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.

A large-scale synthesis of enantiomerically pure gamma-hydroxy-organochalcogenides

Enantiomerically pure (R)- and (S)-gamma-hydroxy-organochalcogenides are prepared using poly-[R]-3-hydroxybutanoate (PHB) as the starting material. (C) 2009 Elsevier Ltd. All rights reserved.

Now What!?! Exploring the Next Steps for Large-scale Library Assessment Projects

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

European resarch school on large scale solar thermal - SHINE

The Solar HeatIntegration NEtwork (SHINE) is a European research school in which 13 PhDstudents in solar thermal technologies are funded by the EU Marie-Curie program.It has five PhD course modules as well as workshops and seminars dedicated to PhDstudents both within the project as well as outside of it. The SHINE researchactivities focus on large solar heating systems and new applications: ondistrict heating, industrial processes and new storage systems. The scope ofthis paper is on systems for district heating for which there are five PhDstudents, three at universities and two at companies. The PhD students allstarted during the early part of 2014 and their initial work has concentratedon literature studies and on setting up models and data collection to be usedfor validation purposes. The PhD students will complete their studies in2017-18.

Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease

Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 (hazard ratio [HR] per standard deviation [SD] increment = 0.77, P-value<0.001), lysophosphatidylcholine 18∶2 (HR = 0.81, P-value<0.001), monoglyceride 18∶2 (MG 18∶2; HR = 1.18, P-value = 0.011) and sphingomyelin 28∶1 (HR = 0.85, P-value = 0.015)]. Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors (C-statistic: 0.76 vs. 0.75; NRI: 9.2%). MG 18∶2 was associated with CHD independently of triglycerides. Lysophosphatidylcholines were negatively associated with body mass index, C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2. MG 18∶2 showed an enrichment (P-value = 0.002) of significant associations with CHD-associated SNPs (P-value = 1.2×10-7 for association with rs964184 in the ZNF259/APOA5 region) and a weak, but positive causal effect (odds ratio = 1.05 per SD increment in MG 18∶2, P-value = 0.05) on CHD, as suggested by Mendelian randomization analysis. In conclusion, we identified four lipid-related metabolites with evidence for clinical utility, as well as a causal role in CHD development.

Software Tools For Large Scale Interactive Hydrodynamic Modeling

Running hydrodynamic models interactively allows both visual exploration and change of model state during simulation. One of the main characteristics of an interactive model is that it should provide immediate feedback to the user, for example respond to changes in model state or view settings. For this reason, such features are usually only available for models with a relatively small number of computational cells, which are used mainly for demonstration and educational purposes. It would be useful if interactive modeling would also work for models typically used in consultancy projects involving large scale simulations. This results in a number of technical challenges related to the combination of the model itself and the visualisation tools (scalability, implementation of an appropriate API for control and access to the internal state). While model parallelisation is increasingly addressed by the environmental modeling community, little effort has been spent on developing a high-performance interactive environment. What can we learn from other high-end visualisation domains such as 3D animation, gaming, virtual globes (Autodesk 3ds Max, Second Life, Google Earth) that also focus on efficient interaction with 3D environments? In these domains high efficiency is usually achieved by the use of computer graphics algorithms such as surface simplification depending on current view, distance to objects, and efficient caching of the aggregated representation of object meshes. We investigate how these algorithms can be re-used in the context of interactive hydrodynamic modeling without significant changes to the model code and allowing model operation on both multi-core CPU personal computers and high-performance computer clusters.

Large scale laboratory cultures of Ankistrodesmus gracilis (Reisch) Korsikov (Chlorophyta) and Diaphanosoma biergei Korinek, 1981 (Cladocera)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Performance and economic indicators of a large scale fish farming in Mato Grosso, Brazil

Performance and economic indicators of a large scale fish farm that produces round fish, located in Mato Grosso State, Brazil, were evaluated. The 130.8 ha-water surface area was distributed in 30 ponds. Average total production costs and the following economic indicators were calculated: gross income (GI), gross margin (GM), gross margin index (GMI), profitability index (PI) and profit (P) for the farm as a whole and for ten ponds individually. Production performance indicators were also obtained, such as: production cycle (PC), apparent feed conversion (FC), average biomass storage (ABS), survival index (SI) and final average weight (FAW). The average costs to produce an average 2.971 kg.ha-1 per year were: R$ 2.43, R$ 0.72 and R$ 3.15 as average variable, fixed and total costs, respectively. Gross margin and profit per year per hectare of water surface were R$ 2,316.91 and R$ 180.98, respectively. The individual evaluation of the ponds showed that the best pond performance was obtained for PI 38%, FC 1.7, ABS 0.980 kg.m-2, TS 56%, FAW 1.873 kg with PC of 12.3 months. The worst PI was obtained for the pond that displayed losses of 138%, FC 2.6, ABS 0.110 kg.m-2, SI 16% and FAW 1.811 kg. However, large scale production of round-fish in farms is economically feasible. The studied farm displays favorable conditions to improve performance and economic indicators, but it is necessary to reproduce the breeding techniques and performance indicators achieved in few ponds to the entire farm.

A novel system for large-scale gene expression analysis: bacterial colonies array

In the present work, we report the use of bacterial colonies to optimize macroarray technique. The devised system is significantly cheaper than other methods available to detect large-scale differential gene expression. Recombinant Escherichia coli clones containing plasmid-encoded copies of 4,608 individual expressed sequence tag (ESTs) were robotically spotted onto nylon membranes that were incubated for 6 and 12 h to allow the bacteria to grow and, consequently, amplify the cloned ESTs. The membranes were then hybridized with a beta-lactamase gene specific probe from the recombinant plasmid and, subsequently, phosphorimaged to quantify the microbial cells. Variance analysis demonstrated that the spot hybridization signal intensity was similar for 3,954 ESTs (85.8%) after 6 h of bacterial growth. Membranes spotted with bacteria colonies grown for 12 h had 4,017 ESTs (87.2%) with comparable signal intensity but the signal to noise ratio was fivefold higher. Taken together, the results of this study indicate that it is possible to investigate large-scale gene expression using macroarrays based on bacterial colonies grown for 6 h onto membranes.

Large-scale transcriptome analyses reveal new genetic marker candidates of head, neck, and thyroid cancer

A detailed genome mapping analysis of 213,636 expressed sequence tags (EST) derived from nontumor and tumor tissues of the oral cavity, larynx, pharynx, and thyroid was done. Transcripts matching known human genes were identified; potential new splice variants were flagged and subjected to manual curation, pointing to 788 putatively new alternative splicing isoforms, the majority (75%) being insertion events. A subset of 34 new splicing isoforms (5% of 788 events) was selected and 23 (68%) were confirmed by reverse transcription-PCR and DNA sequencing. Putative new genes were revealed, including six transcripts mapped to well-studied chromosomes such as 22, as well as transcripts that mapped to 253 intergenic regions. In addition, 2,251 noncoding intronic RNAs, eventually involved in transcriptional regulation, were found. A set of 250 candidate markers for loss of heterozygosis or gene amplification was selected by identifying transcripts that mapped to genomic regions previously known to be frequently amplified or deleted in head, neck, and thyroid tumors. Three of these markers were evaluated by quantitative reverse transcription-PCR in an independent set of individual samples. Along with detailed clinical data about tumor origin, the information reported here is now publicly available on a dedicated Web site as a resource for further biological investigation. This first in silico reconstruction of the head, neck, and thyroid transcriptomes points to a wealth of new candidate markers that can be used for future studies on the molecular basis of these tumors. Similar analysis is warranted for a number of other tumors for which large EST data sets are available.

Interior point method for long-term generation scheduling of large-scale hydrothermal systems

This paper presents an interior point method for the long-term generation scheduling of large-scale hydrothermal systems. The problem is formulated as a nonlinear programming one due to the nonlinear representation of hydropower production and thermal fuel cost functions. Sparsity exploitation techniques and an heuristic procedure for computing the interior point method search directions have been developed. Numerical tests in case studies with systems of different dimensions and inflow scenarios have been carried out in order to evaluate the proposed method. Three systems were tested, with the largest being the Brazilian hydropower system with 74 hydro plants distributed in several cascades. Results show that the proposed method is an efficient and robust tool for solving the long-term generation scheduling problem.

Are large-scale distributional shifts of the blue-winged macaw (Primolius maracana) related to climate change?

Aim To evaluate whether observed geographical shifts in the distribution of the blue-winged macaw (Primolius maracana) are related to ongoing processes of global climate change. This species is vulnerable to extinction and has shown striking range retractions in recent decades, withdrawing broadly from southern portions of its historical distribution. Its range reduction has generally been attributed to the effects of habitat loss; however, as this species has also disappeared from large forested areas, consideration of other factors that may act in concert is merited.Location Historical distribution of the blue-winged macaw in Brazil, eastern Paraguay and northern Argentina.Methods We used a correlative approach to test a hypothesis of causation of observed shifts by reduction of habitable areas mediated by climate change. We developed models of the ecological niche requirements of the blue-winged macaw, based on point-occurrence data and climate scenarios for pre-1950 and post-1950 periods, and tested model predictivity for anticipating geographical distributions within time periods. Then we projected each model to the other time period and compared distributions predicted under both climate scenarios to assess shifts of habitable areas across decades and to evaluate an explanation for observed range retractions.Results Differences between predicted distributions of the blue-winged macaw over the twentieth century were, in general, minor and no change in suitability of landscapes was predicted across large areas of the species' original range in different time periods. No tendency towards range retraction in the south was predicted, rather conditions in the southern part of the species' range tended to show improvement for the species.Main conclusions Our test permitted elimination of climate change as a likely explanation for the observed shifts in the distribution of the blue-winged macaw, and points rather to other causal explanations (e.g. changing regional land use, emerging diseases).