uBench: exposing the impact of CUDA block geometry in terms of performance

The choice of thread-block size and shape is one of the most important user decisions when a parallel problem is written for any CUDA architecture. The reason is that thread-block geometry has a significant impact on the global performance of the program. Unfortunately, the programmer has not enough information about the subtle interactions between this choice of parameters and the underlying hardware. This paper presents uBench, a complete suite of micro-benchmarks, in order to explore the impact on performance of (1) the thread-block geometry choice criteria, and (2) the GPU hardware resources and configurations. Each micro-benchmark has been designed to be as simple as possible to focus on a single effect derived from the hardware and thread-block parameter choice. As an example of the capabilities of this benchmark suite, this paper shows an experimental evaluation and comparison of Fermi and Kepler architectures. Our study reveals that, in spite of the new hardware details introduced by Kepler, the principles underlying the block geometry selection criteria are similar for both architectures.     

Computational and mathematical models meet heterogeneous computing

The Journal of Supercomputing -     

Assessment of chemical and microbiological parameters of indoor swimming pool atmosphere using multiple comparisons

The aim of this study was to evaluate the air quality of an indoor swimming pool, analyzing diurnal and seasonal variations in microbiological counts and chemical parameters. The results indicated that yeast and bacteria counts, as well as carbon dioxide (CO₂), nitrogen oxides (NO_x) and O₃ concentrations, showed significant diurnal difference. On the other hand, temperature, relative humidity (R.H.), yeast counts and concentrations of CO₂, particles, O₃, toluene, and benzene showed seasonal differences. In addition, the relationship between indoor and outdoor air and the degree of correlation between the different parameters have been calculated, suggesting that CO₂, fine particles and NO_x would have indoor origin due to the human activity and secondary reactions favored by the chemical and environmental conditions of the swimming pool; while O₃, benzene and toluene, would come from outside, mainly. The overall results indicated that indoor air quality (IAQ) in the swimming pool building was deficient by the high levels of CO₂ and microorganisms, low temperatures, and high R.H., because frequently the limits established by the legislation were exceeded. This fact could be due to the poor ventilation and the inadequate operation of heating, ventilation, and air‐conditioning systems.     

Cloud-based architecture for web applications with load forecasting mechanism: a use case on the e-learning services of a distant university

In cloud systems, a clear necessity emerges related to the use of efficient and scalable computing resources. For this, accurate predictions on the load of computing resources are a key. Thanks to these accurate predictions, reduced power consumption and enhanced revenue of the system can be achieved, since resources can be ready when users need them and shutdown when they are no longer needed. This work presents an architecture to manage web applications based on cloud computing, which combines both local and public cloud resources. This work also presents the algorithms needed to efficiently manage such architecture. Among them, a load forecasting algorithm has been developed based on Exponential Smoothing. An use case of the e-learning services of our University presenting the behaviour of our architecture has been evaluated through a series of simulations. Among the most remarkable results, power consumption is reduced by 32 % at the cost of 367.31 US$ a month compared with the current architecture.     

Modelling photovoltaic modules with neural networks using angle of incidence and clearness index

A neural network for modelling photovoltaic modules using angle of incidence and clearness index is proposed. Engineers require methods to estimate the output of a photovoltaic plant depending on meteorological conditions. Therefore, models for the grid inverter and the generator must be provided, and their outputs must be combined. The connection between both models is related to the maximum power point of the generator and how it is tracked by the inverter. That maximum power point under specific conditions of irradiance and module temperature is determined by the I–V curve of the module, which must be simulated under those conditions. Algebraic procedures were used to simulate the I–V curve. Recently, neural networks have been used for the same purpose. Previous methods only take into account the irradiance and the module temperature. The model proposed is based on neural networks, and it uses not only the irradiance and the module temperature but also the angle of incidence and the instantaneous clearness index as additional inputs. The normalised clearness replaces the standard clearness index because it allows the removal of the hourly trend found in this last index. This new model improves the results obtained with previous ones as it can distinguish amongst samples with the same solar irradiance and temperature values but with different angle of incidence and instantaneous clearness index. Results show that this model could be used to improve the accuracy of the tools used to forecast the output of photovoltaic plants. Copyright © 2014 John Wiley & Sons, Ltd.     

Apparent bidimensional critical temperature as a graphite surface homogeneity criterion

Nitrogen adsorption isotherms at 77.7 K, over graphites with different surface homogeneity, are analyzed. Three of the samples exhibited the transition from a fluid to a bidimensional solid before the monolayer was completed. The apparent bidimensional critical temperature, deduced from the Hillde Boer equation (applied to experimental isotherms), is proposed as a criterion for surface homogeneity. The calculated values range from 61 K for the most homogeneous surface to 36 K for the less homogeneous one. The estimated degrees of homogeneity are in agreement with previous experimental evidence and the surface characteristics of these samples.     

Acetone transformation into methyl isobutyl ketone over Pt/HMFI catalysts. IV. Effect of density and strength of the acidic sites

Acetone transformation into methyl isobutyl ketone (MIBK) was studied using a fixed-bed dynamic reactor at 160°C, 1 atm pressure and acetone/H₂ molar ratio=3. The reaction was carried out over Pt/HMFI bifunctional catalysts, with 0.30 wt% of platinum which was supported over three aluminosilicates (Si/Al ratio=40, 95 and 160) and a borosilicate (Si/B ratio=44) with similar dispersion. The results show that catalytic properties depend greatly on density and strength of the acidic sites of the catalysts. Moreover, the limiting step of the MIBK synthesis reaction (aldolization of two acetone molecules) is carried out over the acidic sites of the aluminosilicates, but not over those of the borosilicate, which considerably affects reaction selectivity. This revised version was published online in July 2006 with corrections to the Cover Date.     

Technological characterization of Lactobacillus isolates from traditional Manchego cheese for potential use as adjunct starter cultures

Thirty Lactobacillus isolates from artisanal Manchego cheeses, 10 belonging to Lactobacillus plantarum and 20 belonging to Lactobacillus paracasei subsp. paracasei, were examined for potential use as adjunct cultures. Isolates were screened for acidifying and amino-biogenic capacity, for proteolytic, lipolytic, autolytic and aminopeptidase activities, and for sensory characteristics in UHT coagulated milk. Most of the lactobacilli displayed high aminopeptidase and autolytic activities and low acidifying activity. Only one isolate was able to produce tyramine. When growing on milk 53.3% of the Lb. paracasei subsp. paracasei isolates were able to produce pleasant flavours. Strains PBL210 (Lb. plantarum) and PBL213 and PBL226 (Lb. paracasei subsp. paracasei) presented the best technological characteristics, and also were still viable and with unaltered properties after freeze-drying and storage for 12 months. For these reasons, these strains could be good candidates for inclusion as adjuncts in a starter culture to manufacture industrial Manchego cheese.