检索结果-内蒙古大学图书馆

IEEE international Symposium on parallel and distributed Processing workshops and PhD Forum

作者： Can Hankendi Ayse K. Coskun Electrical and Computer Engineering Department Boston University Boston MA 02215

ISBN: (纸本)9781479913725

As today's computing trends are moving towards the cloud, meeting the increasing computational demand while minimizing the energy costs in data centers has become essential. This work introduces two adaptive techniques to reduce the energy consumption of the computing clusters through power and resource management on multi-core processors. We first present a novel power capping technique to constrain the power consumption of computing nodes. Our technique combines Dynamic Voltage-Frequency Scaling (DVFS) and thread allocation on multi-core systems. By utilizing machine learning techniques, our power capping method is able to meet the power budgets 82% of the time without requiring any power measurement device and reduces the energy consumption by 51.6% on average in comparison to the state-of-the-art techniques. We then introduce an autonomous resource management technique for consolidated multi-threaded workloads running on multi-core servers. Our technique first classifies applications according to their energy efficiency measure, then proportionally allocates resources for co-scheduled applications to improve the energy efficiency. The proposed technique improves the energy efficiency by 17% in comparison to state-of-the-art co-scheduling policies.

关键词： increasing computational demand energy efficiency state-of-the-art techniques

来源：评论

学校读者我要写书评

暂无评论

Modelling multiplicity in choreography models

Modelling multiplicity in choreography models

引用

Model-Driven Engineering workshop (MoDRE)

作者： Urooj Fatima Rolv Bræk Department of Telematics Norwegian University of Science and Technology Trondheim Norway

distributed reactive systems provide services where active concurrent components collaborate, may take independent initiatives and interact with each other and their environment. The modelling of such systems is complex. In this paper, we continue previous research where an approach is proposed to model distributed reactive systems. This approach enables us to define precise and complete global behaviour of reactive services through flow-global choreographies. These flow-global choreographies are mapped to flow-localized choreographies and further to distributed component designs in a systematic way. The complete and precise choreographies help service engineers to concentrate on choreographies only and to identify problems early at requirements specification. The proposed approach has the potential to become highly automated. While defining global behaviour, one normally focuses on just one instance of each role in a service to simplify the model. In some cases however, it is important to consider multiplicity issues early while defining requirements. The question then is when and how to deal with multiplicity of role instances and service sessions? Solutions to this problem in different contexts are proposed and discussed in this paper.

关键词： Collaboration Unified modeling language resource management Dynamic scheduling Joining processes Routing Interrupters

来源：评论

学校读者我要写书评

暂无评论

Handling Uncertainty: Pareto-Efficient BoT scheduling on Hybrid Clouds

Handling Uncertainty: Pareto-Efficient BoT Scheduling on Hyb...

引用

international Conference on parallel Processing (ICPP)

作者： M. Reza Hoseinyfarahabady Hamid R.D. Samani Luke M. Leslie Young Choon Lee Albert Y. Zomaya Centre for Distributed and High Performance Computing The University of Sydney NSW Australia

Coping with uncertainty is a challenging and complex problem particularly in hybrid cloud environments-private cloud plus public cloud. Conflicting goals of minimizing the cost and performance, unknown prior knowledge about task running times, and a lack of estimation tools are just a few of the challenges that resource management systems in those environments encounter. The aim in this paper is to find Pareto-optimal schedules for large-scale Bag-of-Tasks (BoT) applications that meet user defined constraints, such as deadline or budget or some tradeoff between them. BoT applications are common in science and engineering and consist of many independent tasks. To achieve the user's chosen Pareto-optimal schedule, we develop a dynamic resource allocation process for hybrid clouds. We also present a hybrid approach to estimating task running times that incorporates several estimators with a feedback control system to cope with the inherent uncertainty in such estimation. Through extensive experiments on a test bed hybrid cloud, using Amazon EC2 as a public cloud, we show that the proposed approach can achieve near optimality with little overhead, and consistently achieves a solution within 2% of the user's chosen Pareto-optimal schedule. Further, we demonstrate that our approach performs better than an extended List scheduling approach by reducing both the total cost and time needed to run the application by almost 20% and 5% on average, respectively.

关键词： Estimation Cloud computing resource management Schedules Approximation algorithms Uncertainty scheduling

来源：评论

学校读者我要写书评

暂无评论

scheduling Workflows in Multi-cluster Environments

Scheduling Workflows in Multi-cluster Environments

引用

international Conference on Advanced Information Networking and Applications workshops (AINAW)

作者： Silvio Luiz Stanzani Líria Matsumoto Sato Marco A.S. Netto Computer and Digital Systems Engineering (PCS) Polytechnic School University of São Paulo Sao Paulo Brazil IBM Research Sao Paulo Brazil

ISBN: (纸本)9781467362399

Scientific applications modeled as workflows can exhibit both task and data parallelism. scheduling these workflows in a multi-cluster environment is challenging due to the large number of task mapping possibilities. Therefore, several heuristics have been proposed over the last years to address such a problem. A key limitation of existing heuristics for multi-cluster environments is that individual tasks are mapped onto single resources, which limits the resource options to reduce the time to the complete workflow executions. This paper introduces the Multi-Cluster Allocation-Heterogeneous Earliest Finish Time (MCA-HEFT) heuristic, which deploys single parallel tasks of a workflow into multiple clusters and schedules them accordingly. We evaluated MCA-HEFT against the Mixed-parallel Heterogeneous Earliest Finish Time (M-HEFT) heuristic, which is one of the most well-known workflow scheduling heuristics in literature. MCA-HEFT was able to produce make spans that were up to 42% shorter than those produced by M-HEFT, having only approximately 10% of tasks distributed on multiple clusters. Our experiments considered several metrics and parameters including critical path size, make span, number of clusters used to execute tasks, and the network impact when deploying the tasks in multiple clusters.

关键词： resource management Processor scheduling Mathematical model Equations scheduling Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Dataflow language compilation for a single chip massively parallel processor

Dataflow language compilation for a single chip massively pa...

引用

IEEE international workshop on Multi-/Many-core Computing systems (MuCoCoS)

作者： Benoit Dupont de Dinechin Kalray France

Summary form only given. The Kalray MPPA-256 processor (Multi-Purpose Processing Array) integrates 256 processing engine (PE) cores and 32 resource management (RM) cores on a single 28nm CMOS chip. These cores are distributed across 16 compute clusters and 4 I/O subsystems. On-chip communications and synchronizations are supported by an explicitly addressed dual network-on-chip (NoC), with one node per compute cluster and 4 nodes per 4 I/O subsystem. The Kalray MPPA software development kit includes a complete programming environment for a C-based dataflow language, whose compiler fully automates the distributed execution of tasks across the processing, memory, communication and synchronization resources of the MPPA architecture. We first introduce the model of computation of the Kalray dataflow language, which is based on cyclostatic dataflow with extensions such as the firing thresholds of Karp & Miller computation graphs. We then describe the main steps of dataflow compilation to a distributed execution platform. These include: task sequencing, communication buffer sizing, task clustering, DMA engine exploitation, place & route, NoC bandwidth allocation, and generation of run-time tables. Finally, we discuss the suitability and restrictions of this and related static dataflow models of computations with regards to the dynamic and real-time requirements of embedded applications targeted by the MPPA processor.

关键词：

来源：评论

学校读者我要写书评

暂无评论

resource-Aware Scaling of Multi-threaded Java Applications in Multi-tenancy Scenarios

Resource-Aware Scaling of Multi-threaded Java Applications i...

引用

IEEE international Conference on Cloud Computing Technology and Science (CloudCom)

作者： José Simão Navaneeth Rameshan Luís Veiga INESC-ID Lisboa Instituto Superior de Engenharia de Lisboa (ISEL) Universitat Politècnica de Catalunya INESC-ID Lisboa Instituto Superior Técnico

Cloud platforms are becoming more prevalent in every computational domain, particularly in e-Science. A typical scientific workload will have a long execution time or be data intensive. Providing an execution environment for these applications, which belong to different tenants, has to deal with the horizontal scaling of execution flows (i.e. threads) and an effective allocation of resources that takes into account the effective progress made by each tenant. While this is trivial for Bag-of-Tasks and embarrassingly parallel jobs, it is hard for HPC single-process multi-threaded applications because they cannot be scaled up automatically just by adding more virtual machines to execute the workload. In this paper we present MengTian, a distributed execution environment or platform capable of addressing the issues above. It encompasses several extensions to the Java execution environment, ranging from middleware to the virtual machine code and libraries. Our Java-based platform provides a Single System Image abstraction supported by a Partially Global Address Space to transparently spawn threads across a cluster of machines. It monitors progress with different levels-of-detail and accounts and restricts resource consumption. The overall goal is to redistribute resources among different JVM instances, increasing the unitary outcome of the progress vs. resource usage ratio over time.

关键词： Instruction sets Message systems Middleware Monitoring Java Processor scheduling resource management

来源：评论

学校读者我要写书评

暂无评论

scheduling of frequently communicating tasks

引用

international JOURNAL OF COMMUNICATION systems 2012年第2期25卷 146-157页

作者： Papazachos, Zafeirios C. Karatza, Helen D. Aristotle Univ Thessaloniki Dept Informat Thessaloniki 54124 Greece

Gang scheduling is an efficient resource management scheme for distributed systems which combines elements of time sharing and space sharing. It is a suitable technique particularly in the case when parallel tasks have to be running concurrently to make progress in communication. This paper studies the impact on scheduling performance when dynamically generated sequential gangs exist in the workload. In the case of sequential gangs, a subsequent gang can be dynamically generated after the execution of the initial gang based on affinity information which resides on the caches of the previously seized processors. The performance of different gang-scheduling algorithms is examined for various cases of workload compositions which range from cases with a low demand for dynamically generated gangs to cases with a high ratio of sequential gangs to solitary gangs. A simulation model is implemented to address associated performance issues. Copyright (C) 2011 John Wiley & Sons, Ltd.

关键词： distributed systems communication-aware policies performance modeling simulation

来源：评论

学校读者我要写书评

暂无评论

A Combined Dual-stage Framework for Robust scheduling of Scientific Applications in Heterogeneous Environments with Uncertain Availability

A Combined Dual-stage Framework for Robust Scheduling of Sci...

引用

26th IEEE international parallel and distributed Processing Symposium (IPDPS) / workshop on High Performance Data Intensive Computing

作者： Ciorba, Florina M. Hansen, Timothy Srivastava, Srishti Banicescu, Ioana Maciejewski, Anthony A. Siegel, Howard Jay Tech Univ Dresden Ctr Informat Serv & High Performance Comp D-01062 Dresden Germany Mississippi State Univ Dept Comp Engn & Sci Starkville MS USA Colorado State Univ Dept Elect & Comp Engn Ft Collins CO 80523 USA

ISBN: (纸本)9780769546766

scheduling parallel applications on existing or emerging computing platforms is challenging, and, among other attributes, must be efficient and robust. A dual-stage framework is proposed in this paper to evaluate the robustness of efficient resource allocation and dynamic load balancing of scientific applications in heterogeneous computing environments with uncertain availability. The first stage employs robust resource allocation heuristics, while the second stage incorporates robust dynamic loop scheduling techniques. The combined dual-stage framework constitutes a comprehensive framework that enables and provides guarantees for the robust execution of scientific applications in computing systems where uncertainty is caused by various unpredictable perturbations. The paper reports on studies for determining the best techniques to be used for each stage that: (a) maximize the probability that the system makespan satisfies a deadline, and (b) minimize the system makespan for every given availability level in the system. The usefulness and benefits of the proposed framework are demonstrated via a small scale example.

关键词： high performance heterogeneous systems non-dedicated systems resource allocation dynamic loop scheduling robustness uncertainties

来源：评论

学校读者我要写书评

暂无评论

Task scheduling in Large-scale distributed systems Utilizing Partial Reconfigurable Processing Elements

Task Scheduling in Large-scale Distributed Systems Utilizing...

引用

26th IEEE international parallel and distributed Processing Symposium (IPDPS) / workshop on High Performance Data Intensive Computing

作者： Nadeem, M. Faisal Ashraf, Imran Ostadzadeh, S. Arash Wong, Stephan Bertels, Koen Delft Univ Technol Fac Elect Engn Math & Comp Sci Comp Engn Lab NL-2600 AA Delft Netherlands

ISBN: (纸本)9780769546766

Recent progress in processing speeds, network bandwidths, and middleware technologies have contributed towards novel computing platforms, ranging from large-scale computing clusters to globally distributed systems. Consequently, most current computing systems possess different types of heterogeneous processing resources. Entering into the peta-scale computing era and beyond, reconfigurable processing elements such as Field Programmable Gate Arrays (FPGAs), as well as forthcoming integrated hybrid computing cores, will play a leading role in the design of future distributed systems. Therefore, it is important to develop simulation tools to measure the performance of reconfigurable processors in the current and future distributed systems. In this paper, we propose the design of a simulation framework to investigate the performance of reconfigurable processors in distributed systems. The framework incorporates the partial reconfigurable functionality to the reconfigurable nodes. Depending on the available reconfigurable area, each node is able to execute more than one task simultaneously. Furthermore as a case study, we present a simple task scheduling algorithm to verify the functionality of the simulation framework. The proposed algorithm supports the scheduling of tasks on partially reconfigurable nodes. The simulation results are based on various experiments and they provide a comparison between full (one node-one task mapping) and partial (one node-multiple tasks mapping) configuration of the nodes, for the same set of parameters in each simulation run. Results suggest that the average wasted area per task is less as compared to the full configuration, verifying the functionality of the simulation framework.

关键词： Simulation framework distributed systems Partial reconfiguration Reconfigurable resources resource management

来源：评论

学校读者我要写书评

暂无评论

A distributed Fine-Grained Flow Control Sytem for Scalable Aircraft Spares management and Optimization in Clouds

A Distributed Fine-Grained Flow Control Sytem for Scalable A...

引用

IEEE 18th international Conference on parallel and distributed systems (ICPADS)

作者： Aye, Theint Theint Ta Nguyen Binh Duong Li, Xiaorong Li, Elaine Wong Kay A STAR Inst High Performance Comp 1 Fusionopolis Way Singapore 138632 Singapore EADS Innovat Works Singapore 797562 Singapore

ISBN: (纸本)9781467345651;9780769549033

In this paper, we presented the design, implementation, and evaluation of a distributed system to manage the parallelized analytics for Aircraft Spare parts management and Optimizations (SMO), which is a well-known problem in logistics industry. Our proposed solution is able to solve the resource-intensive SMO problem using distributed computing infrastructures (e. g., private or public clouds) in a scalable manner. We designed and fine-tuned a parallel meta-heuristics based on a fine-grained flow control workflow model which enables flow controls of running parallel meta-heuristics in multiple processors and achieved significant performance gains. Together with priority based scheduling, the proposed system effectively dispatches submitted SMO jobs over the set of distributed resources to accommodate different classes of users. Extensive experimental studies were conducted to analyze the performance of parallelized SMO job executions in term of execution time, computation and data transmission time, waiting time, memory usage, etc. Insightful lessons have been drawn from the obtained results;and potential areas for further improvements have also been identified.

关键词： Cloud computing parallel meta-heuristics distributed systems workflow control job scheduling

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：