on the result, the energy saved by the application of a heat pump distillation is improved compared to conventional distillation unit.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

scholarly journals Freely scalable and reconfigurable optical hardware for deep learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Liane Bernstein ◽  
Alexander Sludds ◽  
Ryan Hamerly ◽  
Vivienne Sze ◽  
Joel Emer ◽  
...  
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Data Transfer ◽  
Power Delivery ◽  
Optical Data ◽  
Optical Multicast ◽  
Optical Neural Network ◽  
Fully Connected ◽  
Management Power

AbstractAs deep neural network (DNN) models grow ever-larger, they can achieve higher accuracy and solve more complex problems. This trend has been enabled by an increase in available compute power; however, efforts to continue to scale electronic processors are impeded by the costs of communication, thermal management, power delivery and clocking. To improve scalability, we propose a digital optical neural network (DONN) with intralayer optical interconnects and reconfigurable input values. The path-length-independence of optical energy consumption enables information locality between a transmitter and a large number of arbitrarily arranged receivers, which allows greater flexibility in architecture design to circumvent scaling limitations. In a proof-of-concept experiment, we demonstrate optical multicast in the classification of 500 MNIST images with a 3-layer, fully-connected network. We also analyze the energy consumption of the DONN and find that digital optical data transfer is beneficial over electronics when the spacing of computational units is on the order of $$>10\,\upmu $$ > 10 μ m.

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