A Brief Study of Open Source Graph Databases

With the proliferation of large irregular sparse relational datasets, new storage and analysis platforms have arisen to fill gaps in performance and capability left by conventional approaches built on traditional database technologies and query languages. Many of these platforms apply graph structures and analysis techniques to enable users to ingest, update, query and compute on the topological structure of these relationships represented as set(s) of edges between set(s) of vertices. To store and process Facebook-scale datasets, they must be able to support data sources with billions of edges, update rates of millions of updates per second, and complex analysis kernels. These platforms must provide intuitive interfaces that enable graph experts and novice programmers to write implementations of common graph algorithms. In this paper, we explore a variety of graph analysis and storage platforms. We compare their capabil- ities, interfaces, and performance by implementing and computing a set of real-world graph algorithms on synthetic graphs with up to 256 million edges. In the spirit of full disclosure, several authors are affiliated with the development of STINGER.Comment: WSSSPE13, 4 Pages, 18 Pages with Appendix, 25 figure

Excitation lines and the breakdown of Stokes-Einstein relations in supercooled liquids

By applying the concept of dynamical facilitation and analyzing the excitation lines that result from this facilitation, we investigate the origin of decoupling of transport coefficients in supercooled liquids. We illustrate our approach with two classes of models. One depicts diffusion in a strong glass former, and the other in a fragile glass former. At low temperatures, both models exhibit violation of the Stokes-Einstein relation, $D\sim\tau^{-1}$, where $D$ is the self diffusion constant and $\tau$ is the structural relaxation time. In the strong case, the violation is sensitive to dimensionality $d$, going as $D\sim\tau^{-2/3}$ for $d=1$, and as $D\sim \tau^{-0.95}$ for $d=3$. In the fragile case, however, we argue that dimensionality dependence is weak, and show that for $d=1$, $D \sim \tau^{-0.73}$. This scaling for the fragile case compares favorably with the results of a recent experimental study for a three-dimensional fragile glass former.Comment: 7 pages, 7 figures, submitted to Phys. Rev.

The nature of slow dynamics in a minimal model of frustration-limited domains

We present simulation results for the dynamics of a schematic model based on the frustration-limited domain picture of glass-forming liquids. These results are compared with approximate theoretical predictions analogous to those commonly used for supercooled liquid dynamics. Although model relaxation times increase by several orders of magnitude in a non-Arrhenius manner as a microphase separation transition is approached, the slow relaxation is in many ways dissimilar to that of a liquid. In particular, structural relaxation is nearly exponential in time at each wave vector, indicating that the mode coupling effects dominating liquid relaxation are comparatively weak within this model. Relaxation properties of the model are instead well reproduced by the simplest dynamical extension of a static Hartree approximation. This approach is qualitatively accurate even for temperatures at which the mode coupling approximation predicts loss of ergodicity. These results suggest that the thermodynamically disordered phase of such a minimal model poorly caricatures the slow dynamics of a liquid near its glass transition

Irreversible reorganization in a supercooled liquid originates from localised soft modes

The transition of a fluid to a rigid glass upon cooling is a common route of transformation from liquid to solid that embodies the most poorly understood features of both phases1,2,3. From the liquid perspective, the puzzle is to understand stress relaxation in the disordered state. From the perspective of solids, the challenge is to extend our description of structure and its mechanical consequences to materials without long range order. Using computer simulations, we show that the localized low frequency normal modes of a configuration in a supercooled liquid are causally correlated to the irreversible structural reorganization of the particles within that configuration. We also demonstrate that the spatial distribution of these soft local modes can persist in spite of significant particle reorganization. The consequence of these two results is that it is now feasible to construct a theory of relaxation length scales in glass-forming liquids without recourse to dynamics and to explicitly relate molecular properties to their collective relaxation.Comment: Published online: 20 July 2008 | doi:10.1038/nphys1025 Available from http://www.nature.com/nphys/journal/v4/n9/abs/nphys1025.htm

JAK/STAT-1 Signaling Is Required for Reserve Intestinal Stem Cell Activation during Intestinal Regeneration Following Acute Inflammation

Summary The intestinal epithelium serves as an essential barrier to the outside world and is maintained by functionally distinct populations of rapidly cycling intestinal stem cells (CBC ISCs) and slowly cycling, reserve ISCs (r-ISCs). Because disruptions in the epithelial barrier can result from pathological activation of the immune system, we sought to investigate the impact of inflammation on ISC behavior during the regenerative response. In a murine model of αCD3 antibody-induced small-intestinal inflammation, r-ISCs proved highly resistant to injury, while CBC ISCs underwent apoptosis. Moreover, r-ISCs were induced to proliferate and functionally contribute to intestinal regeneration. Further analysis revealed that the inflammatory cytokines interferon gamma and tumor necrosis factor alpha led to r-ISC activation in enteroid culture, which could be blocked by the JAK/STAT inhibitor, tofacitinib. These results highlight an important role for r-ISCs in response to acute intestinal inflammation and show that JAK/STAT-1 signaling is required for the r-ISC regenerative response

Exploring the Design Space of Static and Incremental Graph Connectivity Algorithms on GPUs

Connected components and spanning forest are fundamental graph algorithms due to their use in many important applications, such as graph clustering and image segmentation. GPUs are an ideal platform for graph algorithms due to their high peak performance and memory bandwidth. While there exist several GPU connectivity algorithms in the literature, many design choices have not yet been explored. In this paper, we explore various design choices in GPU connectivity algorithms, including sampling, linking, and tree compression, for both the static as well as the incremental setting. Our various design choices lead to over 300 new GPU implementations of connectivity, many of which outperform state-of-the-art. We present an experimental evaluation, and show that we achieve an average speedup of 2.47x speedup over existing static algorithms. In the incremental setting, we achieve a throughput of up to 48.23 billion edges per second. Compared to state-of-the-art CPU implementations on a 72-core machine, we achieve a speedup of 8.26--14.51x for static connectivity and 1.85--13.36x for incremental connectivity using a Tesla V100 GPU

Bimodal crystallization at polymer-fullerene interfaces

The growth-kinetics of [6,6]-phenyl C61-butyric acid methyl ester (PCBM) crystals, on two different length-scales, is shown to be controlled by the thickness of the polymer layer within a PCBM-polymer bilayer. Using a model amorphous polymer we present evidence, from in situ optical microscopy and grazing-incidence X-ray diffraction (GIXD), that an increased growth-rate of nanoscale crystals impedes the growth of micron-sized, needle-like PCBM crystals. A combination of neutron reflectivity and GIXD measurements, also allows us to observe the establishment of a liquid-liquid equilibrium composition-profile between the PCBM layer and a polymer-rich layer, before crystallization occurs. While the interfacial composition-profile is independent of polymer-film-thickness, the growth-rate of nanoscale PCBM crystals is significantly larger for thinner polymer films. A similar thickness-dependent behavior is observed for different molecular weights of entangled polymer. We suggest that the behavior may be related to enhanced local-polymer-chain-mobility in nanocomposite thin-films

The role of war in deep transitions: exploring mechanisms, imprints and rules in sociotechnical systems

This paper explores in what ways the two world wars influenced the development of sociotechnical systems underpinning the culmination of the first deep transition. The role of war is an underexplored aspect in both the Techno-Economic Paradigms (TEP) approach and the Multi-level perspective (MLP) which form the two key conceptual building blocks of the Deep Transitions (DT) framework. Thus, we develop a conceptual approach tailored to this particular topic which integrates accounts of total war and mechanisms of war from historical studies and imprinting from organisational studies with the DT framework’s attention towards rules and meta-rules. We explore in what ways the three sociotechnical systems of energy, food, and transport were affected by the emergence of new demand pressures and logistical challenges during conditions of total war; how war impacted the directionality of sociotechnical systems; the extent to which new national and international policy capacities emerged during wartime in the energy, food, and transport systems; and the extent to which these systems were influenced by cooperation and shared sacrifice under wartime conditions. We then explore what lasting changes were influenced by the two wars in the energy, food, and transport systems across the transatlantic zone. This paper seeks to open up a hitherto neglected area in analysis on sociotechnical transitions and we discuss the importance of further research that is attentive towards entanglements of warfare and the military particularly in the field of sustainability transitions

Analyzing hybrid architectures for massively parallel graph analysis

The quantity of rich, semi-structured data generated by sensor networks, scientific simulation, business activity, and the Internet grows daily. The objective of this research is to investigate architectural requirements for emerging applications in massive graph analysis. Using emerging hybrid systems, we will map applications to architectures and close the loop between software and hardware design in this application space. Parallel algorithms and specialized machine architectures are necessary to handle the immense size and rate of change of today's graph data. To highlight the impact of this work, we describe a number of relevant application areas ranging from biology to business and cybersecurity. With several proposed architectures for massively parallel graph analysis, we investigate the interplay of hardware, algorithm, data, and programming model through real-world experiments and simulations. We demonstrate techniques for obtaining parallel scaling on multithreaded systems using graph algorithms that are orders of magnitude faster and larger than the state of the art. The outcome of this work is a proposed hybrid architecture for massive-scale analytics that leverages key aspects of data-parallel and highly multithreaded systems. In simulations, the hybrid systems incorporating a mix of multithreaded, shared memory systems and solid state disks performed up to twice as fast as either homogeneous system alone on graphs with as many as 18 trillion edges.PhDCommittee Chair: Bader, David A.; Committee Member: Hong, Bo; Committee Member: Riley, George; Committee Member: Vuduc, Rich; Committee Member: Wills, Lind