265 research outputs found

    Graph Processing in Main-Memory Column Stores

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    Evermore, novel and traditional business applications leverage the advantages of a graph data model, such as the offered schema flexibility and an explicit representation of relationships between entities. As a consequence, companies are confronted with the challenge of storing, manipulating, and querying terabytes of graph data for enterprise-critical applications. Although these business applications operate on graph-structured data, they still require direct access to the relational data and typically rely on an RDBMS to keep a single source of truth and access. Existing solutions performing graph operations on business-critical data either use a combination of SQL and application logic or employ a graph data management system. For the first approach, relying solely on SQL results in poor execution performance caused by the functional mismatch between typical graph operations and the relational algebra. To the worse, graph algorithms expose a tremendous variety in structure and functionality caused by their often domain-specific implementations and therefore can be hardly integrated into a database management system other than with custom coding. Since the majority of these enterprise-critical applications exclusively run on relational DBMSs, employing a specialized system for storing and processing graph data is typically not sensible. Besides the maintenance overhead for keeping the systems in sync, combining graph and relational operations is hard to realize as it requires data transfer across system boundaries. A basic ingredient of graph queries and algorithms are traversal operations and are a fundamental component of any database management system that aims at storing, manipulating, and querying graph data. Well-established graph traversal algorithms are standalone implementations relying on optimized data structures. The integration of graph traversals as an operator into a database management system requires a tight integration into the existing database environment and a development of new components, such as a graph topology-aware optimizer and accompanying graph statistics, graph-specific secondary index structures to speedup traversals, and an accompanying graph query language. In this thesis, we introduce and describe GRAPHITE, a hybrid graph-relational data management system. GRAPHITE is a performance-oriented graph data management system as part of an RDBMS allowing to seamlessly combine processing of graph data with relational data in the same system. We propose a columnar storage representation for graph data to leverage the already existing and mature data management and query processing infrastructure of relational database management systems. At the core of GRAPHITE we propose an execution engine solely based on set operations and graph traversals. Our design is driven by the observation that different graph topologies expose different algorithmic requirements to the design of a graph traversal operator. We derive two graph traversal implementations targeting the most common graph topologies and demonstrate how graph-specific statistics can be leveraged to select the optimal physical traversal operator. To accelerate graph traversals, we devise a set of graph-specific, updateable secondary index structures to improve the performance of vertex neighborhood expansion. Finally, we introduce a domain-specific language with an intuitive programming model to extend graph traversals with custom application logic at runtime. We use the LLVM compiler framework to generate efficient code that tightly integrates the user-specified application logic with our highly optimized built-in graph traversal operators. Our experimental evaluation shows that GRAPHITE can outperform native graph management systems by several orders of magnitude while providing all the features of an RDBMS, such as transaction support, backup and recovery, security and user management, effectively providing a promising alternative to specialized graph management systems that lack many of these features and require expensive data replication and maintenance processes

    Rationalising the difference in crystallisability of two sulflowers using efficient in silico methods

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    The molecular structures of the first and second generation sulflowers, sulflower and persulfurated coronene (PSC), are remarkably similar: carbon ring structures decorated with sulfur atoms, without any additional moiety

    Exploring the origins of secondary growth – two Lower Devonian (Emsian) euphyllophytes from Gaspé, Canada, and their implications for the evolution of secondary growth

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    Secondary growth from a vascular cambium has a deep fossil record among euphyllophytes, with the earliest occurrence dated to 407 Ma. To date, Armoricaphyton and Franhueberia represent the only instances of secondary growth formally documented in the Early Devonian. Secondary growth diversified rapidly and was present in all major euphyllophyte lineages by the Middle Devonian. Here, I describe two new Early Devonian euphyllophytes exhibiting secondary growth, from the Emsian (c. 400-395 Ma) Battery Point Formation (Québec, Canada): Gmujij tetraxylopteroides gen. et sp. nov. and Perplexa praestigians gen et sp. nov. Both these plants possess mesarch actinosteles with Psilophyton-type tracheid thickenings, and each represents a new type of anatomical organization among Early Devonian wood-producing euphyllophytes. These new Early Devonian plants reveal an unexpected level of diversity in the early stages of the first major tracheophyte radiation. Importantly, Gmujij and Perplexa, together with the other Early Devonian euphyllophytes exhibiting secondary growth, reinforce existing hypotheses about the modular regulation of vascular cambial growth and demonstrate that vascular cambial growth is an assemblage of regulatory modules whose deployment followed a mosaic pattern in the evolution of tracheophytes

    Architectural Principles for Database Systems on Storage-Class Memory

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    Database systems have long been optimized to hide the higher latency of storage media, yielding complex persistence mechanisms. With the advent of large DRAM capacities, it became possible to keep a full copy of the data in DRAM. Systems that leverage this possibility, such as main-memory databases, keep two copies of the data in two different formats: one in main memory and the other one in storage. The two copies are kept synchronized using snapshotting and logging. This main-memory-centric architecture yields nearly two orders of magnitude faster analytical processing than traditional, disk-centric ones. The rise of Big Data emphasized the importance of such systems with an ever-increasing need for more main memory. However, DRAM is hitting its scalability limits: It is intrinsically hard to further increase its density. Storage-Class Memory (SCM) is a group of novel memory technologies that promise to alleviate DRAM’s scalability limits. They combine the non-volatility, density, and economic characteristics of storage media with the byte-addressability and a latency close to that of DRAM. Therefore, SCM can serve as persistent main memory, thereby bridging the gap between main memory and storage. In this dissertation, we explore the impact of SCM as persistent main memory on database systems. Assuming a hybrid SCM-DRAM hardware architecture, we propose a novel software architecture for database systems that places primary data in SCM and directly operates on it, eliminating the need for explicit IO. This architecture yields many benefits: First, it obviates the need to reload data from storage to main memory during recovery, as data is discovered and accessed directly in SCM. Second, it allows replacing the traditional logging infrastructure by fine-grained, cheap micro-logging at data-structure level. Third, secondary data can be stored in DRAM and reconstructed during recovery. Fourth, system runtime information can be stored in SCM to improve recovery time. Finally, the system may retain and continue in-flight transactions in case of system failures. However, SCM is no panacea as it raises unprecedented programming challenges. Given its byte-addressability and low latency, processors can access, read, modify, and persist data in SCM using load/store instructions at a CPU cache line granularity. The path from CPU registers to SCM is long and mostly volatile, including store buffers and CPU caches, leaving the programmer with little control over when data is persisted. Therefore, there is a need to enforce the order and durability of SCM writes using persistence primitives, such as cache line flushing instructions. This in turn creates new failure scenarios, such as missing or misplaced persistence primitives. We devise several building blocks to overcome these challenges. First, we identify the programming challenges of SCM and present a sound programming model that solves them. Then, we tackle memory management, as the first required building block to build a database system, by designing a highly scalable SCM allocator, named PAllocator, that fulfills the versatile needs of database systems. Thereafter, we propose the FPTree, a highly scalable hybrid SCM-DRAM persistent B+-Tree that bridges the gap between the performance of transient and persistent B+-Trees. Using these building blocks, we realize our envisioned database architecture in SOFORT, a hybrid SCM-DRAM columnar transactional engine. We propose an SCM-optimized MVCC scheme that eliminates write-ahead logging from the critical path of transactions. Since SCM -resident data is near-instantly available upon recovery, the new recovery bottleneck is rebuilding DRAM-based data. To alleviate this bottleneck, we propose a novel recovery technique that achieves nearly instant responsiveness of the database by accepting queries right after recovering SCM -based data, while rebuilding DRAM -based data in the background. Additionally, SCM brings new failure scenarios that existing testing tools cannot detect. Hence, we propose an online testing framework that is able to automatically simulate power failures and detect missing or misplaced persistence primitives. Finally, our proposed building blocks can serve to build more complex systems, paving the way for future database systems on SCM

    Characterization of Plastic Deformation Evolution in Single Crystal and Nanocrystalline Cu During Shock by Atomistic Simulations

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    The objective of this dissertation is to characterize the evolution of plastic deformation mechanisms in single crystal and nanocrystalline Cu models during shock by atomistic simulations. Molecular dynamics (MD) simulations are performed for a range of particle velocities from 0.5 to 1.7 km/s and initial temperatures of 5, 300 and 600 K for single crystal models as well as particle velocities from 1.5 to 3.4 km/s for nanocrystalline models with grain diameters of 6, 11, 16 and 26 nm. For single crystal models, four different shock directions are selected, \u3c100\u3e, \u3c110\u3e, \u3c111\u3e and \u3c321\u3e, and dislocation density behind the shock wave front generally increases with increasing particle velocity for all shock orientations. Plastic relaxation for shock in the \u3c110\u3e, \u3c111\u3e and \u3c321\u3e directions is primarily due to a reduction in the Shockley partial dislocation density. In contrast, plastic relaxation is limited for shock in the \u3c100\u3e orientation. This is partially due to the emergence of sessile stair-rod dislocations with Burgers vectors of 1/3\u3c100\u3e and 1/6\u3c110\u3e due to the reaction of Shockley partial dislocations with twin boundaries and stacking fault intersections. For \u3c100\u3e shock, FCC Cu is uniaxially compressed towards the BCC structure behind the shock wave front; this process is more favorable at higher shock pressures and temperatures. For particle velocities above 0.9 km/s, regions of HCP crystal structure nucleate from uniaxially compressed Cu. Free energy calculations proves that the nucleation and growth of these HCP clusters are an artifact of the embedded-atom interatomic potential. In addition, simulated x-ray diffraction line profiles are created for \u3c100\u3e shock models of single crystal Cu at the Hugoniot state. Generally, peak broadening in the x-ray diffraction line profiles increases with increasing particle velocity. For nanocrystalline models, the compression of the FCC lattice towards the BCC structure is more apparent at particle velocity of 2.4 km/s, and at this particle velocity, the atomic percentage of BCC structure increases with increasing grain size. The observation of BCC structure strongly depends on grain orientation; grains with \u3c100\u3e directions closely aligned with the shock loading direction show a higher percentage of BCC structure

    The Central Palace Sanctuary at Knossos

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    This study concerns the central portion of the West wing at Knossos -Evans' Central Palace Sanctuary Area. The aim is to present a full account of the finds, and by their consideration, along with an appreciation of the architecture and stratigraphy, to assess the character and function of the area, in its several phases. The initial chapter largely sets the scene, outlining the course of events of the early excavations, and detailing the primary sources drawn upon here. In each of the following chapters, a separate group of material is presented - a chronological order is maintained in this. In the case of the final phase, the extant architecture is discussed separately from the finds - purely for ease of presentation. A full Catalogue of the Vat Room, Temple Repositories and Final phase finds is then presented; followed by some appendices. The plans, line drawings and plates are in the second volume. The earliest group (late First Palace - MM II essentially) is the Vat Room Deposit: vases and largely fragmentary objects of faience, shell and metals. Recovered from a pit below the gypsum floor, the nature of the finds can reasonably be associated with some cult/ritual activity, but of uncertain nature and position. The abundant material yielded by the Temple Repositories (MM Illb - ?LM 1a) was stowed away deliberately after some destruction: it includes vases, many faience items, bone and ivory, stone, metal and natural objects. Individually and taken together, their character is incontrovertibly to do with a shrine - the location again being uncertain. Much of the finer details of the architecture is ambiguous, though the overall succession of phases is established. The finds associated with the last are mundane - vases; but there is still some hint of ritual interest there. Thus, a thread of continuity may be observed - though the nature of the overall pattern remains debateable. More excavation will be required to proceed further

    Super-Flexible Sensors and Advanced 3D Morphing Actuators based on Elastic Instability

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    Super-flexible devices based on soft materials have the potential to sustain large mechanical deformations, enabling advanced applications such as flexible electronics, soft robots, artificial skin, and biomedical transducers. Subject to a large compression, materials may undergo different types of elastic instabilities such as wrinkles, creases, and folds. Despite recent growing interests in turning this usually unwanted phenomenon into useful engineering applications (e.g. tactile sensing), this topic remains relatively under-researched. Therefore, this thesis focuses on developing the control mechanisms of elastic instabilities, and their applications in sensing and actuation systems. Elastic instabilities induced strain-gated logic sensing technology is developed by research into micro structured metal-elastomer tri-layer system. The test structures are designed to study the deformation behaviour and to exploit the large strain sensing mechanism. The stepwise electrical signals are achieved (from ~1010 to ~120 Ω at first switching stage and then to ~50 Ω at second switching stage) that survived much higher than usual compressive strains of up to 60%. On the other hand, elastic instabilities induced topo-optical sensing strategy is created by patterning microstructure arrays within the tri-layer system. Two unwanted phenomena (creases/folds and oxygen quenching effect) are turned into a responsive and programmable 'fold to glitter' function through micro engineering, which can light up areas of an object or material by creating microscopic creases/folds within its surface. The signal-Noise-Ratio (SNR) contrast in optical pattern generation is improved by 6 folds due to the oxygen quenching effect. The numerical analysis by ABAQUS provides the fundamental theory on the mechanism of generating targeted folding through simulating the in-plane and out-of-plane strain energy localization. Different luminescent optical patterns are demonstrated under in-plane uniaxial or equi-biaxial compression. Apart from the surface deformation, the bulk deformation of heterogeneous layered structures of soft functional hydrogel is also developed to generate the controllable and reconfigurable 3D morphing device. The initial configurations with various shapes (“S”, “W” and “C”) are demonstrated due to the swelling ratio mismatch. The developed sensing and actuation technologies provide opportunities for future applications in flexible electronics, tuneable optics, soft robotics and bio-medical systems
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