共查询到20条相似文献,搜索用时 15 毫秒
1.
Dynamic workload balancing of parallel applications with user-level scheduling on the Grid 总被引:1,自引:0,他引:1
This paper suggests a hybrid resource management approach for efficient parallel distributed computing on the Grid. It operates on both application and system levels, combining user-level job scheduling with dynamic workload balancing algorithm that automatically adapts a parallel application to the heterogeneous resources, based on the actual resource parameters and estimated requirements of the application. The hybrid environment and the algorithm for automated load balancing are described, the influence of resource heterogeneity level is measured, and the speedup achieved with this technique is demonstrated for different types of applications and resources. 相似文献
2.
Deepak Kumar Patel Devashree Tripathy Chitaranjan Tripathy 《Engineering with Computers》2016,32(2):173-188
Grid computing has emerged a new field, distinguished from conventional distributed computing. It focuses on large-scale resource sharing, innovative applications and in some cases, high performance orientation. The Grid serves as a comprehensive and complete system for organizations by which the maximum utilization of resources is achieved. The load balancing is a process which involves the resource management and an effective load distribution among the resources. Therefore, it is considered to be very important in Grid systems. For a Grid, a dynamic, distributed load balancing scheme provides deadline control for tasks. Due to the condition of deadline failure, developing, deploying, and executing long running applications over the grid remains a challenge. So, deadline failure recovery is an essential factor for Grid computing. In this paper, we propose a dynamic distributed load-balancing technique called “Enhanced GridSim with Load balancing based on Deadline Failure Recovery” (EGDFR) for computational Grids with heterogeneous resources. The proposed algorithm EGDFR is an improved version of the existing EGDC in which we perform load balancing by providing a scheduling system which includes the mechanism of recovery from deadline failure of the Gridlets. Extensive simulation experiments are conducted to quantify the performance of the proposed load-balancing strategy on the GridSim platform. Experiments have shown that the proposed system can considerably improve Grid performance in terms of total execution time, percentage gain in execution time, average response time, resubmitted time and throughput. The proposed load-balancing technique gives 7 % better performance than EGDC in case of constant number of resources, whereas in case of constant number of Gridlets, it gives 11 % better performance than EGDC. 相似文献
3.
考虑网格资源异构、自治、动态等特性,讨论本地用户具有强占优先权情况下的任务调度问题,提出了TBBS(Time-Balancing Based Scheduling Algorithm)算法.建立调度优化模型,以期望完成时间最小为目标选择执行任务的最佳资源组合.以时间均衡策略将任务分解并调度到资源上执行,减少了子任务同步时因等待而产生的延时,获得较好的并行计算性能.采用重复调度策略,适应计算网格中资源的特性. 相似文献
4.
J. A. Martínez F. Almeida E. M. Garzón A. Acosta V. Blanco 《The Journal of supercomputing》2011,58(3):385-393
Dynamic load balancing in heterogeneous systems is a fundamental research topic in parallel computing due to the high availability
of such systems. The efficient utilization of the heterogeneous resources can significantly enhance the performance of the
parallel system. At the same time, adapting parallel codes to state-of-the-art parallel computers composed of heterogeneous
multinode–multicore processors becomes a very hard task because parallel codes are highly dependent on the parallel architectures.
That means that applications must be tailored requiring a great deal of programming effort. We have developed the ALBIC (Adaptive
Load Balancing of Iterative Computation) system that allows for the dynamic load balancing of iterative codes in heterogeneous
dedicated and nondedicated Linux based systems. In order to validate the system several parallel codes have been analyzed
in different scenarios. The results show that the ALBIC approach achieves better performance than the other proposal. This
lightweighted library eases porting homogeneous parallel codes to heterogeneous platforms, since the code intrusion is low
and the programming effort is quite reduced. 相似文献
5.
Computational Grids are emerging as a new infrastructure for high performance computing. Since the resources in a Grid can
be heterogeneous and distributed, mesh-based applications require a mesh partitioner that considers both processor and network
heterogeneity. We have developed a heterogeneous mesh partitioner, called PaGrid. PaGrid uses a multilevel graph partitioning
approach, augmented by execution time load balancing in the final uncoarsening phase. We show that minimization of total communication
cost (e.g., as used by JOSTLE) can lead to significant load being placed on processors connected by slow links, which results
in higher application execution times. Therefore, PaGrid balances the estimated execution time of the application across processors.
PaGrid performance is compared with two existing mesh partitioners, METIS 4.0 and JOSTLE 3.0, for mapping several application
meshes to two models of heterogeneous computational Grids. PaGrid is found to produce significantly better partitions than
JOSTLE and slightly better partitions than METIS in most cases, in terms of estimated application execution time averaged
over a large number of runs with different random number seeds. 相似文献
6.
Due to the emergence of Grid computing over the Internet, there is presently a need for dynamic load balancing algorithms
which take into account the characteristics of Grid computing environments. In this paper, we consider a Grid architecture
where computers belong to dispersed administrative domains or groups which are connected with heterogeneous communication
bandwidths. We address the problem of determining which group an arriving job should be allocated to and how its load can
be distributed among computers in the group to optimize the performance. We propose algorithms which guarantee finding a load
distribution over computers in a group that leads to the minimum response time or computational cost. We then study the effect
of pricing on load distribution by considering a simple pricing function. We develop three fully distributed algorithms to
decide which group the load should be allocated to, taking into account the communication cost among groups. These algorithms
use different information exchange methods and a resource estimation technique to improve the accuracy of load balancing.
We conducted extensive simulations to evaluate the performance of the proposed algorithms and strategies. 相似文献
7.
Kuo-Qin Yan Shun-Sheng Wang Shu-Ching Wang Chiu-Ping Chang 《Expert systems with applications》2009,36(10):12054-12064
Grid computing has become conventional in distributed systems due to technological advancements and network popularity. Grid computing facilitates distributed applications by integrating available idle network computing resources into formidable computing power. As a result, by using efficient integration and sharing of resources, this enables abundant computing resources to solve complicated problems that a single machine cannot manage. However, grid computing mines resources from accessible idle nodes and node accessibility varies with time. A node that is currently idle, may become occupied within a second of time and then be unavailable to provide resources. Accordingly, node selection must provide effective and sufficient resources over a long period to allow load assignment. This study proposes a hybrid load balancing policy to integrate static and dynamic load balancing technologies. Essentially, a static load balancing policy is applied to select effective and suitable node sets. This will lower the unbalanced load probability caused by assigning tasks to ineffective nodes. When a node reveals the possible inability to continue providing resources, the dynamic load balancing policy will determine whether the node in question is ineffective to provide load assignment. The system will then obtain a new replacement node within a short time, to maintain system execution performance. 相似文献
8.
大规模CFD多区结构网格任务负载平衡算法 总被引:1,自引:0,他引:1
针对现有负载平衡算法的适应度低、可扩展性差、通信开销度量不准确的缺陷, 提出一种大规模CFD多区结构网格任务负载平衡算法。通过对网格块的分割、网格块之间的组合映射、进程上网格计算量的调整来实现并行CFD任务负载平衡。实验结果表明, 该算法既适应同构平台也适应异构平台, 既适应网格块数多于进程数的情况也适应网格块数少于进程数的情况, 该算法可使得整个计算空间分配到各进程上的计算量负载平衡, 同时使得各进程间的最大通信开销最小。 相似文献
9.
高性能集群工作方式越来越受到人们的关注。通常集群是一组通过网络连接的多个异构的计算机系统。在集群工作模式下,一个非常重要的问题就是要确保负载量的均衡。由于目前的负载均衡系统大多只支持同构集群环境,且均衡粒度为作业级,过于粗糙,所以不能很好的适用于并行程序中并行任务的均衡。本文提出了一种并行程序的开发框架,使用移动Agent技术解决任务的动态迁移性,为程序员提供了一个简单的开发接口,大大地简化了他们的工作。系统采用java和Aglet平台开发而成。实验表明,该系统灵活有效。 相似文献
10.
Leyli Mohammad KhanliAuthor Vitae Shiva RazzaghzadehAuthor Vitae 《Future Generation Computer Systems》2012,28(4):682-688
Grid computing is a network of software-hardware capabilities. It serves as a comprehensive and complete system for organizations by which the maximum utilization from resources is achieved. Resource distribution in a heterogeneous and unstable environment and also effective load distribution among these resources are the important and difficult problems in Grid networks. Using dynamic and static algorithms or searching tree and Branch and Bound algorithm are considered to be among the available methods to reach the load balancing in Grid networks. This paper presents a new method for dynamic load balancing. In this method, we use the subtraction of forward and backward ants as a competency rank to take the priority of the sites, and we use a control word to search the suitable resource as well. Our main purpose is to devote jobs to the existing resources based on their processing power. Simulation results show that the proposed method can reduce the total completion time and also total tardiness to get the load balancing. The cost of using resources as an effective factor in load balancing is also observed. 相似文献
11.
Kenli Li Zhao Tong Dan Liu Teklay Tesfazghi Xiangke Liao 《Frontiers of Computer Science in China》2011,5(4):513-525
Grid computing is the combination of computer resources in a loosely coupled, heterogeneous, and geographically dispersed
environment. Grid data are the data used in grid computing, which consists of large-scale data-intensive applications, producing
and consuming huge amounts of data, distributed across a large number of machines. Data grid computing composes sets of independent
tasks each of which require massive distributed data sets that may each be replicated on different resources. To reduce the
completion time of the application and improve the performance of the grid, appropriate computing resources should be selected
to execute the tasks and appropriate storage resources selected to serve the files required by the tasks. So the problem can
be broken into two sub-problems: selection of storage resources and assignment of tasks to computing resources. This paper
proposes a scheduler, which is broken into three parts that can run in parallel and uses both parallel tabu search and a parallel
genetic algorithm. Finally, the proposed algorithm is evaluated by comparing it with other related algorithms, which target
minimizing makespan. Simulation results show that the proposed approach can be a good choice for scheduling large data grid
applications. 相似文献
12.
Grid computing now becomes a practical computing paradigm and solution for distributed systems and applications. Currently increasing resources are involved in Grid environments and a large number of applications are running on computational Grids. Unfortunately Grid computing technologies are still far away from reach of inexperienced application users, e.g., computational scientists and engineers. A software layer is required to provide an easy interface of Grids to end users.To meet this requirement HEAVEN (Hosting European Application Virtual ENvironment) upperware is proposed to build on top of Grid middleware. This paper presents HEAVEN philosophy of virtual computing for Grids – a combinational idea of simulation and emulation approaches. The concept of Virtual Private Computing Environment (VPCE) is thereafter proposed and defined. The design and current implementation of HEAVEN upperware are discussed in detail. Use case of Ag2D application justifies the philosophy of HEAVEN virtual computing methodology and the design/implementation of HEAVEN upperware. 相似文献
13.
《Journal of Parallel and Distributed Computing》2006,66(5):716-731
Cosmology SAMR simulations have played a prominent role in the field of astrophysics. The emerging distributed computing systems provide an economic alternative to the traditional parallel machines, and enable scientists to conduct cosmological simulations that require vast computing power. An important issue of conducting distributed cosmological simulations is about performance and efficiency. In this paper, we present a dynamic load balancing scheme called DistDLB that is designed to improve the performance of distributed cosmology simulations. Distributed systems, e.g. the Computation Grid, usually consist of heterogeneous resources connected with shared networks. By considering these features of distributed systems and unique characteristics of cosmology SAMR simulations, DistDLB focuses on reducing the redistribution cost through a hierarchical load balancing approach and a run-time decision making mechanism. Heuristic methods have been proposed to adaptively adjust load balancing strategies based on the observation of the current system and application state. Our experiments with real-world cosmology simulations on production systems indicate that the proposed DistDLB scheme can effectively improve the performance of cosmology simulations by 2.56–79.14% as compared to the scheme that does not consider the heterogeneous and dynamic features of distributed systems. 相似文献
14.
Task based approaches with dynamic load balancing are well suited to exploit parallelism in irregular applications. For such
applications, the execution time of tasks can often not be predicted due to input dependencies. Therefore, a static task assignment
to execution resources usually does not lead to the best performance. Moreover, a dynamic load balancing is also beneficial
for heterogeneous execution environments. In this article a new adaptive data structure is proposed for storing and balancing
a large number of tasks, allowing an efficient and flexible task management. Dynamically adjusted blocks of tasks can be moved
between execution resources, enabling an efficient load balancing with low overhead, which is independent of the actual number
of tasks stored. We have integrated the new approach into a runtime system for the execution of task-based applications for
shared address spaces. Runtime experiments with several irregular applications with different execution schemes show that
the new adaptive runtime system leads to good performance also in such situations where other approaches fail to achieve comparable
results. 相似文献
15.
Kashif Hesham Khan Kalim Qureshi Mostafa Abd-El-Barr 《The Journal of supercomputing》2014,68(3):1487-1502
Scheduling large-scale application in heterogeneous grid systems is a fundamental NP-complete problem that is critical to obtain good performance and execution cost. To achieve high performance in a grid system it requires effective task partitioning, resource management and load balancing. The heterogeneous and dynamic nature of a grid, as well as the diverse demands of applications running on the grid, makes grid scheduling a major task. Existing schedulers in wide-area heterogeneous systems require a large amount of information about the application and the grid environment to produce reasonable schedules. However, this required information may not be available, may be too expensive to collect, or may increase the runtime overhead of the scheduler such that the scheduler is rendered ineffective. We believe that no one scheduler is appropriate for all grid systems and applications. This is because while data parallel applications in which further data partitioning is possible can be further improved by efficient management of resources, smart selection of resources and load balancing can be possible, in functional/not-dividable-task parallel applications such partitioning is either not possible or difficult or expensive in term of performance. In this paper, we propose a scheduler for data parallel applications (SDPA) which offers an efficient task partitioning and load balancing strategy for data parallel applications in grid environment. The proposed SDPA offers two major features: maintaining job priority even if insufficient number of free resources is available and pre-task assignment to cut the idle time of nodes. The SDPA selects nodes smartly according to the nature of task and the nodes’ resources availability. Simulation results conducted reveal that SDPA achieves performance improvement over reported strategies in the reviewed literature in terms of execution time, throughput and waiting time. 相似文献
16.
在异构计算环境中负载平衡是一个重要问题。移动代理是一种新的分布计算模式,具有许多优势,比如移动代理能够从一台机器移动到另一台机器执行任务。该文提出了一个基于移动代理的并行计算框架,利用一个二段负载平衡策略使程序能够适应不断变化的异构计算环境。实验结果显示移动代理不仅能够用于并行计算,而且能够有效地改善负载平衡。 相似文献
17.
《Parallel Computing》2007,33(7-8):467-487
The approaches to deal with scheduling and load balancing on PC-based cluster systems are famous and well-known. Self-scheduling schemes, which are suitable for parallel loops with independent iterations on cluster computer system, they have been designed in the past. In this paper, we propose a new scheme that can adjust the scheduling parameter dynamically on an extremely heterogeneous PC-based cluster and Grid computing environments in order to improve system performance. A Grid computing environment consists of multiple PC-based clusters is constructed using Globus Toolkit and MPICH-G2 middleware. The experimental results show that our scheduling can result in higher performance than other similar schemes on Grid computing environments. 相似文献
18.
This paper proposes a coordinated load management protocol for Peer-to-Peer?(P2P) coupled federated Grid systems. The participants in the system, such as the resource providers and the consumers who belong to multiple control domains, work together to enable a coordinated federation. The coordinated load management protocol embeds a logical spatial index over a Distributed Hash Table?(DHT) space for efficient management of the coordination objects; the DHT-based space serves as a kind of decentralized blackboard system. We show that our coordination protocol has a message complexity that is logarithmic to the number of nodes in the system, which is significantly better than existing broadcast based coordination protocols. The proposed load management protocol can be applied for efficiently coordinating resource brokering services of distributed computing systems such as grids and PlanetLab. Resource brokering services are the main components that control the way applications are scheduled, managed and allocated in a distributed, heterogeneous, and dynamic Grid computing environments. Existing Grid resource brokers, e-Science application work-flow schedulers, operate in tandem but still lack a coordination mechanism that can lead to efficient application schedules across distributed resources. Further, lack of coordination exacerbates the utilization of various resources (such as computing cycles and network bandwidth). The feasibility of the proposed coordinated load management protocol is studied through extensive simulations. 相似文献
19.
Arun Krishnan 《Concurrency and Computation》2005,17(13):1607-1623
Improvements in the performance of processors and networks have made it feasible to treat collections of workstations, servers, clusters and supercomputers as integrated computing resources or Grids. However, the very heterogeneity that is the strength of computational and data Grids can also make application development for such an environment extremely difficult. Application development in a Grid computing environment faces significant challenges in the form of problem granularity, latency and bandwidth issues as well as job scheduling. Currently existing Grid technologies limit the development of Grid applications to certain classes, namely, embarrassingly parallel, hierarchical parallelism, work flow and database applications. Of all these classes, embarrassingly parallel applications are the easiest to develop in a Grid computing framework. The work presented here deals with creating a Grid‐enabled, high‐throughput, standalone version of a bioinformatics application, BLAST, using Globus as the Grid middleware. BLAST is a sequence alignment and search technique that is embarrassingly parallel in nature and thus amenable to adaptation to a Grid environment. A detailed methodology for creating the Grid‐enabled application is presented, which can be used as a template for the development of similar applications. The application has been tested on a ‘mini‐Grid’ testbed and the results presented here show that for large problem sizes, a distributed, Grid‐enabled version can help in significantly reducing execution times. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
20.
在众核处理器应用中,主要难点在于异构并行应用模式和负载均衡的策略,对于计算流体力学,需要针对相关应用设计相应的方案。我们针对湍流直接数值模拟中串行程序含有部分并行度较高的子程序或函数的特点,设计了一种新的并行计算模式,给出了一种异构平台优化方案,并在中科院超级计算系统"元"上进行了测试和分析,对领域内的典型算例进行了性能测试,着重讨论了不同规模下采用offload模式的CPU和MIC异构并行的扩展性能。 相似文献