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Anindya Neogi
Researcher at IBM
Publications - 47
Citations - 2406
Anindya Neogi is an academic researcher from IBM. The author has contributed to research in topics: Server & Data center. The author has an hindex of 18, co-authored 47 publications receiving 2377 citations.
Papers
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Proceedings ArticleDOI
pMapper: power and migration cost aware application placement in virtualized systems
TL;DR: This work investigates the design, implementation, and evaluation of a power-aware application placement controller in the context of an environment with heterogeneous virtualized server clusters, and presents the pMapper architecture and placement algorithms to solve one practical formulation of the problem: minimizing power subject to a fixed performance requirement.
Proceedings ArticleDOI
Power-aware dynamic placement of HPC applications
TL;DR: This work investigates the use of power management techniques for high performance applications on modern power-efficient servers with virtualization support, and shows that for HPC applications, working set size is a key parameter to take care of while placing applications on virtualized servers.
Patent
Systems, methods and computer programs for determining dependencies between logical components in a data processing system or network
TL;DR: In this article, a dependency generator identifies correlations between the run-time activity of the monitored components, and a weighting is computed for each dependency relationship based on the consistency of containment.
Patent
Techniques for placing applications in heterogeneous virtualized systems while minimizing power and migration cost
Anindya Neogi,Akshat Verma +1 more
TL;DR: In this article, a time horizon is divided into a plurality of time windows, and, for each given one of the windows, a placement of the N applications is computed, taking into account power cost, migration cost, and performance benefit.
Proceedings ArticleDOI
WattApp: an application aware power meter for shared data centers
TL;DR: WattApp is an application-aware power meter for shared data centers that addresses the increasing heterogeneity between applications in emerging virtualized data centers like clouds and introduces application parameters (e.g, throughput) in the power modeling framework.