A multi-GPU algorithm for large-scale neuronal networks

Large-scale simulations of parts of the brain using detailed neuronal models to improve our understanding of brain functions are becoming a reality with the usage of supercomputers and large clusters. However, the high acquisition and maintenance cost of these computers, including the physical space, air conditioning, and electrical power, limits the number of simulations of this kind that scientists can perform. Modern commodity graphical cards, based on the CUDA platform, contain graphical processing units (GPUs) composed of hundreds of processors that can simultaneously execute thousands of threads and thus constitute a low-cost solution for many high-performance computing applications. In this work, we present a CUDA algorithm that enables the execution, on multiple GPUs, of simulations of large-scale networks composed of biologically realistic Hodgkin-Huxley neurons. The algorithm represents each neuron as a CUDA thread, which solves the set of coupled differential equations that model each neuron. Communication among neurons located in different GPUs is coordinated by the CPU. We obtained speedups of 40 for the simulation of 200k neurons that received random external input and speedups of 9 for a network with 200k neurons and 20M neuronal connections, in a single computer with two graphic boards with two GPUs each, when compared with a modern quad-core CPU. Copyright (C) 2010 John Wiley & Sons, Ltd.

Influence of multi-scale landscape structure on the occurrence of carnivorous mammals in a human-modified savanna, Brazil

So Paulo is the most developed state in Brazil and contains few fragments of native ecosystems, generally surrounded by intensive agriculture lands. Despite this, some areas still shelter large native animals. We aimed at understanding how medium and large carnivores use a mosaic landscape of forest/savanna and agroecosystems, and how the species respond to different landscape parameters (percentage of landcover and edge density), in a multi-scale perspective. The response variables were: species richness, carnivore frequency and frequency for the three most recorded species (Puma concolor, Chrysocyon brachyurus and Leopardus pardalis). We compared 11 competing models using Akaike`s information criterion (AIC) and assessed model support using weight of AIC. Concurrent models were combinations of landcover types (native vegetation, ""cerrado"" formations, ""cerrado"" and eucalypt plantation), landscape feature (percentage of landcover and edge density) and spatial scale. Herein, spatial scale refers to the radius around a sampling point defining a circular landscape. The scales analyzed were 250 (fine), 1,000 (medium) and 2,000 m (coarse). The shape of curves for response variables (linear, exponential and power) was also assessed. Our results indicate that species with high mobility, P. concolor and C. brachyurus, were best explained by edge density of the native vegetation at a coarse scale (2,000 m). The relationship between P. concolor and C. brachyurus frequency had a negative power-shaped response to explanatory variables. This general trend was also observed for species richness and carnivore frequency. Species richness and P. concolor frequency were also well explained by a second concurrent model: edge density of cerrado at the fine (250 m) scale. A different response was recorded for L. pardalis, as the frequency was best explained for the amount of cerrado at the fine (250 m) scale. The curve of response was linearly positive. The contrasting results (P. concolor and C. brachyurus vs L. pardalis) may be due to the much higher mobility of the two first species, in comparison with the third. Still, L. pardalis requires habitat with higher quality when compared with other two species. This study highlights the importance of considering multiple spatial scales when evaluating species responses to different habitats. An important and new finding was the prevalence of edge density over the habitat extension to explain overall carnivore distribution, a key information for planning and management of protected areas.

Ciprofibrate quantification in human plasma by high-performance liquid chromatography coupled with electrospray tandem mass spectrometry for pharmacokinetic studies

A rapid, sensitive and specific method for quantifying ciprofibrate in human plasma using bezafibrate as the internal standard (IS) is described. The sample was acidified prior extraction with formic acid (88%). The analyte and the IS were extracted from plasma by liquid-liquid extraction using an organic solvent (diethyl ether/dichloromethane 70/30 (v/v)). The extracts were analyzed by high performance liquid chromatography coupled with electrospray tandem mass spectrometry (HPLC-MS/MS). Chromatography was performed using Genesis C18 4 mu m analytical column (4.6 x 150 mm i.d.) and a mobile phase consisting of acetonitrile/water (70/30, v/v) and 1 mM acetic acid. The method had a chromatographic run time of 3.4 min and a linear calibration curve over the range 0.1-60 mu g/mL (r > 0.99). The limit of quantification was 0.1 mu g/mL. The intra- and interday accuracy and precision values of the assay were less than 13.5%. The stability tests indicated no significant degradation. The recovery of ciprofibrate was 81.2%, 73.3% and 76.2% for the 0.3, 5.0 and 48.0 ng/mL standard concentrations, respectively. For ciprofibrate, the optimized parameters of the declustering potential, collision energy and collision exit potential were -51 V, -16 eV and -5 V, respectively. The method was also validated without the use of the internal standard. This HPLC-MS/MS procedure was used to assess the bioequivalence of two ciprofibrate 100 mg tablet formulations in healthy volunteers of both sexes. The following pharmacokinetic parameters were obtained from the ciprofibrate plasma concentration vs. time curves: AUC(last), AUC(0-168 h), C(max) and T(max). The geometric mean with corresponding 90% confidence interval (CI) for test/reference percent ratios were 93.80% (90% CI = 88.16-99.79%) for C(max), 98.31% (90% CI = 94.91-101.83%) for AUC(last) and 97.67% (90% CI = 94.45-101.01%) for AUC(0-168 h). Since the 90% Cl for AUC(last), AUC(0-168 h) and C(max) ratios were within the 80-125% interval proposed by the US FDA, it was concluded that ciprofibrate (Lipless (R) 100 mg tablet) formulation manufactured by Biolab Sanus Farmaceutica Ltda. is bioequivalent to the Oroxadin (R) (100 mg tablet) formulation for both the rate and the extent of absorption. (C) 2011 Published by Elsevier B.V.

Grid job scheduling using Route with Genetic Algorithm support

In 2006 the Route load balancing algorithm was proposed and compared to other techniques aiming at optimizing the process allocation in grid environments. This algorithm schedules tasks of parallel applications considering computer neighborhoods (where the distance is defined by the network latency). Route presents good results for large environments, although there are cases where neighbors do not have an enough computational capacity nor communication system capable of serving the application. In those situations the Route migrates tasks until they stabilize in a grid area with enough resources. This migration may take long time what reduces the overall performance. In order to improve such stabilization time, this paper proposes RouteGA (Route with Genetic Algorithm support) which considers historical information on parallel application behavior and also the computer capacities and load to optimize the scheduling. This information is extracted by using monitors and summarized in a knowledge base used to quantify the occupation of tasks. Afterwards, such information is used to parameterize a genetic algorithm responsible for optimizing the task allocation. Results confirm that RouteGA outperforms the load balancing carried out by the original Route, which had previously outperformed others scheduling algorithms from literature.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

Evaluation of monolithic columns for determination of formaldehyde and acetaldehyde in sugar cane spirits by High-Performance Liquid Chromatography

High-Performance Liquid Chromatography (HPLC) conditions are described for separation of 2,4-dinitrophenylhydrazone (2,4-DNPH) derivatives of carbonyl compounds in a 10 cm long C-18 reversed phase monolithic column. Using a linear gradient from 40 to 77% acetonitrile (acetonitrile-water system), the separation was achieved in about 10 min-a time significantly shorter than that obtained with a packed particles column. The method was applied for determination of formaldehyde and acetaldehyde in Brazilian sugar cane spirits. The linear dynamic range was between 30 and 600 mu g L-1, and the detection limits were 8 and 4 mu g L-1 for formaldehyde and acetaldehyde, respectively.