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184
2 NONMONOTONE BARZILAI-BORWEIN GRADIENT ALGORITHM FOR ℓ1-REGULARIZED NONSMOOTH MINIMIZATION IN COMPRESSIVE SENSING
"... ar ..."
Effective Dynamic Voltage Scaling through Accurate Performance Modeling ∗
"... Keywords: Power-aware computing, dynamic voltage scaling, interval-based voltage scheduling, performance modeling, power-performance tradeoff. Dynamic voltage scaling (DVS) is widely recognized as an effective way to reduce high CPU power consumption. The technique trades CPU performance for power r ..."
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reduction and energy savings. As a result, there have been many proposals on how to effectively manage a DVS processor to minimize the CPU power consumption while keeping the performance degradation within an acceptable range. Most of these proposals use a simple performanceprediction model which assumes
1Sub-Nyquist Radar via Doppler Focusing
"... Abstract—We investigate the problem of a monostatic pulse-Doppler radar transceiver trying to detect targets, sparsely populated in the radar’s unambiguous time-frequency region. Several past works employ compressed sensing (CS) algorithms to this type of problem, but either do not address sample ra ..."
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rate sampling and digital processing, imposes no restrictions on the transmitter, and uses a CS dictionary with size which does not increase with increasing number of pulses P. Furthermore, in the presence of noise, Doppler focusing enjoys a signal-to-noise ratio (SNR) improvement which scales linearly
Nucleation, Growth, and Scaling in Slow Combustion
"... We study the nucleation and growth of flame fronts in slow combustion. This is modeled by a set of reaction-diffusion equations for the temperature field, coupled to a background of reactants and augmented by a term describing random temperature fluctuations for ignition. We establish connections b ..."
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where 1 1,2 are constants, A is the Arrhenius energy barrier, and Boltzmann's constant has been set to unity. Note that while the dynamics of the process is controlled by the activation term e A/T, the scale for energy is set by T3/2. We choose the same values for the constants as those used in ref
Paying to Save: Reducing Cost of Colocation Data Center via Rewards
"... Abstract—Power-hungry data centers face an urgent pressure on reducing the energy cost. The existing efforts, despite being numerous, have primarily centered around owner-operated data centers (e.g., Google), leaving another critical data center segment — colocation data center (e.g., Equinix) which ..."
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’ power management from unco-ordinated to coordinated, using financial reward as a lever. RECO pays (voluntarily participating) tenants for energy reduction such that the colocation operator’s overall cost is minimized. RECO incorporates the time-varying operation environment (e.g., cooling efficiency
Limits of Energy Saving for the Allocation of Data Center Resources to Networked Applications
"... Abstract-Energy related costs are becoming one of the largest contributors to the overall cost of operating a data center, whereas the degree of data center utilization continues to be very low. Energy-aware dynamic provision of resources based on the consolidation of existing application instances ..."
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speed scaling and powering down nodes. The goal of this paper is to develop a theoretical framework to analyze the limits of energy saving, and strategies to determine the right set of computing nodes on and off to minimize energy consumption while keeping the right level of service for networked
EXPERIMENTS IN TURBULENT SOAP-FILM FLOWS: MARANGONI SHOCKS, FRICTIONAL DRAG, AND ENERGY SPECTRA BY
"... We carry out unprecedented experimental measurements of the frictional drag in turbulent soap-film flows over smooth walls. These flows are effectively two-dimensional, and we are able to create soap-film flows with the two types of turbulent spectrum that are theoretically possible in two dimension ..."
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dimensions: the “enstrophy cascade, ” for which the spectral exponent α = 3, and the “inverse energy cascade, ” for which the spectral exponent α = 5/3. We find that the functional relation between the frictional drag f and the Reynolds number Re depends on the spectral exponent: where α = 3, f ∝ Re−1
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