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Resource capacity is often over provisioned to primarily deal with short periods of peak load. Shaping these peaks by shifting them to low utilization periods (valleys) is referred to as "resource consumption shaping". While originally aimed at the data center level, the resource consumption shaping we consider focuses on local resources, like CPU or I/O as we have identified that individual...
Hadoop, an open source implementation of MapReduce, uses slots to represent resource sharing. The number of slots in a Hadoop cluster node specifies the concurrency of task execution. Thus, the slot configuration has a significant impact on performance. The number of slots is by default hand-configured (static) and slots share resources "fairly". As resource capacity (e.g., #cores) continues...
Space sharing approaches are widely used in job scheduling for HPC systems. The main drawback of these approaches is the blocking of short jobs, which results in low throughput. The research on gang scheduling has shown the potential of time sharing in improving throughput. However, traditional gang scheduling adds jobs for time sharing without selection, which may cause a higher performance degradation...
We present correspondence with category Latent Dirichlet Allocation (corr-c-LDA), a novel probabilistic topic model for the task of image and video annotation. The heart of our annotation model lies in introducing the class label information and assuming the dependence relationships between class label and image feature, as well as class label and annotation words. Instead of modeling the image and...
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