Metascheduling of HPC Jobs in Day-Ahead Electricity Markets

High performance grid computing is a key enabler of large scale collaborative computational science. With the promise of exascale computing, high performance grid systems are expected to incur electricity bills that grow super-linearly over time. In order to achieve cost effectiveness in these systems, it is essential for the scheduling algorithms to exploit electricity price variations, both in space and time, that are prevalent in the dynamic electricity price markets. In this paper, we present a metascheduling algorithm to optimize the placement of jobs in a compute grid which consumes electricity from the day-ahead wholesale market. We formulate the scheduling problem as a Minimum Cost Maximum Flow problem and leverage queue waiting time and electricity price predictions to accurately estimate the cost of job execution at a system. Using trace based simulation with real and synthetic workload traces, and real electricity price data sets, we demonstrate our approach on two currently operational grids, XSEDE and NorduGrid. Our experimental setup collectively constitute more than 433K processors spread across 58 compute systems in 17 geographically distributed locations. Experiments show that our approach simultaneously optimizes the total electricity cost and the average response time of the grid, without being unfair to users of the local batch systems.Comment: Appears in IEEE Transactions on Parallel and Distributed System

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

User-aware performance evaluation and optimization of parallel job schedulers

Die Dissertation User-Aware Performance Evaluation and Optimization of Parallel Job Schedulers beschäftigt sich mit der realitätsnahen, dynamischen Simulation und Optimierung von Lastsituationen in parallelen Rechensystemen unter Berücksichtigung von Feedback-Effekten zwischen Performance und Nutzerverhalten. Die Besonderheit solcher Systeme liegt in der geteilten Nutzung durch mehrere Anwender, was zu einer Einschr änkung der Verfügbarkeit von Ressourcen führt. Sollten nicht alle Rechenanfragen, die sogenannten Jobs, gleichzeitig ausgeführt werden können, werden diese in Warteschlangen zwischengespeichert. Da das Verhalten der Nutzer nicht genau bekannt ist, entsteht eine große Unsicherheit bezüglich zukünftiger Lastsituationen. Ziel ist es, Methoden zu finden, die eine Ressourcenzuweisung erzeugt, die den Zielvorstellungen der Nutzer soweit wie möglich entspricht und diese Methoden realistisch zu evaluieren. Dabei ist auch zu berücksichtigen, dass das Nutzerverhalten und die Zielvorstellungen der Nutzer in Abhängigkeit von der Lastsituation und der Ressourcenzuweisung variieren. Es wird ein dreigliedriger Forschungsansatz gewählt: Analyse von Nutzerverhalten unter Ressourcenbeschränkung: In Traces von parallelen Rechensystem zeigt sich, dass die Wartezeit auf Rechenergebnisse mit dem zukünftigen Nutzerverhalten korreliert, d.h. dass es im Durchschnitt länger dauert bis ein Nutzer, der lange warten musste, erneut das System nutzt. Im Rahmen des Promotionsprojekts wurde diese Analyse fortgesetzt und zusätzliche Korrelationen zwischen weiteren Systemparametern (neben der Wartezeit) und Nutzerverhalten aufgedeckt. Des Weiteren wurden Funktionen zur Zufriedenheit und Reaktion von Nutzern auf variierende Antwortzeiten von Rechensystemen entwickelt. Diese Ergebnisse wurden durch eine Umfrage unter Nutzern von Parallelrechner an der TU Dortmund erzielt, für die ein spezieller Frageboden entwickelt wurde. Modellierung von Nutzerverhalten und Feedback Wegen des dynamischen Zusammenhangs zwischen Systemgeschwindigkeit und Nutzerverhalten ist es nötig, Zuweisungsstrategien in dynamischen, feedback-getriebenen Simulationen zu evaluieren. Hierzu wurde ein mehrstufiges Nutzermodell entwickelt, welches die aktuellen Annahmen an Nutzerverhalten beinhaltet und das zukünftige Hinzufügen von zusätzlichen Verhaltenskomponenten ermöglicht. Die Kernelemente umfassen bisher Modelle für den Tages- und Nachtrhythmus, den Arbeitsrhythmus und Eigenschaften der submittierten Jobs. Das dynamische Feedback ist derart gestaltet, dass erst die Fertigstellung von bestimmten Jobs die zukünftige Jobeinreichung auslöst. Optimierung der Allokationsstrategien zur Steigerung der Nutzerzufriedenheit Die mit Hilfe des Fragebogens entwickelte Wartezeitakzeptanz von Nutzern ist durch ein MILP optimiert worden. Das MILP sucht nach Lösungen, die möglichst viele Jobs innerhalb eines akzeptierten Wartezeitfensters startet bzw. die Summe der Verspätungen minimiert. Durch die Komplexität dieses Optimierungsalgorithmus besteht die Evaluation bisher nur auf fixierten, statischen Szenarien, die Abbilder bestimmter System- und Warteschlangenzustände abbilden. Deswegen ist weiterhin geplant, Schedulingverfahren zur Steigerung der Anzahl an eingereichten Jobs und der Wartezeitzufriedenheit mit Hilfe des dynamischen Modells zu evaluieren

Concepts, reflections and applications of social equity: approaches to accessibility to primary goods and services in the region of Flanders, Belgium

Mobility presents a variety of opportunities as it allows users to access locations and services, and to meet people beyond their immediate surroundings. While the concept of mobility primarily focuses on the ease of moving, accessibility delineates the actual potential to participate in out-of-home activities. As a result, accessibility is a complex concept with a multitude of foci. This complexity is presented in the first section, which explains the general concept of accessibility, how it is defined and how it is related to the notion of transport-related exclusion. This section also gives an overview of the body of literature on the measures to determine area-based as well as personal accessibility levels and points out the important contrast between the simple, easy-to-interpret methods, adopted by policy makers and the complex methods preferred by experts. The second section clarifies how the dichotomous relationship between the urban and rural environment is reflected in transport policy that emphasizes on (especially car-based) mobility rather than on accessibility. Furthermore, the environmental and economic points of view are highlighted and the common policy strategies focused on sustainability are illustrated. Subsequently, the shortcomings in the way in which the contemporary debates concerning mobility, sustainability and the social implications of transport planning are conducted, are criticized. Finally, the last part of this section is dedicated to an extensive discussion on the ability of transport policies to, on the one hand, generate spatially as well as temporally uneven accessibility effects that give preference to certain population groups above others, and on the other hand, their ability to strive for a more equitable distribution of transport services amongst the population. The third section proposes two methodologies for measuring transport-related social exclusion implemented in a literature-based case study in Flanders. These studies comprise the following topics: measuring transport gaps by relating the social to the transport disadvantage and measuring modal disparities by comparing accessibility by private and public transport. The former investigates in which areas the provision of the public transport system is not tailored to specific public transport needs. The latter examines the disparity in access by private and public transport in order to highlight the car dependency. Both case studies incorporate the temporal variability in provision through the private and public transport network, as the time-of-day strongly influences accessibility levels

Performance Portability Through Semi-explicit Placement in Distributed Erlang

We consider the problem of adapting distributed Erlang applications to large or heterogeneous architectures to achieve good performance in a portable way. In many architectures, and especially large architectures, the communication latency between pairs of virtual machines (nodes) is no longer uniform. We propose two language-level methods that enable programs to automatically adapt to heterogeneity and non-uniform communication latencies, and both provide information enabling a program to identify an appropriate node when spawning a process. We provide a means of recording node attributes describing the hardware and software capabilities of nodes, and mechanisms that allow an application to examine the attributes of remote nodes. We provide an abstraction of communication distances that enables an application to select nodes to facilitate efficient communication. We have developed open source libraries that implement these ideas. We show that the use of attributes for node selection can lead to significant performance improvements if different components of the application have different processing requirements. We report a detailed empirical investigation of non-uniform communication times in several representative architectures, and show that our abstract model provides a good description of the hierarchy of communication times

Addressing fairness in SMT multicores with a progress-aware scheduler

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Current SMT (simultaneous multithreading) processors co-schedule jobs on the same core, thus sharing core resources like L1 caches. In SMT multicores, threads also compete among themselves for uncore resources like the LLC (last level cache) and DRAM modules. Per process performance degradation over isolated execution mainly depends on process resource requirements and the resource contention induced by co-runners. Consequently, the running processes progress at different pace. If schedulers are not progress aware, the unpredictable execution time caused by unfairness can introduce undesirable behaviors on the system such as difficulties to keep priority-based scheduling. This work proposes a job scheduler for SMT multicores that provides fairness to the execution of multiprogrammed workloads. To this end, the scheduler estimates per-process standalone performance by periodically creating low-contention co-schedules. These estimates are used to compute the per process progress. Then, those processes with less progress are prioritized to enhance fairness. Experimental results on a Intel Xeon with six dual-threaded SMT cores show that the proposed scheduler reduces unfairness, on average, by 3× over Linux OS. Moreover, thanks to the tread to core allocation policy, the scheduler slightly improves throughput and turnaround time.This work was supported by the Spanish Ministerio de Econom´ıa y Competitividad (MINECO) and Plan E funds, under Grant TIN2012-38341-C04-01, and by the Intel Early Career Faculty Honor Program AwardFeliu Pérez, J.; Sahuquillo Borrás, J.; Petit Martí, SV.; Duato Marín, JF. (2015). Addressing fairness in SMT multicores with a progress-aware scheduler. IEEE. https://doi.org/10.1109/IPDPS.2015.48