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Dynamic fractional resource scheduling for HPC workloads

Dynamic fractional resource scheduling for HPC workloads

引用

international Symposium on parallel and distributed Processing (IPDPS)

作者： Mark Stillwell Frederic Vivien Henri Casanova Department of Information and Computer Sciences University of Hawai Honolulu USA INRIA France

We propose a novel job scheduling approach for homogeneous cluster computing platforms. Its key feature is the use of virtual machine technology for sharing resources in a precise and controlled manner. We justify our approach and propose several job scheduling algorithms. We present results obtained in simulations for synthetic and real-world High Performance Computing (HPC) workloads, in which we compare our proposed algorithms with standard batch scheduling algorithms. We find that our approach widely outperforms batch scheduling. We also identify a few promising algorithms that perform well across most experimental scenarios. Our results demonstrate that virtualization technology coupled with lightweight scheduling strategies affords dramatic improvements in performance for HPC workloads.

关键词： Dynamic scheduling Processor scheduling resource management scheduling algorithm Virtual machining High performance computing Time sharing computer systems Computational modeling Clustering algorithms Optical coupling

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A Grid simulation framework to study advance scheduling strategies for complex workflow applications

A Grid simulation framework to study advance scheduling stra...

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IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Adan Hirales-Carbajal Andrei Tchernykh Thomas Röblitz Ramin Yahyapour Computer Science Department CICESE Ensenada Baja California Mexico IT und Medien Centrum & Fakultät für Informatik Technische Universität Dortmund Dortmund Germany

ISBN: (纸本)9781424465330

Workflow scheduling in Grids becomes an important area as it allows users to process large scale problems in an atomic way. However, validating the performance of workflow scheduling strategies in real production environment cannot be feasibly carried out. The complexity of production systems, dynamicity of Grid execution environments, and the difficulty to reproduce experiments, make workflow scheduling production systems a complex research environment. Instead, this work is based on a trace driven simulator. This work presents workflow scheduling support as an extension to the Teikoku Grid scheduling Framework (tGSF). tGSF was developed as a response for a standard compliant and trace based Grid scheduling simulation environment. Workflow scheduling is provided via a second layer of Grid scheduler, extensible to new workflow and parallel scheduling strategies. This work also includes a usage case scenario, which illustrates how this extension can be used for quantitative experimental study.

关键词： Processor scheduling Computational modeling Production systems resource management Standards development Grid computing Computer simulation Application software Computer science resource virtualization

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Scalable Hierarchical scheduling for Multiprocessor systems Using Adaptive Feedback-Driven Policies

Scalable Hierarchical Scheduling for Multiprocessor Systems ...

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international Symposium on parallel and distributed Processing with Applications, ISPA

作者： Yangjie Cao Hongyang Sun Depei Qian Weiguo Wu Department of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China Department of Computer Engineering Nanyang Technological University Singapore

This work addresses the problem of allocating resource-intensive parallel jobs on multicore- and multiprocessor-based systems, where the performance gains largely depend on effectively exploiting application parallelization across the available parallel computing resources. The objective is to find efficient allocation approaches that minimize the parallel jobs' completion time, i.e. makespan. Integrating feedback-driven adaptive strategies, we present a general hierarchical scheduling framework and show that two hierarchical scheduling algorithms: ABG-DS and AG-DS achieve scalable performance in term of makespan regardless of the number of hierarchical levels. Specifically, we prove that both ABG-DS and AG-DS have O(1)-competitive ratio for batched parallel jobs. Extending an existing tool, called Malleable-Lab, we evaluate the performance and scalability of our proposed algorithms and compare with that of well-known EQUI-based strategies. The simulation results demonstrate that both ABG-DS and AG-DS generally outperforms EQUI-EQUI for a wide range of parallel workloads. Moreover, feedback-driven adaptive scheduling algorithms show better scalability when the number of levels increases in the scheduling hierarchy.

关键词： Program processors scheduling scheduling algorithm Scalability resource management

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Decomposition Based Algorithm for State Prediction in Large Scale distributed systems

Decomposition Based Algorithm for State Prediction in Large ...

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international Symposium on parallel and distributed Computing

作者： Mihai Istin Andreea Vişan Florin Pop Valentin Cristea Faculty of Automatic Control and Computers University “Politehnica” of Bucharest Romania

Prediction represents an important component of resource management, providing information about the future state, utilization and availability of resources. We propose a new prediction algorithm inspired from the decomposition of a complex wave into simpler waves with fixed frequencies (similar to Fourier decomposition). The partial results obtained from this decomposition stage are combined using approaches inspired from artificial intelligence models. The experimental results for different system parameters, used in Alice experiment, highlight the great improvement, discussed in terms of error reduction, offered by this new prediction algorithm. The tests were made using real-time monitoring data provided by a system monitoring tool, in the case of one-step and multi-step ahead prediction. The prediction's results can be used by the resource management systems in order to improve the scheduling decisions, assuring the load balancing and optimizing the resource utilization.

关键词： Prediction algorithms Large-scale systems resource management Monitoring Availability Frequency Artificial intelligence System testing Real time systems Load management

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ADREA: A Framework for Adaptive resource Allocation in distributed Computing systems

ADREA: A Framework for Adaptive Resource Allocation in Distr...

引用

IEEE international Conference on parallel and distributed Computing, Applications and Technologies (PDCAT)

作者： Masnida Hussin Young Choon Lee Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Information Technologies University of Sydney Sydney NSW Australia

Large-scale distributed computing systems (LDCSs) can be best characterized by their dynamic nature particularly in terms of availability and performance. Typically, these systems deal with various types of jobs in many aspects, such as resource requirements, quality of service (QoS) and other temporal constraints. These diverse characteristics in both resources and jobs impose a great burden on scheduling and resource allocation. That is, inefficient resource allocation brings about poor resource utilization issues and often unreliable job execution. We present the Adaptive Reliable Allocation (ADREA) scheme, which attempts to ensure reliable job execution effectively exploiting heterogeneity in both resources and jobs using a novel clustering technique and a dynamic job migration policy. Specifically, ADREA intends to pave the way in producing better performance (e.g., response time, resource utilization) with reliable computation. Extensive simulations with varying processing capacities and different job arrival rates have been carried out to evaluate our scheme. The results demonstrate that the proposed scheme provides better performance over other algorithms as it significantly improves both job completion time and resource utilization.

关键词： resource management Dynamic scheduling Availability Heuristic algorithms Time factors Computational modeling

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A scheduling framework for large-scale, parallel, and topology-aware applications

A scheduling framework for large-scale, parallel, and topolo...

引用

international Symposium on parallel and distributed Processing (IPDPS)

作者： Valentin Kravtsov Pavel Bar David Carmeli Assaf Schuster Martin Swain Computer Science Department Technion-Israel Institute of Technology Haifa Israel Systems Biology Research Group University of Ulster Coleraine UK

scheduling of large-scale, distributed topology-aware applications requires that not only the properties of the requested machines be considered, but also the properties of the machines' interconnections. This requirement severely complicates the scheduling process, as even a matching between a single multi-processors task and available machines in a single time slot becomes an NP-complete problem with no polynomial approximation. In this paper we propose a complete scheduling framework for multi-cluster, heterogeneous environments that provides, in practice, an efficient solution for the scheduling of topology-aware applications. The proposed framework is very flexible as it is composed of pluggable components and can be easily configured to support a variety of scheduling policies. W e also describe three novel scheduling and coallocation algorithms that were developed and plugged into the framework. The proposed scheduling framework was integrated into the QosCosGrid system, where it is used as the main decision-making module.

关键词： Large-scale systems Network topology Application software Grid computing resource management Processor scheduling Computer science systems biology Cities and towns NP-complete problem

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workshop on systems management techniques processes and services

Workshop on systems management techniques processes and serv...

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IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

In our sixth year of SMTPS, we would like to invite the pioneers in computing resource management and discuss the latest ideas, with a special focus on “cloud computing.” With advent of virtualization technologies, efficient and effective systems management plays an even more critical role to deal with the ever-increasing computing resources and their connectivity and complexity. The cloud computing paradigm has been introduced to better respond to dynamic computation demand by emerging applications and workload, and to better utilize computing resources and energy in aggregation to serve a large group of users.

关键词： Meteorology

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GridP2P: resource Usage in Grids and Peer-to-Peer systems

GridP2P: Resource Usage in Grids and Peer-to-Peer Systems

引用

IEEE international Symposium on parallel and distributed Processing

作者： Sergio Esteves Luis Veiga Paulo Ferreira INESC-ID/IST Distributed Systems Group

ISBN: (纸本)9781424465330

The last few years have witnessed huge growth in computer technology and available resources throughout the Internet. These resources can be used to run CPU-intensive applications requiring long periods of processing time. Grid systems allow us to take advantage of available resources lying over a network. However, these systems impose several difficulties to their usage (e.g. heavy authentication and configuration management);in order to overcome them, Peer-to-Peer systems provide open access making the Grid available to any user. Our solution consists of a platform for distributed cycle sharing which attempts to combine Grid and Peer-to-Peer models. A major goal is to allow any ordinary user to use remote idle cycles in order to speedup commodity applications. Oh the other hand, users can also provide spare cycles of their machines when they are not using them. Our solution encompasses the following functionalities: application management, job creation and scheduling, resource discovery, security policies, and overlay network management. The simple and modular organization of this system allows that components can be changed at minimum cost. In addition, the use of history-based policies provides powerful usage semantics concerning the resource management.

关键词： peer to peer Grates grids configuration management management of resources modular organization Computer technology Solutions Grid

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AuctionNet: Market oriented task scheduling in heterogeneous distributed environments

AuctionNet: Market oriented task scheduling in heterogeneous...

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IEEE international Symposium on parallel and distributed Processing workshops and Phd Forum (IPDPSW)

作者： Han Zhao Xiaolin Li Department of Computer Science Scalable Software Systems Laboratory Oklahoma State University Stillwater OK USA

ISBN: (纸本)9781424465330

We propose a suite of market-oriented task scheduling algorithms to build an AuctionNet for heterogeneous distributed environments. In heterogeneous distributed environments, computing nodes are autonomous and owned by different organizations, for example peer-to-peer systems, desktop grids/clouds. To address such diverse heterogeneity and dynamism in systems, applications, and local policies, efficient and fair task scheduling becomes a challenging issue. To cope with such complexity in a distributed and noncooperative environment, we propose to use market-oriented incentive mechanisms to regulate task scheduling in a distributed manner. Further, to accommodate multiple objectives and criteria, we adopt a combined approach leveraging the advantage of both hypergraph theory and incentive mechanisms. We first formulate a general framework of market-oriented task scheduling in distributed systems. We then present two algorithms for task-bundle scheduling. Preliminary results demonstrate the satisfactory performance of our proposed algorithms. The remaining work to complete the PhD dissertation is then presented. The proposed research carries significant intellectual merits and potential broader impacts in the following aspects. (1) We propose the notion of task-bundle for the first time in the literature. Product-bundle has been a common marketing strategy in our daily life for a long time. In the emerging commercial clouds and desktop clouds, task-bundle could be a useful concept for computing and storage markets. (2) We propose efficient distributed mechanisms that are very suitable for such distributed systems. A novel algorithm combining hypergraph and incentive mechanisms achieves multi-objective optimization. (3) We conduct rigorous analytical study and prove that our algorithms ensure efficiency and fairness and in the meantime maximize social welfare. (4) Overall, this proposal lays a solid foundation and sheds light on future research and realworld applicatio

关键词： Processor scheduling distributed computing Job shop scheduling scheduling algorithm Cloud computing Environmental economics Peer to peer computing Proposals resource management Grid computing

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Utility Accrual Object Distribution in Real-Time systems

Utility Accrual Object Distribution in Real-Time Systems

引用

international Conference on parallel and distributed systems (ICPADS)

作者： Morteza Mohaqeqi Mehdi Kargahi School of Electrical and Computer Engineering University College of Engineering University of Tehran Iran

This paper considers object-based distributed real-time systems within which objects provide system services to the real-time tasks. Each task is subject to a time/utility function (TUF) which determines the accrued utility of the task according to its completion time. One major problem in such systems is to place the objects onto the computing nodes so as to maximize the total accrued utility. Thus, we propose a utility accrual object distribution (UAOD) algorithm which consists of two phases. In the first phase, through object placement and replication beside some types of deadline decomposition and adaptation, the computing nodes are reserved for the most beneficial tasks. As the second phase, UAOD follows a load-balancing algorithm for the placement of the remaining objects on the nodes to service the less beneficial tasks. Simulation results reveal that the total accrued utility is improved with the UAOD algorithm comparing to the traditional object placement methods.

关键词： Real time systems Time factors Program processors resource management Processor scheduling Load management Educational institutions

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