Energy efficiency and performance management of parallel dataflow applications

The energy efficiency of space heaters is rated by Annual Fuel Utilization Efficiency (AFUE) governed by the Department of Energy in the United States which is a simple ratio of usable heat and fuel usage of a single heating device. It doesn't consider the overall performance of the heating system including not only the heating devices but also the characteristics of the building in different applications. The current AFUE method calculates only the energy efficiency which is thermodynamics first law efficiency. In this research, the systematic efficiency of a heating system rather than simple device efficiency has been defined and investigated. The systematic efficiency considers the overall efficiency of the whole heating system and it varies in the different applications even though with the same heating device. So it represents the performance of the system more precisely. Analytical models have been built to calculate both the systematic energy efficiency and exergy efficiency, and to evaluate the systematic energy and exergy efficiency of heating systems for direct fired and indirect fired heaters. Efficiency performances of the systems with these two types of heaters are compared. Sensitivities of input parameters for systematic energy efficiency are studied to show the impact towards systematic energy efficiency. Indoor carbon dioxide concentration level of direct fired heating system is also studied. In a case study, results show that systematic energy efficiency of indirect fired heating system is always constant at heater device efficiency which is 80\% while systematic energy efficiency of direct fired heating system varies from 40%-92% under different condition (heat loss coefficient, ambient temperature and air change requirement), indicating that simple device efficiency is not capable to evaluate the overall performance of heating system. New efficiency method such as systematic energy efficiency used in this research is needed to better describe the performance of the heating system. Results of indoor carbon dioxide level of direct fired heating system, from 1000 to 4500 PPM under different conditions, show that indoor air quality needs to be considered while using direct fired heating.

Future large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance of data intensive parallel applications with various execution patterns running on large scale power-aware clusters. Our analytical model can help users explore the effects of machine and application dependent characteristics on system energy efficiency and isolate efficient ways to scale system parameters (e.g. processor count, CPU power/frequency, workload size and network bandwidth) to balance energy use and performance. We derive our iso-energy-efficiency model and apply it to the NAS Parallel Benchmarks on two power-aware clusters. Our results indicate that the model accurately predicts total system energy consumption within 5% error on average for parallel applications with various execution and communication patterns. We demonstrate effective use of the model for various application contexts and in scalability decision-making.

Power dissipation has become a critical design metric in microprocessor-based system design. In a multi-core system, running multiple applications, power and performance can be dynamically traded off using an integrated power management (PM) unit. This PM unit monitors the performance and power of each core and dynamically adjusts the individual voltages and frequencies in order to maximize system performance under a given power budget (usually set by the operating system). This paper presents a performance and power analysis methodology, featuring a simulation model for multi-core systems that can be easily reconfigured for different scenarios and a PM infrastructure for the exploration and analysis of PM algorithms. Two algorithms have been implemented: one for discrete and one for continuous power modes based on non-linear programming. Extensive experiments are reported, illustrating the effect of power management both at the core and the chip level.

A multicomputer is a loosely coupled multiprocessor architecture, which is also called a cluster computer or just a cluster. It may be assembled from commercially available PCs and networking hardware as a low-cost alternative to rack mounted blades, interconnected through a high speed backplane, or to a high performance, tightly coupled, shared memory multiprocessor. Parallel software applications exploit parallelism in a cluster by distributing chunks of data among its remote nodes for simultaneous processing.Each remote node processes its chunk of data in parallel with the others and returns its partial result back to the master node for combination into a final result. When the chunk size, or system granularity, is just right, there is a balance between the network-transit time and the remote-processing time of the data; the distributed application runs at maximum efficiency and the system granularity is said to be optimal. That said, one wonders why there are no tools explicitly designed to help parallel software designers and performance analysts determine the optimal granularity size of a given cluster!We present a back-to-basics approach, application-level program named McGAT, for Multi-computer Granularity Assessment Tool. The user specifies a range of chunk sizes to analyze, along with a remote node's processing time estimate for a particular sized chunk. McGAT is not a simulation, but a parallel application that runs on the user's hardware, distributing chunks of data to each of the cluster's remote nodes. Each node responds after an amount of time necessary to process that data, based on the user's processing time estimates. McGAT reports system throughput for each chunk size over the user-specified range.The chunk size with the maximum throughput indicates the optimal granularity of the system on which it is run, which is a key parallel software design component. The user may then choose a chunk size that provides maximum throughput within the requirements of his or her specific application.Our presentation includes graphs comparing the results from runs on a 3-, 4-, and 5-node Linux-based PC cluster, interconnected through both 10 and 100 Mbps Ethernet. We plan to expand our knowledge base to include larger numbers of nodes, and a virtual ring to complement or virtual star communications protocol.McGAT may be used to establish a performance baseline, and again later to quantify the effect of any subsequent changes to the cluster. McGAT is offered as open source software, and a beta release for Linux based platforms is available for download from the DSRLab website under the GNU General Public License.

Energy efficiency of the system is always paid more attention in the research of the discharge plasma’s application technology. Based on the project of ballast water treatment technology by multiphase nanosecond pulse discharge cooperated with photocatalysis, the nozzles-plate electrode was adopted, system energy and energy efficiency were investigated with different discharge factors and compared when the nozzles were coated with the titanium dioxide (TiO2) film or not. The results show that cooperating with the photocatalysis, pulsed discharge system power and energy efficiency were not significantly affected. Reactor power increases with the absolute value of the input high voltage and pulse repetition frequency and decreases with the distance between the nozzles and the plate. There are no obvious effects of the numbers of the nozzles and the air flow rate. Energy efficiency of the system increases with the absolute value of the input high voltage, firstly, then decreases. It changes inversely with the air flow rate. The energy efficiency of the system decreases with the pulsed repetition rate and the distance between the nozzles-plate. It was up to 25.7% with the input voltage of - 30 kV, and the air flow rate of 80 mL/min, pulse repetition frequency of 50 Hz and 6 nozzles- plate distance of 0.5 cm.

With the development of smart grid technology, power energy efficiency evaluation will be driven to become more intelligent and professional. In order to achieve energy conservation and low-carbon economy, energy efficiency technologies need to be improved. The application of energy efficient technologies has to be enhanced from the supply side, power grid side and demand-side in order to raise energy efficiency effects and update energy conservation technologies. The key technologies, system architecture and advanced applications of demand-side power efficiency evaluation and management system were described in detail in this paper. The monitoring model, efficiency analysis, and optimized control of energy efficiency management system were also elaborated with case studies. The impact and prospect of this technology were finally analyzed.

Energy, exergy and economic (3E) analyses of a novel DME-power polygeneration system with CO2 capture based on biomass gasification

Dynamic power management features are now an integral part of processor chip and system design. Dynamic voltage and frequency scaling (DVFS), core folding and per-core power gating (PCPG) are power control actuators (or knobs) that are available in modern multi-core systems. However, figuring out the actuation protocol for such knobs in order to achieve maximum efficiency has so far remained an open research problem. In the context of specific system utilization dynamics, the desirable order of applying these knobs is not easy to determine. For complexity-effective algorithm development, DVFS, core folding and PCPG control methods have evolved in a somewhat decoupled manner. However, as we show in this paper, independent actuation of these techniques can lead to conflicting decisions that jeopardize the system in terms of power-performance efficiency. Therefore, a more robust coordination protocol is necessary in orchestrating the power management functions. Heuristics for achieving such coordinated control are already becoming available in server systems. It remains an open research problem to optimally adjust power and performance management options at runtime for a wide range of time-varying workload applications, environmental conditions, and power constraints. This research paper contributes a novel approach for a systematically architected, robust, multi-knob power management protocol, which we empirically analyze on live server systems. We use a latest generation POWER7+ multi-core system to demonstrate the benefits of our proposed new coordinated power management algorithm (called PAMPA). We report measurement-based analysis to show that PAMPA achieves comparable power-performance efficiencies (relative to a baseline decoupled control system) while achieving conflict-free actuation and robust operation.

Conventional off-chip voltage regulators are typically bulky and slow, and are inefficient at exploiting system and workload variability using Dynamic Voltage and Frequency Scaling (DVFS). On-die integration of voltage regulators has the potential to increase the energy efficiency of computer systems by enabling power control at a fine granularity in both space and time. The energy conversion efficiency of on-chip regulators, however, is typically much lower than off-chip regulators, which results in significant energy losses. Fine-grained power control and high voltage regulator efficiency are difficult to achieve simultaneously, with either emerging on-chip or conventional off-chip regulators. A voltage conversion framework that relies on a hierarchy of off-chip switching regulators and on-chip linear regulators is proposed to enable fine-grained power control with a regulator efficiency greater than 90%. A DVFS control policy that is based on a reinforcement learning (RL) approach is developed to exploit the proposed framework. Per-core RL agents learn and improve their control policies independently, while retaining the ability to coordinate their actions to accomplish system level power management objectives. When evaluated on a mix of 14 parallel and 13 multiprogrammed workloads, the proposed voltage conversion framework achieves 18% greater energy efficiency than a conventional framework that uses on-chip switching regulators. Moreover, when the RL based DVFS control policy is used to control the proposed voltage conversion framework, the system achieves a 21% higher energy efficiency over a baseline oracle policy with coarse-grained power control capability.

Crude oil resources in the world continue to diminish; automobile, agricultural machinery and construction machinery manufacturing companies are placing more emphasis on energy efficient series hydraulic hybrid systems which can replace their conventional transmission systems. Series hydraulic hybrid system is a mechatronics system with two source of power (that includes prime mover and hydro-pneumatic accumulator) which drives the vehicle. Even though, it has been proven as an energy efficient system, sizing of the components or sub-system for automobiles has got a major influence on energy efficiency of vehicle. In this paper, a power bond graph approach is used to model the dynamics of series hydraulic hybrid system and simulation results elucidate various modes of operations. It also shows the dynamic response of hydro-pneumatic accumulator, prime-mover and system output speed. Further, design optimization of system is carried out to optimize the physical /process parameters for the maximum system's output energy that, leads to increase in energy efficiency and environmental friendly vehicle.

Efficient power management in Hybrid Energy Storage Systems (HESS) for off-grid PV inverters remains a challenge, particularly in terms of energy efficiency and battery degradation mitigation. In this context, this paper proposes a Model Predictive Control (MPC) based power management designed to mitigate Li-ion battery degradation while improving the overall system efficiency. To validate this proposal, extensive experimental results are presented. The proposed formulation aims to minimize battery stress by smoothing the current profile and reducing cycling effects. The performance of the MPC power management is verified through a comparative experimental analysis of four distinct strategies: rule-based, frequency-filtering, a benchmark MPC, and the proposed MPC. Evaluation is based on four key metrics: RMS current, total power losses, Equivalent Full Cycles (EFC), and State of Health variation (ΔSOH). Experimental results demonstrate that the proposed method outperforms the compared strategies across all evaluated criteria, significantly reducing battery stress in terms of cycling and current distribution. Furthermore, long-term simulations corroborate these findings, showing a substantial reduction in battery degradation compared to other established methods. These results confirm that the proposed method, provides a robust solution for mitigating battery degradation in hybrid inverter applications.

This document highlights Energy Efficiency (EE) in agricultural production systems through the analysis of the life-cycle of publications in Scopus database, along with the help of SigmaPlot and SciMAT software. Among the results obtained; the growth rate on publications was determined until 2019, with trends in EE research in the agricultural sector. According to the search formulas "energy efficiency" (LIMIT-TO (DOCTYPE, "ar)) and "energy efficiency AND agriculture" (LIMIT-TO (DOCTYPE," ar), which made visible the scientific projection according to the inflection point, as well as the most important motor issues, where those related to soil, water, climatic variability, crops, nitrogen and phosphorus are emphasized, being The United States the country with the greatest scientific dissemination in this regard. In addition, publications and institutions relevant to the case of Colombia were established through TAK ("energy efficiency" AND agriculture) AND (LIMIT-TO (AFFILCOUNTRY, "Colombia").

The theoretical and methodological principles of the formation of energy efficiency management have been clarified. The concepts of “energy efficiency of technical systems”, “energy efficiency of biological systems”, “energy efficiency of socio-economic systems”, “energy efficiency of a business entity”, and “energy efficiency of a territorial community” have been distinguished. It has been proven that increasing the energy efficiency of economic entities in the context of territorial community development should not allow: deterioration of working conditions of economic entity’s personnel and life safety of residents of communities (imperative of the human factor); complication of the ecological situation on the community territory (ecological imperative); reduction of economic efficiency of a business entity and well-being of the community population (priority of economic assessment). The types of energy effect of the territorial community have been established. The essence of the concepts of “energy saving efficiency of territorial community” and “energy saving effect of territorial community” have been defined. The types of energy saving effect of the territorial community have been reasoned. The fuel flow matrix has been formed. The functional components of the energy efficiency management process have been defined. The directions for optimization of energy flows in territorial communities have been substantiated as follows: the choice of energy supply enterprises; optimization of energy resource delivery routes; substantiation of energy-optimal sizes and structure of the transport fleet of territorial communities and oil industry (if available); optimization of storage stocks of energy resources and their management.

Energy efficiency (EE) performance of millimeter-wave (mmWave) large-array systems attracts a lot of attention. And insertion loss is an inherent characteristic of hybrid precoding systems, which greatly reduces the system performance. EE analysis considering the insertion loss based on the dynamic array architecture is still an open issue. This paper researches the ergodic EE of mmWave hybrid pre-coding system with the insertion loss, based on the adaptive overlapped subarray (OSA) architecture. The ergodic EE is a more valuable indicator than the instantaneous EE for the system under dynamic architecture. However, it is difficult to directly calculate the precise ergodic EE due to the intractable relationship between EE and the channel matrix. Instead, we simplify the precise ergodic EE to get a lower bound, and analyze the ergodic EE performance based upon the lower bound. By this way, we analyze the ergodic EE performance of two typical hybrid pre-coding schemes taking the dynamic architectures. Simulation results verify the effectiveness of analyses.

Objective. The goal of the study is to identify ways to improve energy efficiency by conducting a comprehensive analysis of engineering systems of a house, taking into account the existing model of energy supply and by monitoring the indicators of influence on the efficiency of engineering and technical equipment. Methods. The main method is based on a survey of the level of energy efficiency of heating and hot water supply systems. Results. The article discusses the concept of energy efficiency of a building, energy efficiency class, main utility systems of a residential building, indicators of influence on the state of systems, engineering component and ways to improve it. The article addresses issues related to a full analysis of existing systems in order to assess the implementation of necessary energy-saving measures, as well as their risks and benefits. The possibilities of controlling energy consumption and efficiency of works carried out due to the reconstruction of utility systems of the building have been determined. The results of the analysis of energy-efficient measures, and the feasibility of implementing each of them have been determined in order to identify optimal solutions. Conclusion. Increasing the energy efficiency of building utility systems is one of the priority tasks for creating comfortable living conditions. The energy efficiency class of building utility systems is established according to the state of a system, takes into account all quality indicators for energy consumption, and the energy certificate fully shows the level of energy efficiency.