On the leakage-power modeling for optimal server operation

Leakage power consumption is a com- ponent of the total power consumption in data cen- ters that is not traditionally considered in the set- point temperature of the room. However, the effect of this power component, increased with temperature, can determine the savings associated with the careful management of the cooling system, as well as the re- liability of the system. The work presented in this paper detects the need of addressing leakage power in order to achieve substantial savings in the energy consumption of servers. In particular, our work shows that, by a careful detection and management of two working regions (low and high impact of thermal- dependent leakage), energy consumption of the data- center can be optimized by a reduction of the cooling budget

QCD equation of state at finite isospin density from the linear sigma model with quarks: The cold case

We use the two-flavor linear sigma model with quarks to study the phase structure of isospin asymmetric matter at zero temperature. The meson degrees of freedom provide the mean field chiral- and isospin-condensates on top of which we compute the effective potential accounting for constituent quark fluctuations at one-loop order. Using the renormalizability of the model, we absorb the ultraviolet divergences into suitable counter-terms that are added respecting the original structure of the theory. These counter-terms are determined from the stability conditions which require the effective potential to have minima in the condensates directions at the classical values, as well as the transition from the non-condensed to the condensed phase to be smooth as a function of the isospin chemical potential. We use the model to study the evolution of the condensates as well as the pressure, energy and isospin densities and the sound velocity as functions of the isospin chemical potential. The approach does a good average description up to isospin chemical potentials values not too large as compared to the vacuum pion mass.Comment: 11 pages and 7 figures. Expanded discussion, references and graphs added, conclusions unchange

Thermal analysis and modeling of embedded processors

This paper presents a complete modeling approach to analyze the thermal behavior of microprocessor-based systems. While most compact modeling approaches require a deep knowledge of the implementation details, our method defines a black box technique which can be applied to different target processors when this detailed information is unknown. The obtained results show high accuracy, applicability and can be easily automated. The proposed methodology has been used to study the impact of code transformations in the thermal behavior of the chip. Finally, the analysis of the thermal effect of the source code modifications can be included in a temperature-aware compiler which minimizes the total temperature of the chip, as well as the temperature gradients, according to these guidelines

Nanocomposite-forming solutions based on cassava starch and laponite: viscoelastic and rheological characterization

Nanocomposites-forming solutions (NFS) based on cassava starch and laponite were prepared and next characterized by means of dynamic oscillatory and steady shear rheological tests to evaluate their ability to be processed by knife coating. The effects of speed (rpm) and homogenization time on the laponite dispersion characteristics were first analyzed. Laponite dispersions were affected by both process parameters. High speed (rpm), i.e. 20,000 or 23,000 rpm for 30 min or prolonged homogenization time (10,000 rpm 6 speed agitation 6 23,000 rpm, for 60 min) led to high f-potential values, with laponite particles size <80 nm. With addition of laponite nanoparticles to cassava starch dispersion, an evident transition in NFS from liquid-like viscous to solid-like elastic behavior was observed. Rheological results indicated that laponite nanoparticles induced new interactions with starch chains allowing to obtain a network structure typical of a semi-rigid gel which shows some spread ability.São Paulo Research Foundation (FAPESP), the grant (2013/07914-8)

Enhancing Regression Models for Complex Systems using Evolutionary Techniques for Feature Engineering

Abstract This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer&apos;s expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data center

Interplay of computer simulations and x-ray absorption spectra in the study of the bromide hydration structure

X-ray absorption spectra (EXAFS and XANES) were generated from snapshots of a Monte Carlo (MC) simulation of a bromide ion aqueous solution and from model structures. The MC simulation relies on a recently developed and tested polarizable potential based on ab initio potential energy surfaces. A comparison with the experimental K-edge Br spectrum of a 0.3 M YBr3 aqueous solution was performed. XANES spectra are reproduced acceptably only if statistical fluctuations are included, which is performed in this work by using snapshots from computer simulation. As expected, single scattering BrO contributions are dominant in the case of the EXAFS region. Due to this fact, Br- in water is a good model system for studying the influence of the distribution of distances on the determination of structural parameters. Then, a parallel study of the data analysis procedure of the experimental EXAFS spectrum and those theoretically computed from the structures supplied by the MC simulation, was carried out. The shape of the distribution function and its asymmetry must be taken into account in a practical way to obtain a more accurate determination of the BrO first-shell distance. A further refinement consists in using the computer simulation to extrapolate the BrO distance from the experimental EXAFS spectrum. In this way, a BrO distance of 3.44±0.07 Å and a coordination number of 6±0.5 were determine

3D Thermal-Aware Floorplanner for Many-Core Single-Chip Systems

Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. In this paper, we propose a thermal-driven 3D floorplanner. Our contributions include: (1) a novel multi-objective formulation to consider the thermal and performance constraints in the optimization approach; (2) an efficient Mixed Integer Linear Programming (MILP) representation of the floorplanning model; and (3) a smooth integration of the MILP model with an accurate thermal modelling of the architecture. The experimental work is conducted for two realistic many-core single-chip architectures: an homogeneous system resembling Intel’s SCC, and an improved heterogeneous setup. The results show promising improvements of the mean, peak temperature and the thermal gradient, with a reduced overhead in the wire length of the system