Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Por management has become a central issue inlarge-scale computing clusters where a considerable amount ofenergy is consumed and a large operational cost is incurredannually. Traditional por management techniques have a centralizeddesign that creates challenges for scalability of computingclusters. In this work,  develop a framework for distributedpor budget allocation that maximizes the utility of computingnodes subject to a total por budget constraint. To eliminate the role of central coordinator in the primaldualtechnique,  propose a distributed por budget allocationalgorithm (DiBA) which maximizes the combined performanceof a cluster subject to a por budget constraint in a distributedfashion. Specifically, DiBA is a consensus-based algorithm inwhich each server determines its optimal por consumptionlocally by communicating its state with neighbors (connectednodes) in a cluster.  characterize a synchronous primal-dualtechnique to obtain a benchmark for comparison with thedistributed algorithm that  propose.  demonstrate numericallythat DiBA is a scalable algorithm that outperforms theconventional primal-dual method on large scale clusters in termsof convergence time. Further, DiBA eliminates the communicationbottleneck in the primal-dual method.  thoroughly evaluatethe characteristics of DiBA through simulations of large-scaleclusters. Furthermore,  provide results from a proof-of-conceptimplementation on a real experimental cluster.
['Masoud Badiei', 'Xin Zhan', 'Reza Azimi', 'Sherief Reda', 'Na Li']
I am writing a research paper on a idea DiBA: Distributed Power Budget Allocation for Large-Scale Computing Clusters
[{"from": "human", "value": "I am writing a research paper on a idea DiBA: Distributed Power Budget Allocation for Large-Scale Computing Clusters"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Por management has become a central issue inlarge-scale computing clusters where a considerable amount ofenergy is consumed and a large operational cost is incurredannually. Traditional por management techniques have a centralizeddesign that creates challenges for scalability of computingclusters. In this work,  develop a framework for distributedpor budget allocation that maximizes the utility of computingnodes subject to a total por budget constraint. To eliminate the role of central coordinator in the primaldualtechnique,  propose a distributed por budget allocationalgorithm (DiBA) which maximizes the combined performanceof a cluster subject to a por budget constraint in a distributedfashion. Specifically, DiBA is a consensus-based algorithm inwhich each server determines its optimal por consumptionlocally by communicating its state with neighbors (connectednodes) in a cluster.  characterize a synchronous primal-dualtechnique to obtain a benchmark for comparison with thedistributed algorithm that  propose.  demonstrate numericallythat DiBA is a scalable algorithm that outperforms theconventional primal-dual method on large scale clusters in termsof convergence time. Further, DiBA eliminates the communicationbottleneck in the primal-dual method.  thoroughly evaluatethe characteristics of DiBA through simulations of large-scaleclusters. Furthermore,  provide results from a proof-of-conceptimplementation on a real experimental cluster."}]