Energy-aware scheduling in distributed computing systems

Distributed computing systems, such as data centers, are key for supporting modern computing demands. However, the energy consumption of data centers has become a major concern over the last decade. Worldwide energy consumption in 2012 was estimated to be around 270 TWh, and grim forecasts predict it will quadruple by 2030. Maximizing energy efficiency while also maximizing computing efficiency is a major challenge for modern data centers. This work addresses this challenge by scheduling the operation of modern data centers, considering a multi-objective approach for simultaneously optimizing both efficiency objectives. Multiple data center scenarios are studied, such as scheduling a single data center and scheduling a federation of several geographically-distributed data centers. Mathematical models are formulated for each scenario, considering the modeling of their most relevant components such as computing resources, computing workload, cooling system, networking, and green energy generators, among others. A set of accurate heuristic and metaheuristic algorithms are designed for addressing the scheduling problem. These scheduling algorithms are comprehensively studied, and compared with each other, using statistical tools to evaluate their efficacy when addressing realistic workloads and scenarios. Experimental results show the designed scheduling algorithms are able to significantly increase the energy efficiency of data centers when compared to traditional scheduling methods, while providing a diverse set of trade-off solutions regarding the computing efficiency of the data center. These results confirm the effectiveness of the proposed algorithmic approaches for data center infrastructures.Los sistemas informáticos distribuidos, como los centros de datos, son clave para satisfacer la demanda informática moderna. Sin embargo, su consumo de energético se ha convertido en una gran preocupación. Se estima que mundialmente su consumo energético rondó los 270 TWh en el año 2012, y algunos prevén que este consumo se cuadruplicará para el año 2030. Maximizar simultáneamente la eficiencia energética y computacional de los centros de datos es un desafío crítico. Esta tesis aborda dicho desafío mediante la planificación de la operativa del centro de datos considerando un enfoque multiobjetivo para optimizar simultáneamente ambos objetivos de eficiencia. En esta tesis se estudian múltiples variantes del problema, desde la planificación de un único centro de datos hasta la de una federación de múltiples centros de datos geográficmentea distribuidos. Para esto, se formulan modelos matemáticos para cada variante del problema, modelado sus componentes más relevantes, como: recursos computacionales, carga de trabajo, refrigeración, redes, energía verde, etc. Para resolver el problema de planificación planteado, se diseñan un conjunto de algoritmos heurísticos y metaheurísticos. Estos son estudiados exhaustivamente y su eficiencia es evaluada utilizando una batería de herramientas estadísticas. Los resultados experimentales muestran que los algoritmos de planificación diseñados son capaces de aumentar significativamente la eficiencia energética de un centros de datos en comparación con métodos tradicionales planificación. A su vez, los métodos propuestos proporcionan un conjunto diverso de soluciones con diferente nivel de compromiso respecto a la eficiencia computacional del centro de datos. Estos resultados confirman la eficacia del enfoque algorítmico propuesto

Energy-aware scheduling in heterogeneous computing systems

In the last decade, the grid computing systems emerged as useful provider of the computing power required for solving complex problems. The classic formulation of the scheduling problem in heterogeneous computing systems is NP-hard, thus approximation techniques are required for solving real-world scenarios of this problem. This thesis tackles the problem of scheduling tasks in a heterogeneous computing environment in reduced execution times, considering the schedule length and the total energy consumption as the optimization objectives. An efficient multithreading local search algorithm for solving the multi-objective scheduling problem in heterogeneous computing systems, named MEMLS, is presented. The proposed method follows a fully multi-objective approach, applying a Pareto-based dominance search that is executed in parallel by using several threads. The experimental analysis demonstrates that the new multithreading algorithm outperforms a set of fast and accurate two-phase deterministic heuristics based on the traditional MinMin. The new ME-MLS method is able to achieve significant improvements in both makespan and energy consumption objectives in reduced execution times for a large set of testbed instances, while exhibiting very good scalability. The ME-MLS was evaluated solving instances comprised of up to 2048 tasks and 64 machines. In order to scale the dimension of the problem instances even further and tackle large-sized problem instances, the Graphical Processing Unit (GPU) architecture is considered. This line of future work has been initially tackled with the gPALS: a hybrid CPU/GPU local search algorithm for efficiently tackling a single-objective heterogeneous computing scheduling problem. The gPALS shows very promising results, being able to tackle instances of up to 32768 tasks and 1024 machines in reasonable execution times.En la última década, los sistemas de computación grid se han convertido en útiles proveedores de la capacidad de cálculo necesaria para la resolución de problemas complejos. En su formulación clásica, el problema de la planificación de tareas en sistemas heterogéneos es un problema NP difícil, por lo que se requieren técnicas de resolución aproximadas para atacar instancias de tamaño realista de este problema. Esta tesis aborda el problema de la planificación de tareas en sistemas heterogéneos, considerando el largo de la planificación y el consumo energético como objetivos a optimizar. Para la resolución de este problema se propone un algoritmo de búsqueda local eficiente y multihilo. El método propuesto se trata de un enfoque plenamente multiobjetivo que consiste en la aplicación de una búsqueda basada en dominancia de Pareto que se ejecuta en paralelo mediante el uso de varios hilos de ejecución. El análisis experimental demuestra que el algoritmo multithilado propuesto supera a un conjunto de heurísticas deterministas rápidas y e caces basadas en el algoritmo MinMin tradicional. El nuevo método, ME-MLS, es capaz de lograr mejoras significativas tanto en el largo de la planificación y como en consumo energético, en tiempos de ejecución reducidos para un gran número de casos de prueba, mientras que exhibe una escalabilidad muy promisoria. El ME-MLS fue evaluado abordando instancias de hasta 2048 tareas y 64 máquinas. Con el n de aumentar la dimensión de las instancias abordadas y hacer frente a instancias de gran tamaño, se consideró la utilización de la arquitectura provista por las unidades de procesamiento gráfico (GPU). Esta línea de trabajo futuro ha sido abordada inicialmente con el algoritmo gPALS: un algoritmo híbrido CPU/GPU de búsqueda local para la planificación de tareas en en sistemas heterogéneos considerando el largo de la planificación como único objetivo. La evaluación del algoritmo gPALS ha mostrado resultados muy prometedores, siendo capaz de abordar instancias de hasta 32768 tareas y 1024 máquinas en tiempos de ejecución razonables

Including accurate user estimates in HPC schedulers: ban empirical analysis

This article focuses on the problem of dealing with low accuracy of job runtime estimates provided by users of high performance computing systems. The main goal of the study is to evaluate the benefits on the system utilization of providing accurate estimations, in order to motivate users to make an effort to provide better estimates. We propose the Penalty Scheduling Policy for including information about user estimates. The experimental evaluation is performed over realistic workload and scenarios, and validated by the use of a job scheduler simulator. We simulated different static and dynamic scenarios, which emulate diverse user behavior regarding the estimation of jobs runtime. Results demonstrate that the accuracy of users runtime estimates influences the waiting time of jobs. Under our proposed policy, in a scenario where users improve their estimates, waiting time of users with high accuracy can be up to 2.43 times lower than users with the lowest accuracy.XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Scientific computing in the Latin America-Europe GISELA grid infrastructure

This work presents the application of parallel computing techniques to solve two scientific computing applications over the Latin America-Europe GISELA grid computing platform. The article describes two scientific computing applications –the semi-automatic processing of historical climate images and a software package for fluid dynamics– which usually require large computing times when applied to realistic scenarios. The proposal of applying parallel computing techniques over the GISELA grid infrastructure is formulated, and the implemented solutions are described. A preliminary experimental analysis is reported, presenting the estimated efficiency gains when using the grid infrastructure.Sociedad Argentina de Informática e Investigación Operativ

Restauración automática de acentos ortográficos en adverbios interrogativos

La omisión de acentos ortograáficos es un error tipográfi co muy frecuente en el idioma español; su restauración automática consiste en la inserción de acentos omitidos en los lugares que son necesarios. Los adverbios interrogativos son un caso especialmente di ficultoso de este problema, ya que en muchas ocasiones no existen marcas claras que indiquen su presencia. Este trabajo presenta dos técnicas de aprendizaje automático, Conditional Random Fields (CRF) y Support Vector Ma- chines (SVM), aplicadas a la resolución del problema de la restauración automática de acentos ortográ cos para el caso especifí co de los adverbios interrogativos. Se obtuvieron buenos resultados con ambas técnicas, siendo sensiblemente superior el resultado obtenido utilizando un clasificador basado en CRF, y que utiliza como atributos los tokens que más comúnmente preceden y siguen a los adverbios interrogativos.Sociedad Argentina de Informática e Investigación Operativ

Including accurate user estimates in HPC schedulers: ban empirical analysis

This article focuses on the problem of dealing with low accuracy of job runtime estimates provided by users of high performance computing systems. The main goal of the study is to evaluate the benefits on the system utilization of providing accurate estimations, in order to motivate users to make an effort to provide better estimates. We propose the Penalty Scheduling Policy for including information about user estimates. The experimental evaluation is performed over realistic workload and scenarios, and validated by the use of a job scheduler simulator. We simulated different static and dynamic scenarios, which emulate diverse user behavior regarding the estimation of jobs runtime. Results demonstrate that the accuracy of users runtime estimates influences the waiting time of jobs. Under our proposed policy, in a scenario where users improve their estimates, waiting time of users with high accuracy can be up to 2.43 times lower than users with the lowest accuracy.XV Workshop de Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI

Genetic variations associated with non- contact muscle injuries in sport: A systematic review

Introduction Non-contact muscle injuries (NCMI) account for a large proportion of sport injuries, affecting athletes’ performance and career, team results and financial aspects. Recently, genetic factors have been attributed a role in the susceptibility of an athlete to sustain NCMI. However, data in this field are only just starting to emerge. Objectives To review available knowledge of genetic variations associated with sport-related NCMI. Methods The databases Pubmed, Scopus, and Web of Science were searched for relevant articles published until February 2021. The records selected for review were original articles published in peer-reviewed journals describing studies that have examined NCMI-related genetic variations in adult subjects (17–60 years) practicing any sport. The data extracted from the studies identified were as follows: general information, and data on genetic polymorphisms and NCMI risk, incidence and recovery time and/or severity. Results Seventeen studies examining 47 genes and 59 polymorphisms were finally included. 29 polymorphisms affecting 25 genes were found significantly associated with NCMI risk, incidence, recovery time, and/or severity. These genes pertain to three functional categories: (i) muscle fiber structural/contractile properties, (ii) muscle repair and regeneration, or (iii) muscle fiber external matrix composition and maintenance. Conclusion Our review confirmed the important role of genetics in NCMI. Some gene variants have practical implications such as differences of several weeks in recovery time detected between genotypes. Knowledge in this field is still in its early stages. Future studies need to examine a wider diversity of sports and standardize their methods and outcome measure

Cariaco (Venezuela) (Sucre) (Golfo). Cartas náuticas (1754). 1:88653

Orientado con lis en rosa de 8 vientos prolongadosIndica veriles, bajos, fondeaderos y sondas batimétricasManuscrito a plumilla en tinta negra y grisSeñala toponimia costeraTítulo enmarcado en cartela decorada con instrumentos geográficosEn el verso: costa firme portulano. Plano del golfo de Cariaco y descripción de la punta de Araya por José Blanco 1754Copia digital. Madrid : Ministerio de Cultura. Dirección General del Libro, Archivos y Bibliotecas, 201

A parallel hybrid evolutionary algorithm for the optimization of broker virtual machines subletting in cloud systems

This article presents a new parallel hybrid evolutionary algorithm to solve the problem of virtual machines subletting in cloud systems. The problem deals with the efficient allocation of a set of virtual machine requests from customers into available pre-booked resources from a cloud broker, in order to maximize the broker profit. The proposed parallel algorithm uses a distributed subpopulations model, and a Simulated Annealing operator. The experimental evaluation analyzes the profit and makespan results of the proposed methods over a set of problem instances that account for realistic workloads and scenarios using real data from cloud providers. A comparison with greedy heuristics indicates that the proposed method is able to compute solutions with up to 133.8% improvement in the profit values, while accounting for accurate makespan results

Genetic analyses place most Spanish isolates of Beauveria bassiana in a molecular group with word-wide distribution

<p>Abstract</p> <p>Background</p> <p>The entomopathogenic anamorphic fungus <it>Beauveria bassiana </it>is currently used as a biocontrol agent (BCA) of insects. Fifty-seven <it>Beauveria bassiana </it>isolates -53 from Spain- were characterized, integrating group I intron insertion patterns at the 3'-end of the nuclear large subunit ribosomal gene (LSU rDNA) and elongation factor 1-alpha (EF1-α) phylogenetic information, in order to assess the genetic structure and diversity of this Spanish collection of <it>B. bassiana</it>.</p> <p>Results</p> <p>Group I intron genotype analysis was based on the four highly conserved insertion sites of the LSU (Ec2653, Ec2449, Ec2066, Ec1921). Of the 16 possible combinations/genotypes, only four were detected, two of which were predominant, containing 44 and 9 members out of 57 isolates, respectively. Interestingly, the members of the latter two genotypes showed unique differences in their growth temperatures. In follow, EF1-α phylogeny served to classify most of the strains in the <it>B. bassiana s.s</it>. (<it>sensu stricto</it>) group and separate them into 5 molecular subgroups, all of which contained a group I intron belonging to the IC1 subtype at the Ec1921 position. A number of parameters such as thermal growth or origin (host, geographic location and climatic conditions) were also examined but in general no association could be found.</p> <p>Conclusion</p> <p>Most Spanish <it>B. bassiana </it>isolates (77.2%) are grouped into a major phylogenetic subgroup with word-wide distribution. However, high phylogenetic diversity was also detected among Spanish isolates from close geographic zones with low climatic variation. In general, no correlation was observed between the molecular distribution and geographic origin or climatic characteristics where the Spanish <it>B. bassiana </it>isolates were sampled.</p