10,171 research outputs found

    Language integrated relational lenses

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    Relational databases are ubiquitous. Such monolithic databases accumulate large amounts of data, yet applications typically only work on small portions of the data at a time. A subset of the database defined as a computation on the underlying tables is called a view. Querying views is helpful, but it is also desirable to update them and have these changes be applied to the underlying database. This view update problem has been the subject of much previous work before, but support by database servers is limited and only rarely available. Lenses are a popular approach to bidirectional transformations, a generalization of the view update problem in databases to arbitrary data. However, perhaps surprisingly, lenses have seldom actually been used to implement updatable views in databases. Bohannon, Pierce and Vaughan propose an approach to updatable views called relational lenses. However, to the best of our knowledge this proposal has not been implemented or evaluated prior to the work reported in this thesis. This thesis proposes programming language support for relational lenses. Language integrated relational lenses support expressive and efficient view updates, without relying on updatable view support from the database server. By integrating relational lenses into the programming language, application development becomes easier and less error-prone, avoiding the impedance mismatch of having two programming languages. Integrating relational lenses into the language poses additional challenges. As defined by Bohannon et al. relational lenses completely recompute the database, making them inefficient as the database scales. The other challenge is that some parts of the well-formedness conditions are too general for implementation. Bohannon et al. specify predicates using possibly infinite abstract sets and define the type checking rules using relational algebra. Incremental relational lenses equip relational lenses with change-propagating semantics that map small changes to the view into (potentially) small changes to the source tables. We prove that our incremental semantics are functionally equivalent to the non-incremental semantics, and our experimental results show orders of magnitude improvement over the non-incremental approach. This thesis introduces a concrete predicate syntax and shows how the required checks are performed on these predicates and show that they satisfy the abstract predicate specifications. We discuss trade-offs between static predicates that are fully known at compile time vs dynamic predicates that are only known during execution and introduce hybrid predicates taking inspiration from both approaches. This thesis adapts the typing rules for relational lenses from sequential composition to a functional style of sub-expressions. We prove that any well-typed functional relational lens expression can derive a well-typed sequential lens. We use these additions to relational lenses as the foundation for two practical implementations: an extension of the Links functional language and a library written in Haskell. The second implementation demonstrates how type-level computation can be used to implement relational lenses without changes to the compiler. These two implementations attest to the possibility of turning relational lenses into a practical language feature

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Fictocritical Cyberfeminism: A Paralogical Model for Post-Internet Communication

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    This dissertation positions the understudied and experimental writing practice of fictocriticism as an analog for the convergent and indeterminate nature of “post-Internet” communication as well a cyberfeminist technology for interfering and in-tervening in metanarratives of technoscience and technocapitalism that structure contemporary media. Significant theoretical valences are established between twen-tieth century literary works of fictocriticism and the hybrid and ephemeral modes of writing endemic to emergent, twenty-first century forms of networked communica-tion such as social media. Through a critical theoretical understanding of paralogy, or that countercultural logic of deploying language outside legitimate discourses, in-volving various tactics of multivocity, mimesis and metagraphy, fictocriticism is ex-plored as a self-referencing linguistic machine which exists intentionally to occupy those liminal territories “somewhere in among/between criticism, autobiography and fiction” (Hunter qtd. in Kerr 1996). Additionally, as a writing practice that orig-inated in Canada and yet remains marginal to national and international literary scholarship, this dissertation elevates the origins and ongoing relevance of fictocriti-cism by mapping its shared aims and concerns onto proximal discourses of post-structuralism, cyberfeminism, network ecology, media art, the avant-garde, glitch feminism, and radical self-authorship in online environments. Theorized in such a matrix, I argue that fictocriticism represents a capacious framework for writing and reading media that embodies the self-reflexive politics of second-order cybernetic theory while disrupting the rhetoric of technoscientific and neoliberal economic forc-es with speech acts of calculated incoherence. Additionally, through the inclusion of my own fictocritical writing as works of research-creation that interpolate the more traditional chapters and subchapters, I theorize and demonstrate praxis of this dis-tinctively indeterminate form of criticism to empirically and meaningfully juxtapose different modes of knowing and speaking about entangled matters of language, bod-ies, and technologies. In its conclusion, this dissertation contends that the “creative paranoia” engendered by fictocritical cyberfeminism in both print and digital media environments offers a pathway towards a more paralogical media literacy that can transform the terms and expectations of our future media ecology

    A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases

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    In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance

    Approximate Computing Survey, Part I: Terminology and Software & Hardware Approximation Techniques

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    The rapid growth of demanding applications in domains applying multimedia processing and machine learning has marked a new era for edge and cloud computing. These applications involve massive data and compute-intensive tasks, and thus, typical computing paradigms in embedded systems and data centers are stressed to meet the worldwide demand for high performance. Concurrently, the landscape of the semiconductor field in the last 15 years has constituted power as a first-class design concern. As a result, the community of computing systems is forced to find alternative design approaches to facilitate high-performance and/or power-efficient computing. Among the examined solutions, Approximate Computing has attracted an ever-increasing interest, with research works applying approximations across the entire traditional computing stack, i.e., at software, hardware, and architectural levels. Over the last decade, there is a plethora of approximation techniques in software (programs, frameworks, compilers, runtimes, languages), hardware (circuits, accelerators), and architectures (processors, memories). The current article is Part I of our comprehensive survey on Approximate Computing, and it reviews its motivation, terminology and principles, as well it classifies and presents the technical details of the state-of-the-art software and hardware approximation techniques.Comment: Under Review at ACM Computing Survey

    ACE: A Consent-Embedded privacy-preserving search on genomic database

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    In this paper, we introduce ACE, a consent-embedded searchable encryption scheme. ACE enables dynamic consent management by supporting the physical deletion of associated data at the time of consent revocation. This ensures instant real deletion of data, aligning with privacy regulations and preserving individuals' rights. We evaluate ACE in the context of genomic databases, demonstrating its ability to perform the addition and deletion of genomic records and related information based on ID, which especially complies with the requirements of deleting information of a particular data owner. To formally prove that ACE is secure under non-adaptive attacks, we present two new definitions of forward and backward privacy. We also define a new hard problem, which we call D-ACE, that facilitates the proof of our theorem (we formally prove its hardness by a security reduction from DDH to D-ACE). We finally present implementation results to evaluate the performance of ACE

    2P-BFT-Log: 2-Phase Single-Author Append-Only Log for Adversarial Environments

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    Replicated append-only logs sequentially order messages from the same author such that their ordering can be eventually recovered even with out-of-order and unreliable dissemination of individual messages. They are widely used for implementing replicated services in both clouds and peer-to-peer environments because they provide simple and efficient incremental reconciliation. However, existing designs of replicated append-only logs assume replicas faithfully maintain the sequential properties of logs and do not provide eventual consistency when malicious participants fork their logs by disseminating different messages to different replicas for the same index, which may result in partitioning of replicas according to which branch was first replicated. In this paper, we present 2P-BFT-Log, a two-phase replicated append-only log that provides eventual consistency in the presence of forks from malicious participants such that all correct replicas will eventually agree either on the most recent message of a valid log (first phase) or on the earliest point at which a fork occurred as well as on an irrefutable proof that it happened (second phase). We provide definitions, algorithms, and proofs of the key properties of the design, and explain one way to implement the design onto Git, an eventually consistent replicated database originally designed for distributed version control. Our design enables correct replicas to faithfully implement the happens-before relationship first introduced by Lamport that underpins most existing distributed algorithms, with eventual detection of forks from malicious participants to exclude the latter from further progress. This opens the door to adaptations of existing distributed algorithms to a cheaper detect and repair paradigm, rather than the more common and expensive systematic prevention of incorrect behaviour.Comment: Fixed 'two-phase' typ

    Compositional Probabilistic Model Checking with String Diagrams of MDPs

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    We present a compositional model checking algorithm for Markov decision processes, in which they are composed in the categorical graphical language of string diagrams. The algorithm computes optimal expected rewards. Our theoretical development of the algorithm is supported by category theory, while what we call decomposition equalities for expected rewards act as a key enabler. Experimental evaluation demonstrates its performance advantages.Comment: 32 pages, Extended version of a paper in CAV 202

    Flashpoint: A Low-latency Serverless Platform for Deep Learning Inference Serving

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    Recent breakthroughs in Deep Learning (DL) have led to high demand for executing inferences in interactive services such as ChatGPT and GitHub Copilot. However, these interactive services require low-latency inferences, which can only be met with GPUs and result in exorbitant operating costs. For instance, ChatGPT reportedly requires millions of U.S. dollars in cloud GPUs to serve its 1+ million users. A potential solution to meet low-latency requirements with acceptable costs is to use serverless platforms. These platforms automatically scale resources to meet user demands. However, current serverless systems have long cold starts which worsen with larger DL models and lead to poor performance during bursts of requests. Meanwhile, the demand for larger and larger DL models make it more challenging to deliver an acceptable user experience cost-effectively. While current systems over-provision GPUs to address this issue, they incur high costs in idle resources which greatly reduces the benefit of using a serverless platform. In this thesis, we introduce Flashpoint, a GPU-based serverless platform that serves DL inferences with low latencies. Flashpoint achieves this by reducing cold start durations, especially for large DL models, making serverless computing feasible for latency-sensitive DL workloads. To reduce cold start durations, Flashpoint reduces download times by sourcing the DL model data from within the compute cluster rather than slow cloud storage. Additionally, Flashpoint minimizes in-cluster network congestion from redundant packet transfers of the same DL model to multiple machines with multicasting. Finally, Flashpoint also reduces cold start durations by automatically partitioning models and deploying them in parallel on multiple machines. The reduced cold start durations achieved by Flashpoint enable the platform to scale resource allocations elastically and complete requests with low latencies without over-provisioning expensive GPU resources. We perform large-scale data center simulations that were parameterized with measurements our prototype implementations. We evaluate the system using six state-of-the-art DL models ranging from 499 MB to 11 GB in size. We also measure the performance of the system in representative real-world traces from Twitter and Microsoft Azure. Our results in the full-scale simulations show that Flashpoint achieves an arithmetic mean of 93.51% shorter average cold start durations, leading to 75.42% and 66.90% respective reductions in average and 99th percentile end-to-end request latencies across the DL models with the same amount of resources. These results show that Flashpoint boosts the performance of serving DL inferences on a serverless platform without increasing costs

    Leveraging Manifold Theory for Trajectory Design - A Focus on Futuristic Cislunar Missions

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    Optimal control methods for designing trajectories have been studied extensively by astro-dynamicists. Direct and indirect methods provide separate approaches to arrive at the optimal solution, each having their associated advantages and challenges. Among the realm of optimized transfer trajectories, fuel-optimal trajectories are typically most sought and characterized by se-quential thrust and coast arcs. On the other hand, it is well known that a simplified dynamical model like the CR3BP analyzed in a rotating coordinate system, reveal fixed points known as Lagrange points. These spatial points can be orbited, with researchers categorizing periodic orbits around them starting from the simple planar Lyapunov orbits and continuing to the more enigmatic butterfly orbits. Studying linearized dynamics using eigenanalysis in the vicinity of a point on these periodic orbits lead to interesting departures spatially manifesting into the invariant manifolds. This thesis delves into the novel idea of merging aspects of invariant manifold theory and indirect optimal control methods to provide efficient computation of feasible transfer trajectories. The marriage of these ideas provide the possibility of alleviating the challenges of an end-to end optimization using indirect methods for a long mission by utilizing the pre-computed and analyzed manifolds for insertion points of a long terminal coast arc. In addition to this, realistic and accurate mission scenarios require consideration of a high-fidelity dynamical model as well as shadow constraints. A methodology to use the “manifold analogues” in such cases has been discussed and utilized in this thesis along with modelling of eclipses during optimization, providing mission designers a basis for efficient and accurate/mission-ready trajectory design. This overcomes the shortcomings in state of the art software packages such as MYSTIC and COPERNICUS
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