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Symmetric Mapping: An architectural pattern for resource supply in grids and clouds

Symmetric Mapping: An architectural pattern for resource sup...

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international Symposium on parallel and distributed Processing (IPDPS)

作者： Xavier Grehant Isabelle Demeure CNRS LTCI and CERN openlab Institut Telecom-Telecom ParisTech LTCI France CNRS LTCI Institut Telecom-Telecom ParisTech LTCI France

This paper presents the symmetric mapping pattern, an architectural pattern for the design of resource supply systems. The focus of symmetric mapping is on separation of concerns for cost-effective resource allocation. It divides resource supply in three functions: (1) Users and providers match and engage in resource supply agreements, (2) users place tasks on subscribed resource containers, and (3) providers place supplied resource containers on physical resources. The pattern relies on stakeholders to act for their own interest. The efficiency of the whole system is determined by the degree of freedom left to the three functions and the efficiency of the associated decision systems. We propose a formalism of the symmetric mapping pattern, we observe to what extend existing grid and cloud systems follow it, and we propose elements of an original implementation.

关键词： Clouds resource management Contracts Telecommunications Containers Control systems Processor scheduling Software maintenance Throughput Subscriptions

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Multi-users scheduling in parallel systems

Multi-users scheduling in parallel systems

引用

international Symposium on parallel and distributed Processing (IPDPS)

作者： Erik Saule Denis Trystram LIG Grenoble University Montbonnot Saint Martin France

ISBN: (纸本)9781424437511

We are interested in this paper to study scheduling problems in systems where many users compete to perform their respective jobs on shared parallel resources. Each user has specific needs or wishes for computing his/her jobs expressed as a function to optimize (among maximum completion time, sum of completion times and sum of weighted completion times). Such problems have been mainly studied through game theory. In this work, we focus on solving the problem by optimizing simultaneously each user's objective function independently using classical combinatorial optimization techniques. Some results have already been proposed for two users on a single computing resource. However, no generic combinatorial method is known for many objectives. The analysis proposed in this paper concerns an arbitrarily fixed number of users and is not restricted to a single resource. We first derive inapproximability bounds; then we analyze several greedy heuristics whose approximation ratios are close to these bounds. However, they remain high since they are linear in the number of users. We provide a deeper analysis which shows that a slightly modified version of the algorithm is a constant approximation of a Pareto-optimal solution.

关键词： Processor scheduling Game theory Algorithm design and analysis Approximation algorithms Clustering algorithms scheduling algorithm High performance computing Pareto analysis resource management Queueing analysis

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The Owner Share Scheduler for a distributed System

The Owner Share Scheduler for a Distributed System

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international Conference on parallel Processing workshops (ICPPW)

作者： José Nelson Falavinha Junior Aleardo Manacero Junior Miron Livny Daniel Bradley Department of Electrical Engineering São Paulo State University - UNESP Ilha Solteira São Paulo Brazil Department of Computer Science São Paulo State University - UNESP São José do Rio Preto São Paulo Brazil Department of Computer Science University of Wisconsin Madison Wisconsin USA

In large distributed systems, where shared resources are owned by distinct entities, there is a need to reflect resource ownership in resource allocation. An appropriate resource management system should guarantee that resource's owners have access to a share of resources proportional to the share they provide. In order to achieve that some policies can be used for revoking access to resources currently used by other users. In this paper, a scheduling policy based in the concept of distributed ownership is introduced called Owner Share Enforcement Policy (OSEP). OSEP goal is to guarantee that owner do not have their jobs postponed for longer periods of time. We evaluate the results achieved with the application of this policy using metrics that describe policy violation, loss of capacity, policy cost and user satisfaction in environments with and without job checkpointing. We also evaluate and compare the OSEP policy with the Fair-Share policy, and from these results it is possible to capture the trade-offs from different ways to achieve fairness based on the user satisfaction.

关键词： resource management Processor scheduling Checkpointing Computer science Costs Hardware parallel processing Measurement Helium scheduling algorithm

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Using a market economy to provision compute resources across planet-wide clusters

Using a market economy to provision compute resources across...

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international Symposium on parallel and distributed Processing (IPDPS)

作者： Murray Stokely Jim Winget Ed Keyes Carrie Grimes Benjamin Yolken Google Inc. Mountain View CA USA Department of Management Science and Engineering University of Stanford Stanford CA USA

We present a practical, market-based solution to the resource provisioning problem in a set of heterogeneous resource clusters. We focus on provisioning rather than immediate scheduling decisions to allow users to change long-term job specifications based on market feedback. Users enter bids to purchase quotas, or bundles of resources for long-term use. These requests are mapped into a simulated clock auction which determines uniform, fair resource prices that balance supply and demand. The reserve prices for resources sold by the operator in this auction are set based on current utilization, thus guiding the users as they set their bids towards under-utilized resources. By running these auctions at regular time intervals, prices fluctuate like those in a real-world economy and provide motivation for users to engineer systems that can best take advantage of available resources. These ideas were implemented in an experimental resource market at Google. Our preliminary results demonstrate an efficient transition of users from more congested resource pools to less congested resources. The disparate engineering costs for users to reconfigure their jobs to run on less expensive resource pools was evidenced by the large price premiums some users were willing to pay for more expensive resources. The final resource allocations illustrated how this framework can lead to significant, beneficial changes in user behavior, reducing the excessive shortages and surpluses of more traditional allocation methods.

关键词： resource management Supply and demand scheduling algorithm Engineering management Job specification Feedback Clocks systems engineering and theory Costs distributed computing

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Monitoring of Complex Applications Execution in distributed Dependable systems

Monitoring of Complex Applications Execution in Distributed ...

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international Symposium on parallel and distributed Computing

作者： Florin Pop Alexandru Costan Ciprian Dobre Corina Stratan Valentin Cristea Faculty of Automatic Control and Computer Science Polytechnic University of Bucharest Romania

ISBN: (纸本)9781424444106

The execution of applications in dependable system requires a high level of instrumentation for automatic control. We present in this paper a monitoring solution for complex application execution. The monitoring solution is dynamic, offering real-time information about systems and applications. The complex applications are described using workflows. We show that the management process for application execution is improved using monitoring information. The environment is represented by distributed dependable systems that offer a flexible support for complex application execution. Our experimental results highlight the performance of the proposed monitoring tool, the MonALISA framework.

关键词： Application software Computerized monitoring resource management distributed computing Automatic control Instruments scheduling Performance analysis Fault detection Availability

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Core-aware memory access scheduling schemes

Core-aware memory access scheduling schemes

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international Symposium on parallel and distributed Processing (IPDPS)

作者： Zhibin Fang Xian-He Sun Yong Chen Surendra Byna Department of Computer Science Illinois Institute of Technology Chicago IL USA

ISBN: (纸本)9781424437511

Multi-core processors have changed the conventional hardware structure and require a rethinking of system scheduling and resource management to utilize them efficiently. However, current multi-core systems are still using conventional single-core memory scheduling. In this study, we investigate and evaluate traditional memory access scheduling techniques, and propose a core-aware memory scheduling for multi-core environments. Since memory requests from the same source exhibit better locality, it is reasonable to schedule the requests by taking the source of the requests into consideration. Motivated from this principle of locality, we propose two core-aware policies based on traditional bank-first and row-first schemes. Simulation results show that the core-aware policies can effectively improve the performance. Compared with the bank-first and row-first policies, the proposed core-aware policies reduce the execution time of certain NAS parallel benchmarks by up to 20% in running the benchmarks separately, and by 11% in running them concurrently.

关键词： Processor scheduling Multicore processing Control systems Sun parallel processing Delay Hardware Yarn Computer science Concurrent computing

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A distributed heuristic for decentralized workflow scheduling in global Grids

A distributed heuristic for decentralized workflow schedulin...

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international workshop on Grid Computing

作者： Mustafizur Rahman Rajiv Ranjan Rajkumar Buyya Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia Service Oriented Computing Research Group School of Computer Science and Engineering University of New South Wales Australia

Efficient scheduling is a key concern for the effectual execution of performance driven Grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized Grid environment. However, in this paper, we present a distributed list heuristic for decentralized scheduling of workflow applications in global Grids. The simulation results show that the proposed scheduling approach is scalable with respect to increased workload on the system.

关键词： Processor scheduling Grid computing resource management Computer science scheduling algorithm Laboratories Software engineering distributed computing Application software Peer to peer computing

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Market-Based Load Balancing for distributed Heterogeneous Multi-resource Servers

Market-Based Load Balancing for Distributed Heterogeneous Mu...

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international Conference on parallel and distributed systems (ICPADS)

作者： Chih-Chiang Yang Kun-Ting Chen Chien Chen Jing-Ying Chen Department of Computer Science National Chiao Tung University Hsinchu Taiwan

To cope with rapidly increasing Internet usage nowadays, providing Internet services using multiple servers has become a necessity. To ensure sufficient service quality and server utilization at the same time, effective methods are needed to spread load among servers properly. Existing load balancing methods often assume servers are homogeneous and consider only one type of resource, such as CPU. Such methods suffer from the fact that different requests often demand multiple types of resources with different requirements; trying to balance the usage of only one resource type may induce an inadvertent performance bottleneck, leading to low resource utilization and service quality. To address this problem, we propose a load balancing method based on the concept of distributed market mechanism, where requests are priced with respect to the load of multiple resources on each server. By migrating jobs among servers to balance inter-server load and minimize intra-server job cost at the same time, our method shows significant improvement in terms of load imbalance degrees, server utilization, and response time when compared to other published methods, especially when server heterogeneity increases.

关键词： Load management Web server Costs Network servers Web and internet services Computer science resource management Delay scheduling Hardware

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RDMS: A hardware task scheduling algorithm for Reconfigurable Computing

RDMS: A hardware task scheduling algorithm for Reconfigurabl...

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international Symposium on parallel and distributed Processing (IPDPS)

作者： Miaoqing Huang Harald Simmler Olivier Serres Tarek El-Ghazawi NSF Center for High-Performance Reconfigurable Computing (CHREC) Department of Electrical and Computer Engineering George Washington University USA

Reconfigurable computers (RC) can provide significant performance improvement for domain applications. However, wide acceptance of today's RCs among domain scientist is hindered by the complexity of design tools and the required hardware design experience. Recent developments in HW/SW co-design methodologies for these systems provide the ease of use, but they are not comparable in performance to manual co-design. This paper aims at improving the overall performance of hardware tasks assigned to FPGA devices by minimizing both the communication overhead and configuration overhead, which are introduced by using FPGA devices. The proposed reduced data movement scheduling (RDMS) algorithm takes data dependency among tasks, hardware task resource utilization, and inter-task communication into account during the scheduling process and adopts a dynamic programming approach to reduce the communication between muP and FPGA co-processor and the number of FPGA configurations to a minimum. Compared to two other approaches that consider data dependency and hardware resource utilization only, RDMS algorithm can reduce inter-configuration communication time by 11% and 44% respectively based on simulation using randomly generated data flow graphs. The implementation of RDMS on a real-life application, N-body simulation, verifies the efficiency of RDMS algorithm against other approaches.

关键词： Hardware scheduling algorithm Field programmable gate arrays Partitioning algorithms Coprocessors High performance computing Application software resource management Dynamic scheduling Computational modeling

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CellMR: A framework for supporting mapreduce on asymmetric cell-based clusters

CellMR: A framework for supporting mapreduce on asymmetric c...

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international Symposium on parallel and distributed Processing (IPDPS)

作者： M. Mustafa Rafique Benjamin Rose Ali R. Butt Dimitrios S. Nikolopoulos Department of Computer Science Virginia Technology Blacksburg VA USA Institute of Computer Science Foundation for Research and Technology Hellas Crete Greece

The use of asymmetric multi-core processors with on-chip computational accelerators is becoming common in a variety of environments ranging from scientific computing to enterprise applications. The focus of current research has been on making efficient use of individual systems, and porting applications to asymmetric processors. In this paper, we take the next step by investigating the use of multi-core-based systems, especially the popular Cell processor, in a cluster setting. We present CellMR, an efficient and scalable implementation of the MapReduce framework for asymmetric Cell-based clusters. The novelty of CellMR lies in its adoption of a streaming approach to supporting MapReduce, and its adaptive resource scheduling schemes: Instead of allocating workloads to the components once, CellMR slices the input into small work units and streams them to the asymmetric nodes for efficient processing. Moreover, CellMR removes I/O bottlenecks by design, using a number of techniques, such as double-buffering and asynchronous I/O, to maximize cluster performance. Our evaluation of CellMR using typical MapReduce applications shows that it achieves 50.5% better performance compared to the standard nonstreaming approach, introduces a very small overhead on the manager irrespective of application input size, scales almost linearly with increasing number of compute nodes (a speedup of 6.9 on average, when using eight nodes compared to a single node), and adapts effectively the parameters of its resource management policy between applications with varying computation density.

关键词： Acceleration Processor scheduling distributed computing Multicore processing resource management Computer architecture High performance computing parallel architectures Data processing parallel programming

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