Adaptive Partitioning for Large-Scale Dynamic Graphs

Abstract—In the last years, large-scale graph processing has gained increasing attention, with most recent systems placing particular emphasis on latency. One possible technique to improve runtime performance in a distributed graph processing system is to reduce network communication. The most notable way to achieve this goal is to partition the graph by minimizing the num-ber of edges that connect vertices assigned to different machines, while keeping the load balanced. However, real-world graphs are highly dynamic, with vertices and edges being constantly added and removed. Carefully updating the partitioning of the graph to reflect these changes is necessary to avoid the introduction of an extensive number of cut edges, which would gradually worsen computation performance. In this paper we show that performance degradation in dynamic graph processing systems can be avoided by adapting continuously the graph partitions as the graph changes. We present a novel highly scalable adaptive partitioning strategy, and show a number of refinements that make it work under the constraints of a large-scale distributed system. The partitioning strategy is based on iterative vertex migrations, relying only on local information. We have implemented the technique in a graph processing system, and we show through three real-world scenarios how adapting graph partitioning reduces execution time by over 50 % when compared to commonly used hash-partitioning. I

Photonic artificial muscles: From micro robots to tissue engineering

Light responsive shape-changing polymers are able to mimic the function of biological muscles accomplishing mechanical work in response to selected stimuli. A variety of manufacturing techniques and chemical processes can be employed to shape these materials to different length scales, from centimeter fibers and films to 3D printed micrometric objects trying to replicate biological functions and operations. Controlled deformations shown to mimick basic animal operations such as walking, swimming or grabbing objects, while also controlling the refractive index and the geometry of devices, opens up the potential to implement tunable optical properties. Another possibility is that of combining artificial polymers with cells or biological tissue (such as intact cardiac trabeculae) with the aim to improve tissue formation in vitro or to support the mechanical function of damaged biological muscles. Such versatility is afforded by chemistry. New customized liquid crystalline monomers are presented here that modulate material properties for different applications. The role of synthetic material composition is highlighted as we demonstrate how using apparently similar molecular formulations, that liquid crystalline polymers can be adapted to different technological and medical challenges

xDGP: A Dynamic Graph Processing System with Adaptive Partitioning

13 pagesMany real-world systems, such as social networks, rely on mining efficiently large graphs, with hundreds of millions of vertices and edges. This volume of information requires partitioning the graph across multiple nodes in a distributed system. This has a deep effect on performance, as traversing edges cut between partitions incurs a significant performance penalty due to the cost of communication. Thus, several systems in the literature have attempted to improve computational performance by enhancing graph partitioning, but they do not support another characteristic of real-world graphs: graphs are inherently dynamic, their topology evolves continuously, and subsequently the optimum partitioning also changes over time. In this work, we present the first system that dynamically repartitions massive graphs to adapt to structural changes. The system optimises graph partitioning to prevent performance degradation without using data replication. The system adopts an iterative vertex migration algorithm that relies on local information only, making complex coordination unnecessary. We show how the improvement in graph partitioning reduces execution time by over 50%, while adapting the partitioning to a large number of changes to the graph in three real-world scenarios

Free-form Light Actuators - Fabrication and Control of Actuation in Microscopic Scale

Liquid crystalline elastomers (LCEs) are smart materials capable of reversible shape-change in response to external stimuli, and have attracted researchers' attention in many fields. Most of the studies focused on macroscopic LCE structures (films, fibers) and their miniaturization is still in its infancy. Recently developed lithography techniques, e.g., mask exposure and replica molding, only allow for creating 2D structures on LCE thin films. Direct laser writing (DLW) opens access to truly 3D fabrication in the microscopic scale. However, controlling the actuation topology and dynamics at the same length scale remains a challenge. In this paper we report on a method to control the liquid crystal (LC) molecular alignment in the LCE microstructures of arbitrary three-dimensional shape. This was made possible by a combination of direct laser writing for both the LCE structures as well as for micrograting patterns inducing local LC alignment. Several types of grating patterns were used to introduce different LC alignments, which can be subsequently patterned into the LCE structures. This protocol allows one to obtain LCE microstructures with engineered alignments able to perform multiple opto-mechanical actuation, thus being capable of multiple functionalities. Applications can be foreseen in the fields of tunable photonics, micro-robotics, lab-on-chip technology and others

The impact of bilingualism on executive functions in children and adolescents: a systematic review based on the PRISMA method

Approximately half of the world's population is bilingual or multilingual. The bilingual advantage theory claims that the constant need to control both known languages, that are always active in the brain, to use the one suitable for each specific context improves cognitive functions and specifically executive functions. However, some authors do not agree on the bilingual effect, given the controversial results of studies on this topic. This systematic review aims to summarize the results of studies on the relationship between bilingualism and executive functions. The review was conducted according to PRISMA-statement through searches in the scientific database PsychINFO, PsycARTICLES, MEDLINE, and PUBMED. Studies included in this review had at least one bilingual and monolingual group, participants aged between 5 and 17 years, and at least one executive function measure. Studies on second language learners, multilingual people, and the clinical population were excluded. Fifty-three studies were included in the systematic review. Evidence supporting the bilingual effect seems to appear when assessing inhibition and cognitive flexibility, but to disappear when working memory is considered. The inconsistent results of the studies do not allow drawing definite conclusions on the bilingual effect. Further studies are needed; they should consider the role of some modulators (e.g., language history and context, methodological differences) on the observed results

An improved fault mitigation strategy for CUDA Fermi GPUs

High computation is a predominant requirement in many applications. In this field, Graphic Processing Units (GPUs) are more and more adopted. Low prices and high parallelism let GPUs be attractive, even in safety critical applications. Nonetheless, new methodologies must be studied and developed to increase the dependability of GPUs. This paper presents an improved fault mitigation strategy against permanent faults for CUDA Fermi GPUs. The proposed approach exploits the reverse engineering of the block scheduling policy in CUDA Fermi GPUs in order to minimize the fault mitigation timing overhead. The graceful performance degradation achieved by the proposed technique outperforms multithreaded CPU implementations and other fault mitigation strategies for CUDA GPU, even in presence of multiple permanent faults

Molecular Epidemiology of Canine Parvovirus, Europe

Canine parvovirus (CPV), which causes hemorrhagic enteritis in dogs, has 3 antigenic variants: types 2a, 2b, and 2c. Molecular method assessment of the distribution of the CPV variants in Europe showed that the new variant CPV-2c is widespread in Europe and that the viruses are distributed in different countries

The endocannabinoid 2-AG controls skeletal muscle cell differentiation via CB1 receptor-dependent inhibition of Kv7 channels.

Little is known of the involvement of endocannabinoids and cannabinoid receptors in skeletal muscle cell differentiation. We report that, due to changes in the expression of genes involved in its metabolism, the levels of the endocannabinoid 2-arachidonoylglycerol (2-AG) are decreased both during myotube formation in vitro from murine C2C12 myoblasts and during mouse muscle growth in vivo. The endocannabinoid, as well as the CB1 agonist arachidonoyl-2-chloroethylamide, prevent myotube formation in a manner antagonized by CB1 knockdown and by CB1 antagonists, which, per se, instead stimulate differentiation. Importantly, 2-AG also inhibits differentiation of primary human satellite cells. Muscle fascicles from CB1 knockout embryos contain more muscle fibers, and postnatal mice show muscle fibers of an increased diameter relative to wild-type littermates. Inhibition of Kv7.4 channel activity, which plays a permissive role in myogenesis and depends on phosphatidylinositol 4,5-bisphosphate (PIP2), underlies the effects of 2-AG. We find that CB1 stimulation reduces both total and Kv7.4-bound PIP2 levels in C2C12 cells and inhibits Kv7.4 currents in transfected CHO cells. We suggest that 2-AG is an endogenous repressor of myoblast differentiation via CB1-mediated inhibition of Kv7.4 channels

A meta-analysis of science education studies for students with intellectual and developmental disabilities (IDD)

Teaching science education has remained limited for students with intellectual and developmental disabilities (IDD), which, in turn, has resulted in an ongoing discrepancy between these students and their typically developing peers for decades. Although there is a growing body of research in effective teaching approaches aimed at overcoming this discrepancy, there is still a need to identify evidence-based practices for addressing this academic core content. The purpose of this meta-analysis was to (a) find out the skills taught in science education to students with IDD, (b) define the characteristics of instructional approaches or adaptations of instructional approaches used to teach science content and practices, (c) conduct visual and effect size analysis of science education studies meeting the Council for Exceptional Children (CEC) quality indicators (QIs; Cook et al., 2015), and (d) determine whether there are differences in effect sizes of science education studies meeting CEC QIs based on participant and intervention characteristics. Of 27 studies reviewed, 18 studies met all the CEC QIs. A meta-analysis of these 18 studies resulted in an overall medium effect size of 0.82 CI95 (0.76, 0.87). While all the moderator variables showed a medium effect size in participant characteristics, intervention characteristics showed differences in effect sizes for comprehension-based learning and peer and researcher-implemented interventions

A software-based self test of CUDA Fermi GPUs

Nowadays, Graphical Processing Units (GPUs) have become increasingly popular due to their high computational power and low prices. This makes them particularly suitable for high-performance computing applications, like data elaboration and financial computation. In these fields, high efficient test methodologies are mandatory. One of the most effective ways to detect and localize hardware faults in GPUs is a Software-Based-Self-Test methodology (SBST). In this paper a fully comprehensive SBST and fault localization methodology for GPUs is presented. This novel approach exploits different custom test strategies for each component inside the GPU architecture. Such strategies guarantee both permanent fault detection and accurate fault localization