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Titlebook: Job Scheduling Strategies for Parallel Processing; 16th International W Walfredo Cirne,Narayan Desai,Uwe Schwiegelshohn Conference proceedi

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樓主: Monroe
21#
發(fā)表于 2025-3-25 04:35:12 | 只看該作者
Conference proceedings 2013PP 2012, which was held in Shanghai, China, in May 2012. The 14 revised papers presented were carefully reviewed and selected from 24 submissions. The papers cover the following topics: parallel batch scheduling; workload analysis and modeling; resource management system software studies; and Web scheduling.
22#
發(fā)表于 2025-3-25 10:21:49 | 只看該作者
23#
發(fā)表于 2025-3-25 13:07:43 | 只看該作者
Job Scheduling Strategies for Parallel Processing978-3-642-35867-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
24#
發(fā)表于 2025-3-25 16:23:03 | 只看該作者
25#
發(fā)表于 2025-3-25 21:32:59 | 只看該作者
Web-Scale Job Scheduling,s their high-performance computing counterparts. And yet little is known about the unique job scheduling challenges of these environments. This article aims to ameliorate this situation. It discusses the challenges of running web infrastructure and describes several techniques to address them. It al
26#
發(fā)表于 2025-3-26 01:02:31 | 只看該作者
DEMB: Cache-Aware Scheduling for Distributed Query Processing,arge scalable distributed systems by connecting multiple heterogeneous less powerful machines rather than purchasing expensive homogeneous and very powerful machines. As more servers are added to such clusters, more memory is available for caching data objects across the distributed machines. Howeve
27#
發(fā)表于 2025-3-26 07:02:39 | 只看該作者
28#
發(fā)表于 2025-3-26 12:29:09 | 只看該作者
On Workflow Scheduling for End-to-End Performance Optimization in Distributed Network Environments,rk environments. With limited computing resources, it is often unavoidable to map multiple workflow modules to the same computer node with possible concurrent module execution, whose scheduling may significantly affect the workflow’s end-to-end performance in the network. We formulate this on-node w
29#
發(fā)表于 2025-3-26 16:01:37 | 只看該作者
Dynamic Kernel/Device Mapping Strategies for GPU-Assisted HPC Systems,ortant for high-performance computing (HPC) systems. Existing GPU execution environment restricts the GPU usage to local host node. This is suitable for standalone computer nodes, but becomes inefficient for HPC systems that consist of a large number of GPU-assisted nodes. In this paper, a novel fra
30#
發(fā)表于 2025-3-26 18:00:56 | 只看該作者
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