Effects of Continuous vs Discrete Frequency Scaling and Core Allocation on Energy Efficiency of Static Schedules for Moldable Tasks

2021 ◽  
Author(s):  
Sebastian Litzinger ◽  
Jörg Keller
Keyword(s):  
Energy Efficiency ◽  
Parallel Machines ◽  
Frequency Scaling ◽  
Task Execution ◽  
Core Allocation ◽  
Time Frequency ◽  
Discrete Frequency ◽  
Continuous Frequency ◽  
Time And Energy ◽  
Task Sets

Models for energy-efficient static scheduling of parallelizable tasks with deadlines on frequency-scalable parallel machines comprise moldable vs. malleable tasks and continuous vs. discrete frequency levels, plus preemptive vs. non-preemptive task execution with or without task migration. We investigate the tradeoff between scheduling time and energy efficiency when going from continuous to discrete core allocation and frequency levels on a multicore processor, and from preemptive to non-preemptive task execution. To this end, we present a tool to convert a schedule computed for malleable tasks on machines with continuous frequency scaling [Sanders and Speck, Euro-Par (2012)] into one for moldable tasks on a machine with discrete frequency levels. We compare the energy efficiency of the converted schedule to the energy consumed by a schedule produced by the integrated crown scheduler [Melot et al., ACM TACO (2015)] for moldable tasks and a machine with discrete frequency levels. Our experiments with synthetic and application-based task sets indicate that the converted Sanders Speck schedules, while computed faster, consume more energy on average than crown schedules. Surprisingly, it is not the step from malleable to moldable tasks that is responsible but the step from continuous to discrete frequency levels. One-time frequency scaling during a task’s execution can compensate for most of the energy overhead caused by frequency discretization.

scholarly journals Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling

Sensors ◽  
2016 ◽  
Vol 16 (7) ◽  
pp. 1091 ◽  
Author(s):  
Ze Yu ◽  
Peng Lin ◽  
Peng Xiao ◽  
Lihong Kang ◽  
Chunsheng Li
Keyword(s):  
Frequency Scaling ◽  
Spatial Variance ◽  
Time Frequency ◽  
Sar Imaging

scholarly journals ASPEK PENGETAHUAN, SIKAP DAN KETERAMPILAN PADA RESPON PETANI TERHADAP UPJA DI KECAMATAN TOHO

2019 ◽  
Vol 8 (2) ◽  
pp. 13
Author(s):  
Ellyta Ellyta ◽  
Mulyati Mulyati ◽  
Hery Medianto Kurniawan ◽  
Ekawati Ekawati
Keyword(s):  
Energy Efficiency ◽  
Research Method ◽  
Descriptive Analysis ◽  
Analysis Data ◽  
Likert Scale ◽  
Response Analysis ◽  
Agricultural Machinery ◽  
Service Unit ◽  
Delayed Development ◽  
Time And Energy

The use of agricultural tools and machinery has become a primary needs of farmers in processing and increasing their farming production, this activity encourages the emergence of agricultural tools and machinery service unit (UPJA) that has an intention in assistaining farmers in achieving time and energy efficiency and also in order to overcome scarcity of farmer resources in processing their farming. However, the delayed development of UPJA in several regions has encouraged this research in order to analyze farmers' responses to the use of agricultural tools and machinery service unit. Research method: This study was conducted at the Bukit Raya UPJA Village Pak Leheng Toho District from January - March 2018. This research used the descriptive analysis data, which was displayed in table form with several categories that have been determined based on aspects of knowledge, attitude, and skills. Response measurements were carried out using a Likert scale (scoring) with a score of 1-5. The results of the all of the farmer showed that the response analysis from the aspects of knowledge, attitude, and skills of UPJA Bukit Raya amounted to 3.48 in the good category, which means that farmers generally gave a good respond to the existence of the UPJA Bukit Raya Village, in Pak Leheng Village, Toho District.Keywords: Agricultural Machinery, Farmer Energy Efficiency, Likert Scale

scholarly journals Big Steps Towards Query Eco-Processing - Thinking Smart

2021 ◽  
Vol Volume 34 - 2020 - Special... ◽  
Author(s):  
Simon Pierre Dembele ◽  
Ladjel Bellatreche ◽  
Carlos Ordonez ◽  
Nabil Gmati ◽  
Mathieu Roche ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Cost Models ◽  
It Systems ◽  
Environmentally Responsible ◽  
International Audience ◽  
Query Optimizers ◽  
Carbon Dioxide Co2 ◽  
Time And Energy ◽  
Sensitive Parameters

Soumission à Episciences International audience Computers and electronic machines in businesses consume a significant amount of electricity, releasing carbon dioxide (CO2), which contributes to greenhouse gas emissions. Energy efficiency is a pressing concern in IT systems, ranging from mobile devices to large servers in data centers, in order to be more environmentally responsible. In order to meet the growing demands in the awareness of excessive energy consumption, many initiatives have been launched on energy efficiency for big data processing covering electronic components, software and applications. Query optimizers are one of the most power consuming components of a DBMS. They can be modified to take into account the energetical cost of query plans by using energy-based cost models with the aim of reducing the power consumption of computer systems. In this paper, we study, describe and evaluate the design of three energy cost models whose values of energy sensitive parameters are determined using the Nonlinear Regression and the Random Forests techniques. To this end, we study in depth the operating principle of the selected DBMS and present an analysis comparing the performance time and energy consumption of typical queries in the TPC benchmark. We perform extensive experiments on a physical testbed based on PostreSQL, MontetDB and Hyrise systems using workloads generatedusing our chosen benchmark to validate our proposal. Les ordinateurs et les machines électroniques des entreprises consomment une quantité importante d’électricité, libérant ainsi du dioxyde de carbone (CO2), qui contribue aux émissions de gaz à effet de serre. L’efficacité énergétique est une préoccupation urgente dans les systèmesinformatiques, partant des équipements mobiles aux grands serveurs dans les centres de données, afin d’être plus respectueux envers l’environnement. Afin de répondre aux exigences croissantes en matière de sensibilisation à l’utilisation excessive de l’énergie, de nombreuses initiatives ont été lancées sur l’efficacité énergétique pour le traitement des données massives couvrant les composantsélectroniques, les logiciels et les applications. Les optimiseurs de requêtes sont l’un des composants les plus énergivores d’un SGBD. Ils peuvent être modifiés pour prendre en compte le coût énergétique des plans des requêtes à l’aide des modèles de coût énergétiques intégrés dans l’optimiseur dans le but de réduire la consommation électrique des systèmes informatiques. Dans cet article, nousétudions, décrivons et évaluons la conception de trois modèles de coût énergétique dont les valeurs des paramètres sensibles à l’énergie sont définis en utilisant la technique de la Régression non linéaire et la technique des forêts aléatoires. Pour ce fait, nous menons une étude approfondie du principe de fonctionnement des SGBD choisis et présentons une analyse des performances en termes de temps et énergie sur des requêtes typiques du benchmarks TPC-H. Nous effectuons des expériences approfondies basées sur les systèmes PostgreSQL, MonetDB et Hyrise en utilisant un jeu de données généré à partir du benchmarks TPC-H afin de valider nos propositions.

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