Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of...Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.展开更多
When the communication time is relatively shorter than the computation time for every task, the task duplication based scheduling (TDS) algorithm proposed by Darbha and Agrawal generates an optimal schedule. Park and ...When the communication time is relatively shorter than the computation time for every task, the task duplication based scheduling (TDS) algorithm proposed by Darbha and Agrawal generates an optimal schedule. Park and Choe also proposed an extended TDS algorithm whose optimality condition is less restricted than that of TDS algorithm, but the condition is very complex and is difficult to satisfy when the number of tasks is large. An efficient algorithm is proposed whose optimality condition is less restricted and simpler than both of the algorithms, and the schedule length is also shorter than both of the algorithms. The time complexity of the proposed algorithm is O(v2), where v represents the number of tasks.展开更多
A scheduling scheme is proposed to reduce execution time by means of both checkpoint sharing and task duplication under a peer-to-peer(P2P) architecture. In the scheme, the checkpoint executed by each peer(i.e., a res...A scheduling scheme is proposed to reduce execution time by means of both checkpoint sharing and task duplication under a peer-to-peer(P2P) architecture. In the scheme, the checkpoint executed by each peer(i.e., a resource) is used as an intermediate result and executed in other peers via its duplication and transmission. As the checkpoint is close to a final result, the reduction of execution time for each task becomes higher, leading to reducing turnaround time. To evaluate the performance of our scheduling scheme in terms of transmission cost and execution time, an analytical model with an embedded Markov chain is presented. We also conduct simulations with a failure rate of tasks and compare the performance of our scheduling scheme with that of the existing scheme based on client-server architecture. Performance results show that our scheduling scheme is superior to the existing scheme with respect to the reduction of execution time and turnaround time.展开更多
文摘Heterogeneous computing is one effective method of high performance computing with many advantages. Task scheduling is a critical issue in heterogeneous environments as well as in homogeneous environments. A number of task scheduling algorithms for homogeneous environments have been proposed, whereas, a few for heterogeneous environments can be found in the literature. A novel task scheduling algorithm for heterogeneous environments, called the heterogeneous critical task （HCT） scheduling algorithm is presented. By means of the directed acyclic graph and the gantt graph, the HCT algorithm defines the critical task and the idle time slot. After determining the critical tasks of a given task, the HCT algorithm tentatively duplicates the critical tasks onto the processor that has the given task in the idle time slot, to reduce the start time of the given task. To compare the performance of the HCT algorithm with several recently proposed algorithms, a large set of randomly generated applications and the Gaussian elimination application are randomly generated. The experimental result has shown that the HCT algorithm outperforms the other algorithm.
文摘When the communication time is relatively shorter than the computation time for every task, the task duplication based scheduling (TDS) algorithm proposed by Darbha and Agrawal generates an optimal schedule. Park and Choe also proposed an extended TDS algorithm whose optimality condition is less restricted than that of TDS algorithm, but the condition is very complex and is difficult to satisfy when the number of tasks is large. An efficient algorithm is proposed whose optimality condition is less restricted and simpler than both of the algorithms, and the schedule length is also shorter than both of the algorithms. The time complexity of the proposed algorithm is O(v2), where v represents the number of tasks.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2012R1A1A4A0105777)supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (NIPA-2013-H030113-4007) supervised by the NIPA (National IT Industry Promotion Agency)
文摘A scheduling scheme is proposed to reduce execution time by means of both checkpoint sharing and task duplication under a peer-to-peer(P2P) architecture. In the scheme, the checkpoint executed by each peer(i.e., a resource) is used as an intermediate result and executed in other peers via its duplication and transmission. As the checkpoint is close to a final result, the reduction of execution time for each task becomes higher, leading to reducing turnaround time. To evaluate the performance of our scheduling scheme in terms of transmission cost and execution time, an analytical model with an embedded Markov chain is presented. We also conduct simulations with a failure rate of tasks and compare the performance of our scheduling scheme with that of the existing scheme based on client-server architecture. Performance results show that our scheduling scheme is superior to the existing scheme with respect to the reduction of execution time and turnaround time.
