34 research outputs found

    GLB: Lifeline-based Global Load Balancing library in X10

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    We present GLB, a programming model and an associated implementation that can handle a wide range of irregular paral- lel programming problems running over large-scale distributed systems. GLB is applicable both to problems that are easily load-balanced via static scheduling and to problems that are hard to statically load balance. GLB hides the intricate syn- chronizations (e.g., inter-node communication, initialization and startup, load balancing, termination and result collection) from the users. GLB internally uses a version of the lifeline graph based work-stealing algorithm proposed by Saraswat et al. Users of GLB are simply required to write several pieces of sequential code that comply with the GLB interface. GLB then schedules and orchestrates the parallel execution of the code correctly and efficiently at scale. We have applied GLB to two representative benchmarks: Betweenness Centrality (BC) and Unbalanced Tree Search (UTS). Among them, BC can be statically load-balanced whereas UTS cannot. In either case, GLB scales well-- achieving nearly linear speedup on different computer architectures (Power, Blue Gene/Q, and K) -- up to 16K cores

    Deep Teaching: Materials for Teaching Machine and Deep Learning

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    [EN] Machine learning (ML) is considered to be hard because it is relatively complicated in comparison to other topics of computer science. The reason is that machine learning is based heavily on mathematics and abstract concepts. This results in an entry barrier for students: Most students want to avoid such difficult topics in elective courses or self-study. In the project Deep.Teaching we address these issues: We motivate by selected applications and support courses as well as self-study by giving practical exercises for different topics in machine learning. The teaching material, provided as jupyter notebooks, consists of theoretical and programming sections. For didactical reasons, we designed programming exercises such that the students have to deeply understand the concepts and principles before they can start to implement a solution. We provide all necessary boilerplate code such that the students can primarily focus on the educational objectives of the exercises. We used different ways to give feedback for self-study: obscured solutions for mathematical results, software tests with assert statements, and graphical illustrations of sample solutions. All of the material is published under a permissive license. Developing jupyter notebooks collaboratively for educational purposes poses some problems. We address these issues and provide solutions/best practices.The project Deep.Teaching is funded by the German National Ministry of Education and Research (BMBF), project number 01IS17056.Herta, C.; Voigt, B.; Baumann, P.; Strohmenger, K.; Jansen, C.; Fischer, O.; Zhang, G.... (2019). Deep Teaching: Materials for Teaching Machine and Deep Learning. En HEAD'19. 5th International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 1153-1131. https://doi.org/10.4995/HEAD19.2019.9177OCS1153113

    Oxytocin Receptor Genotype Modulates Ventral Striatal Activity to Social Cues and Response to Stressful Life Events

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    Background Common variants in the oxytocin receptor gene (OXTR) have been shown to influence social and affective behavior and to moderate the effect of adverse experiences on risk for social-affective problems. However, the intermediate neurobiological mechanisms are not fully understood. Although human functional neuroimaging studies have reported that oxytocin effects on social behavior and emotional states are mediated by amygdala function, animal models indicate that oxytocin receptors in the ventral striatum (VS) modulate sensitivity to social reinforcers. This study aimed to comprehensively investigate OXTR-dependent brain mechanisms associated with social-affective problems. Methods In a sample of 1445 adolescents we tested the effect of 23-tagging single nucleotide polymorphisms across the OXTR region and stressful life events (SLEs) on functional magnetic resonance imaging blood oxygen level-dependent activity in the VS and amygdala to animated angry faces. Single nucleotide polymorphisms for which gene-wide significant effects on brain function were found were then carried forward to examine associations with social-affective problems. Results A gene-wide significant effect of rs237915 showed that adolescents with minor CC-genotype had significantly lower VS activity than CT/TT-carriers. Significant or nominally significant gene × environment effects on emotional problems (in girls) and peer problems (in boys) revealed a strong increase in clinical symptoms as a function of SLEs in CT/TT-carriers but not CC-homozygotes. However, in low-SLE environments, CC-homozygotes had more emotional problems (girls) and peer problems (boys). Moreover, among CC-homozygotes, reduced VS activity was related to more peer problems. Conclusions These findings suggest that a common OXTR-variant affects brain responsiveness to negative social cues and that in "risk- carriers" reduced sensitivity is simultaneously associated with more social-affective problems in "favorable environments" and greater resilience against stressful experiences. © 2014 Society of Biological Psychiatry

    Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

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    The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders