• Journal of KIISE:Computer Systems and Theory
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• v.37 no.2
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• pp.76-89
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• 2010

The performance of Distributed Heterogeneous Computing System depends on the algorithm which schedules input DAG graph. Among various scheduling algorithms, list scheduling algorithm provides superior performance with low complexity. List scheduling consists of task prioritizing phase and processor allocation phase, but most studies only focus on task prioritizing phase. In this paper, we propose LIP policy which has the same complexity with traditional allocation policies but has superior performance. The performance of LIP has been observed by applying them to task prioritizing phase of traditional list scheduling algorithms, HCPT, HEFT, GCA, and PETS. The results show that LIP has better performance than insertion-based policy and non-insertion-based policy, which are traditional processor allocation policies.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.9
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• pp.1073-1082
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• 1999

본 논문에서는 시스템 내의 프로세서들을 효과적으로 사용하기 위한 적응적 프로세서 할당 정책을 제안한다. 프로그램의 병렬성을 향상시키기 위하여 일반적으로 병렬 처리에 사용될 프로세서 개수를 증가시킨다. 그러나 증가된 프로세서들은 그레인 크기에 변화를 일으키며 이는 캐쉬 성능에 영향을 미친다. 특히 대역이 제한된 공유 버스를 사용하는 시스템에서는 프로세서 개수의 증가는 공유 버스에 대한 접근 경쟁을 크게 증가하므로 버스에서 대기하는 시간이 프로세서 증가에 의한 계산 능력 이득을 상쇄시키는 주요한 원인이 되고 있다. 본 논문에서 제안한 적응적 프로세서 할당 정책은 프로그램이 수행되는 도중에 임의의 기간동안 공유버스에 대기중인 프로세서 분포에 관한 정보를 얻는다. 그리고 이 정보를 바탕으로 프로세서 개수를 변경하는 방법이다. 모의 시험에서 적응적 프로세서 할당 정책은 프로그램들의 버스 트래픽 특성에 따른 최적의 적합한 프로세서 개수를 발견함을 보인다. 그리고 적응적 프로세서 할당 정책은 고정된 프로세서 개수를 사용한 가장 좋은 성능보다는 다소 떨어진 성능을 나타내었으나 시스템의 프로세서 활용성을 높여 효과적 시스템 사용에 기여함을 보인다. Abstract In this paper, the adaptive processor allocation policy is suggested to make effective use of processors in system. To enhance the parallelism, the number of processors used in the parallel computing may be increased. However, increasing the number of processors affects the grain size of the parallel program. Therefore, it affects the cache performance. In particular, when the shared bus is employed, since increasing the number of processors can result in a significant amount of contention to achieve the shared-bus, the increased computing power is offset by the bus waiting time due to these contentions. The adaptive processor allocation policy acquires the information about the distribution of waiting processors on shared bus for any execution period of programs. And it changes the number of processors working in parallel processing during the program's run. Our simulation results show that the adaptive processor allocation policy finds the optimum feasible number of processors based on the bus traffic characteristic of programs. Thus, it contributes to effective system utilization, even though it performs slightly less efficiently than using a fixed number of processors with the best performance.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.245-252
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• 2001

Multicomputer systems achieve high performance by utilizing a number of computing nodes. Multidimensional meshes have become popular as multicomputer architectures due to their simplicity and efficiency. In this paper we propose an efficient processor allocation scheme for 3D torus based on first-fit approach. The scheme minimizes the allocation time by effectively manipulating the 3D information an 2D information using CST (Coverage Status Table). Comprehensive computer simulation reveals that the allocation time of the proposed scheme is always smaller than the earlier scheme based on best-fit approach, while allowing comparable processor utilization. The difference gets more significant as the input load increases. To investigate the performance of the proposed scheme with different scheduling environment, non-FCFs scheduling policy along with the typical FCFS policy is also studied.

• Journal of Computing Science and Engineering
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• v.8 no.1
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• pp.43-56
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• 2014

Semi-partitioned scheduling is a new approach for allocating tasks on multiprocessor platforms. By splitting some tasks between processors, semi-partitioned scheduling is used to improve processor utilization. In this paper, a new semi-partitioned scheduling algorithm called SS-DRM is proposed for multiprocessor platforms. The scheduling policy used in SS-DRM is based on the delayed rate monotonic algorithm, which is a modified version of the rate monotonic algorithm that can achieve higher processor utilization. This algorithm can safely schedule any system composed of two tasks with total utilization less than or equal to that on a single processor. First, it is formally proven that any task which is feasible under the rate monotonic algorithm will be feasible under the delayed rate monotonic algorithm as well. Then, the existing allocation method is extended to the delayed rate monotonic algorithm. After that, two improvements are proposed to achieve more processor utilization with the SS-DRM algorithm than with the rate monotonic algorithm. According to the simulation results, SS-DRM improves the scheduling performance compared with previous work in terms of processor utilization, the number of required processors, and the number of created subtasks.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.116-126
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• 2015

In a distributed heterogeneous computing system, the performance of a parallel application greatly depends on its task scheduling algorithm. Therefore, in order to improve the performance, it is essential to consider some factors that can have effect on the performance of the parallel application in a given environment. One of the most important factors that affects the total execution time is a critical path. In this paper, we propose the CLTS algorithm for a task scheduling. The CLTS sets the priorities of all nodes to improve overall performance by applying leveling method to improve parallelism of task execution and by reducing the delay caused by waiting for execution of critical nodes in priority phase. After that, it conditionally uses insertion based policy or duplication based policy in processor allocation phase to reduce total schedule time. To evaluate the performance of the CLTS, we compared the CLTS with the DCPD and the HCPFD in our simulation. The results of the simulations show that the CLTS is better than the HCPFD by 7.29% and the DCPD by 8.93%. with respect to the average SLR, and also better than the HCPFD by 9.21% and the DCPD by 7.66% with respect to the average speedup.