Comparing scheduling techniques with varying workloads
Multi-constraint scheduling of MapReduce workloads
... and techniques are introduced in order to improve the scheduling of MapReduce in the presence of different constraints found in real-world scenarios, such as completion time goals, data locality, hardware ...
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Topology-aware GPU scheduling for learning workloads in cloud environments
... To feed the performance prediction model, the application pro- files are experimentally generated, defining the optimal resource al- location (best-performing) and some possible sub-optimal resource allocation ...
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A Survey on Task Scheduling For Parallel Workloads in the Cloud Computing System
... dynamic scheduling techniques have been suggested whereby VMs may be migrated on-the-fly to new compute nodes within the ...dynamic scheduling, the service provider allocates more resources as they ...
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Scheduling for Heavy-Tailed and Light-Tailed Workloads in Queueing Systems
... We show in this section that by choosing the multiprogramming level c carefully, it is possible to design LPS-c so that it provides ‘tail-robust’ performance. Our results in Section 4.3 and 4.4 highlight the tension in ...
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Scheduling, Characterization and Prediction of HPC Workloads for Distributed Computing Environments
... management techniques to minimize their resource usage while providing competitive quality of service to ...and scheduling of virtual ...real-world workloads from Microsoft Azure Public ...
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ASIdE: Using Autocorrelation-Based Size Estimation for Scheduling Bursty Workloads.
... V. D ISCUSSION A. ASIdE’s Optimality With ASIdE, upon each job completion, the entire queue is scanned to predict the service times of all queuing jobs according to the measured conditional probabilities. We have shown ...
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Task Scheduling for Highly Concurrent Analytical and Transactional Main-Memory Workloads
... We turn off merge operations for the column-store [36], in order to avoid unpredictable periods of inactivity due to the TPC-C tables being merged and locked, and achieve a stable behaviour for all variations. Due to the ...
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Network-aware migration control and scheduling of differentiated virtual machine workloads
... of workloads across ...predicted workloads, a migration schedule is es- tablished that minimizes the total completion ...objects, varying migra- tion times and limited ...
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A Survey on Scheduling Techniques in Hadoop
... IJEDR1501046 International Journal of Engineering Development and Research (www.ijedr.org) 253 B. Thirumala Rao et. al. [29] discuss on Apache Hadoop which was designed mainly for running large batch of jobs such as Web ...
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Exploring Portfolio Scheduling for Long-term Execution of Scientific Workloads in IaaS Clouds
... dynamic workloads and varying application ...online scheduling algorithms must be found. Portfolio scheduling, which selects dynamically a suitable policy from a broad portfolio, may provide a ...
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Data-Driven Intelligent Scheduling For Long Running Workloads In Large-Scale Datacenters
... IT techniques are becoming the most critical factors to booming evolutions and future success of various industries, which is named the Fourth Industrial ...intelligence techniques to improve effectiveness, ...
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On distributed scheduling for wireless networks with time-varying channels
... gion results by time sharing using global, common randomness together with static-split strategies. 2. We develop a decentralized, threshold-based throughput-optimal schedul- ing algorithm for the network, in which nodes ...
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Comparing Provisioning and Scheduling Strategies for Workflows on Clouds
... Montage (cf. Fig. 2(a)) is a workflow used in astronom- ical image processing. Its size varying depending on the dimension of the studied sky region. In our tests we used a version with 24 tasks. The workflow ...
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Scheduling Irregular Workloads on GPUs
... irregular workloads which hold dynamic data dependencies and parallelism, however, pose unique programming/performance challenges because a thread cannot make progress until all dependencies are ...special ...
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Dynamic Fractional Resource Scheduling for HPC Workloads
... In other words, we do not allow the allocation of a node to a set of tasks whose cumulative memory requirement exceeds 100%. This is to avoid the use of process swapping, which can have a hard to predict but almost ...
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Dynamic Fractional Resource Scheduling for HPC Workloads
... In other words, we do not allow the allocation of a node to a set of tasks whose cumulative memory requirement exceeds 100%. This is to avoid the use of process swapping, which can have a hard to predict but almost ...
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Scheduling Medical Application Workloads on Virtualized Computing Systems
... scheduling methodology that uses this prediction model to complement theoretical heuristics for optimized job scheduling must be implemented. I.3 Significance of the Study As mentioned earlier, the idea of ...
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Capacity Planning Techniques for Growing SAS Workloads
... SAS Add-In for Microsoft Office SAS Data Integration Studio SAS Enterprise Guide SAS Enterprise Miner SAS Forecast Studio SAS Information Map Studio SAS Management Console SAS Mod[r] ...
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Cost-Minimizing Preemptive Scheduling of MapReduce Workloads on Hybrid Clouds
... MapReduce workloads, which fully utilize their own on-premise resources while outsourcing the tasks only when ...disparate workloads of different MapReduce tasks, an efficient scheduling mechanism is ...
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Cost-minimizing preemptive scheduling of mapreduce workloads on hybrid clouds
... MapReduce workloads, which fully utilize their own on-premise resources while outsourcing the tasks only when ...disparate workloads of different MapReduce tasks, an efficient scheduling mechanism is ...
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