Modeling the input history of programs for improved instruction-memory performance

When a program is loaded into memory for execution, the relative position of its basic blocks is crucial, since loading basic blocks that are unlikely to be executed first places them high in the instruction-memory hierarchy only to be dislodged as the execution goes on. In this paper we study the use of Bayesian networks as models of the input history of a program. The main point is the creation of a probabilistic model that persists as the program is run on different inputs and at each new input refines its own parameters in order to reflect the program's input history more accurately. As the model is thus tuned, it causes basic blocks to be reordered so that, upon arrival of the next input for execution, loading the basic blocks into memory automatically takes into account the input history of the program. We report on extensive experiments, whose results demonstrate the efficacy of the overall approach in progressively lowering the execution times of a program on identical inputs placed randomly in a sequence of varied inputs. We provide results on selected SPEC CINT2000 programs and also evaluate our approach as compared to the gcc level-3 optimization and to Pettis-Hansen reordering

Nonlinear modeling of the cyclic response of RC columns

Cyclic load reversals (like those induced by earthquakes) result in accelerated bond degradation, leading to significant bar slippage. The bond-slip mechanism is reported to be one of the most common causes of damage and even collapse of existing RC structures subjected to earthquake loading. RC structures with plain reinforcing bars, designed and built prior to the enforcement of the modern seismic-oriented design philosophies, are particularly sensitive to bond degradation. However, perfect bond conditions are typically assumed in the numerical analysis of RC structures. This paper describes the numerical modeling of the cyclic response of two RC columns, one built with deformed bars and the other with plain bars and structural detailing similar to that typically adopted in pre-1970s structures. For each column, different modeling strategies to simulate the column response were tested. Models were built using the OpenSees and the SeismoStruct platforms, and calibrated with the available tests results. Within each platform, different types of nonlinear elements were used to represent the columns. Bond-slip effects were included in the OpenSees models resorting to a simple modeling strategy. The models and the parameters adopted are presented and discussed. Comparison is established between the most relevant experimental results and the corresponding results provided by the numerical models. Conclusions are drawn about the capacity of the tested models to simulate the columns response and about the influence of considering or not considering the effects of bars slippage

Boletim agrometeorológico: ano agrícola 1976-77.

bitstream/item/43277/1/1976-77.pd

Lie Algebroid Yang Mills with Matter Fields

Lie algebroid Yang-Mills theories are a generalization of Yang-Mills gauge theories, replacing the structural Lie algebra by a Lie algebroid E. In this note we relax the conditions on the fiber metric of E for gauge invariance of the action functional. Coupling to scalar fields requires possibly nonlinear representations of Lie algebroids. In all cases, gauge invariance is seen to lead to a condition of covariant constancy on the respective fiber metric in question with respect to an appropriate Lie algebroid connection. The presentation is kept in part explicit so as to be accessible also to a less mathematically oriented audience.Comment: 24 pages, accepted for publication in J. Geom. Phy

Structural and optical properties of europium doped zirconia single crystals fibers grown by laser floating zone

Yttria stabilized zirconia single crystal fibers doped with europium ions were developed envisaging optical applications. The laser floating zone technique was used in order to grow millimetric high quality single crystal fibers. The as-grown fibers are completely transparent and inclusion free, exhibiting a cubic structure. Under ultraviolet (UV) excitation, a broad emission band appears at 551 nm. The europium doped fibers are translucent with a tetragonal structure and exhibit an intense red emission at room temperature under UV excitation. The fingerprint transition lines between the 5D0 and 7FJ(0–4) multiplets of the Eu3+ ions are observed with the main emission line at ∼ 606 nm due to 5D0→7F2 transition. Photoluminescence excitation and wavelength dependent the photoluminescence spectra confirm the existence of different Eu3+ optical centers. © 2011 American Institute of PhysicsFCT-PTDC/CTM/66195/2006FCT-SFRH/BD/45774/200

An infrared diagnostic for magnetism in hot stars

Magnetospheric observational proxies are used for indirect detection of magnetic fields in hot stars in the X-ray, UV, optical, and radio wavelength ranges. To determine the viability of infrared (IR) hydrogen recombination lines as a magnetic diagnostic for these stars, we have obtained low-resolution (R~1200), near-IR spectra of the known magnetic B2V stars HR 5907 and HR 7355, taken with the Ohio State Infrared Imager/Spectrometer (OSIRIS) attached to the 4.1m Southern Astrophysical Research (SOAR) Telescope. Both stars show definite variable emission features in IR hydrogen lines of the Brackett series, with similar properties as those found in optical spectra, including the derived location of the detected magnetospheric plasma. These features also have the added advantage of a lowered contribution of stellar flux at these wavelengths, making circumstellar material more easily detectable. IR diagnostics will be useful for the future study of magnetic hot stars, to detect and analyze lower-density environments, and to detect magnetic candidates in areas obscured from UV and optical observations, increasing the number of known magnetic stars to determine basic formation properties and investigate the origin of their magnetic fields.Comment: 4 pages, accepted for publication in A&

Modified electrodes for electrochemical reduction of carbon dioxide

The efforts to constrain greenhouse gas emissions and concerns over security of fossil fuels have led to increased attention for renewable energy for the past decade. Renewable energy is one of the key solutions to the actual energy challenges. Omnidea in collaboration with Research Institutes is developing a technology based upon a regenerative energy storage cycle that could be a contribution to a low-carbon energy future. In this cycle the recharge system, which is composed of an electrochemical cell, converts CO2 into fuel (hydrocarbons and hydrogen) using an external source of power (e.g. solar power). The discharge system produces electric energy when hydrocarbons and oxygen from the recharge system are directly supplied to a Solid Oxide Fuel Cell (SOFC). Currently state of the art systems for direct electrochemical reduction of CO2 exhibit low current densities and or low Faradaic efficiencies. Thus considerable research activity is still needed to develop electrodes with a performance suitable for an industrial application. This paper describes the progress to date and the work carried out with the aim of achieving this goal. It addresses particularly the modification of electrodes for electrochemical conversion of CO2 and reports voltammetric studies as a tool for screening and optimizing electrodes for CO2 conversio