3,915 research outputs found
A classical bounce: constraints and consequences
We perform a detailed investigation of the simplest possible cosmological
model in which a bounce can occur, namely that where the dynamics is led by a
simple massive scalar field in a general self-interacting potential and a
background spacetime with positively curved spatial sections. By means of a
phase space analysis, we give the conditions under which an initially
contracting phase can be followed by a bounce and an inflationary phase lasting
long enough (i.e., at least 60-70 e-folds) to suppress spatial curvature in
today's observable universe. We find that, quite generically, this realization
requires some amount of fine-tuning of the initial conditions. We study the
effect of this background evolution on scalar perturbations by propagating an
initial power-law power spectrum through the contracting phase, the bounce and
the inflationary phase. We find that it is drastically modified, both
spectrally (k-mode mixing) and in amplitude. It also acquires, at leading
order, an oscillatory component, which, once evolved through the radiation and
matter dominated eras, happens to be compatible with the WMAP data.Comment: Updated references, improved figure resolutio
A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The Case of IBM Blue Gene/Q
The complexity and cost of managing high-performance computing
infrastructures are on the rise. Automating management and repair through
predictive models to minimize human interventions is an attempt to increase
system availability and contain these costs. Building predictive models that
are accurate enough to be useful in automatic management cannot be based on
restricted log data from subsystems but requires a holistic approach to data
analysis from disparate sources. Here we provide a detailed multi-scale
characterization study based on four datasets reporting power consumption,
temperature, workload, and hardware/software events for an IBM Blue Gene/Q
installation. We show that the system runs a rich parallel workload, with low
correlation among its components in terms of temperature and power, but higher
correlation in terms of events. As expected, power and temperature correlate
strongly, while events display negative correlations with load and power. Power
and workload show moderate correlations, and only at the scale of components.
The aim of the study is a systematic, integrated characterization of the
computing infrastructure and discovery of correlation sources and levels to
serve as basis for future predictive modeling efforts.Comment: 12 pages, 7 Figure
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