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Scheduling workflow applications on processors with different capabilities
, 2006
"... Efficient scheduling of workflow applications represented by weighted directed acyclic graphs (DAG) on a set of heterogeneous processors is essential for achieving high performance. The optimization problem is NPcomplete in general. A few heuristics for scheduling on heterogeneous systems have been ..."
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Cited by 26 (1 self)
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Efficient scheduling of workflow applications represented by weighted directed acyclic graphs (DAG) on a set of heterogeneous processors is essential for achieving high performance. The optimization problem is NPcomplete in general. A few heuristics for scheduling on heterogeneous systems have been proposed recently. However, few of them consider the case where processors have different capabilities. In this paper, we present a novel list scheduling based algorithm to deal with this situation. The algorithm (SDC) has two distinctive features. First, the algorithm takes into account the effect of Percentage of Capable Processors (PCP) when assigning the task node weights. For two task nodes with same average computation cost, our weight assignment policy tends to give higher weight to the task with small PCP. Secondly, during the processor selection phase, the algorithm adjusts the effective Earliest Finish Time strategy by incorporating the average communication cost between the current scheduling node and its children. Comparison study shows that our algorithm performs better than related work overall.
Posterior Task Scheduling Algorithms for Heterogeneous Computing Systems
"... Abstract. The task scheduling problem in heterogeneous system is known as NPhard. Recently, Bajaj and Agrawal proposed an algorithm TANH (Task duplicationbased scheduling Algorithm for Network of Heterogeneous systems) with optimality conditions, which are wider than previous optimality conditions ..."
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Abstract. The task scheduling problem in heterogeneous system is known as NPhard. Recently, Bajaj and Agrawal proposed an algorithm TANH (Task duplicationbased scheduling Algorithm for Network of Heterogeneous systems) with optimality conditions, which are wider than previous optimality conditions. TANH algorithm combines the clustering technique with task duplication. We propose two postprocessing algorithms, HPSA1 (Heterogeneous Posterior Scheduling Algorithm) and HPSA2, to reduce the schedule length for DAGs which don’t satisfy the optimality conditions of TANH algorithm. Our algorithms reduce the schedule length by exchanging task clusters in which its parent tasks reside. We compare with HCNF (Heterogeneous Critical Node First) algorithm by illustrating an example to show how our algorithms operate.
Vinod Kumar, Ph.d
"... In Distributed Computing Systems (DCSs), a program is split into small tasks and distributed among several computing elements to minimize the overall system cost. Several challenges have been posed by this mode of processing which can be classified mainly into two broad categories. One class belongs ..."
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In Distributed Computing Systems (DCSs), a program is split into small tasks and distributed among several computing elements to minimize the overall system cost. Several challenges have been posed by this mode of processing which can be classified mainly into two broad categories. One class belongs to the hardware oriented issues of building such systems more and more effective while the other aims at designing efficient algorithms to make the best use of the technology in hand. The task allocation problem in a DCS belongs to the later class. Intrinsically, task allocation problem is NP hard. To overcome this issue, it is necessary to introduce heuristics for generating near optimal solution to the given problem. This paper deals with the problem of task allocation in DCSs in such a way that the load on each processing node is almost balanced. Further, the development of an effective algorithm for allocating ‘m ’ tasks to ‘n ’ processors of a given distributed system using task clustering by taking both Inter Task Communication Cost (ITCC) and the Execution Cost (EC) is taken into consideration.
CASS: An Efficient Task Management System for Distributed Memory Architectures *
"... The thesis of this research is that the task of exposing the parallelism in a given application should be left to the algorithm designer, who has intimate knowledge of the application characteristics. On the other hand, the task of limiting the parallelism in a chosen parallel algorithm is best hand ..."
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The thesis of this research is that the task of exposing the parallelism in a given application should be left to the algorithm designer, who has intimate knowledge of the application characteristics. On the other hand, the task of limiting the parallelism in a chosen parallel algorithm is best handled by the compiler or operating system for the target MPP machine. Toward this end, we have developed CASS (for Clustering And Scheduling System), a task management system that provides facilities for automatic granularity optimization and task scheduling of parallel programs on distributed memory parallel architectures. Our tool environment, CASS, consists of a twophase method of compilertime scheduling, in which task clustering is performed prior to the actual scheduling process. The clustering module identifies the optimal number of processing nodes that the program will require to obtain maximum performance on the target parallel machine. The scheduling module maps the clusters onto a fixed number of processors and determines the order of execution of tasks in each processor. 1
Duplication based List Scheduling in Heterogeneous Distributed Computing
"... Whenever tasks of an application are scheduled in Heterogeneous Distributed Computing environment, idle slots on processors are efficiently utilized to minimize the overall running time. Since task assignment problem has been proved to be NPcomplete problem, many heuristics have been given in the l ..."
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Whenever tasks of an application are scheduled in Heterogeneous Distributed Computing environment, idle slots on processors are efficiently utilized to minimize the overall running time. Since task assignment problem has been proved to be NPcomplete problem, many heuristics have been given in the literature caring empty slots on processors as well as dependencies among tasks. This paper presents an efficient and effective way to allocate tasks of an application in the Heterogeneous Distributed Computing environment. Generally in list based static scheduling where computation time and communication time are known apriori. First tasks are prioritized and then the processors that minimize the cost function are assigned to the appropriate tasks. Duplication
Dedication
, 2006
"... To the Graduate Council: I am submitting herewith a dissertation written by Zhiao Shi entitled “Scheduling tasks with precedence constraints on heterogeneous distributed computing systems. ” I have examined the final electronic copy of this dissertation for form and content and rec ..."
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To the Graduate Council: I am submitting herewith a dissertation written by Zhiao Shi entitled “Scheduling tasks with precedence constraints on heterogeneous distributed computing systems. ” I have examined the final electronic copy of this dissertation for form and content and rec
A comparison of general approaches to . . .
, 1997
"... This paper demonstrates the effectiveness of the twophase method of scheduling, in which task clustering is performed prior to the actual scheduling process. Task clustering determines the optimal or nearoptimal number of processors on which to schedule the task graph. In other words, there is nev ..."
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This paper demonstrates the effectiveness of the twophase method of scheduling, in which task clustering is performed prior to the actual scheduling process. Task clustering determines the optimal or nearoptimal number of processors on which to schedule the task graph. In other words, there is never a need to use more processors (even though they are available) than the number of clusters produced by the task clustering algorithm. The paper also indicates that when task clustering is performed prior to scheduling, load balancing (LB) is the preferred approach for cluster merging. LB is fast, easy to implement, and produces significantly better final schedules than communication traffic minimizing(CTM). In summary, the twophase method consisting of task clustering and load balancing is a simple yet highly effective strategy for scheduling task graphs on distributed memory parallel architectures.