The proceedings contain 13 papers. The topics discussed include: a combinatorial multi-armed bandit approach for stochastic facility allocation problem;blockchain governance and liquid democracy – quantifying decentr...
ISBN:
(纸本)9798400706707
The proceedings contain 13 papers. The topics discussed include: a combinatorial multi-armed bandit approach for stochastic facility allocation problem;blockchain governance and liquid democracy – quantifying decentralization in gitcoin and internet computer;causal mutual byzantine broadcast;research summary: enhancing localization, selection, and processing of data in vehicular cyber-physical systems;DeepSLOs for the computing Continuum;Blockchains made Lightweight: A Median Rule for State Machine Replication;Tracing the Latencies of Ares: a DSM case study;the next 700 benchmarking frameworks for concurrent data structures;and safety assistance systems for bicyclists: toward empirical studies of the dooring problem.
Service-orientation recommends dividing software into separate independent services, with each service being implemented in the programming language that best fits into the service's problem space. However, data m...
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The proceedings contain 10 papers. The topics discussed include: graph neural networks as application of distributed algorithms;cascade: an edge computing platform for real-time machine intelligence;towards an approxi...
ISBN:
(纸本)9781450392808
The proceedings contain 10 papers. The topics discussed include: graph neural networks as application of distributed algorithms;cascade: an edge computing platform for real-time machine intelligence;towards an approximation-aware computational workflow framework for accelerating large-scale discovery tasks;DARTS: distributed IoT architecture for real-time, resilient and AI-compressed workflows;drone-truck cooperated delivery under time varying dynamics;a roadmap to post-Moore era for distributed systems;colder than the warm start and warmer than the cold start! experience the spawn start in FaaS providers;QUANTAS: quantitative user-friendly adaptable networked things abstract simulator;exploring the use of strongly consistent distributed shared memory in 3D NVEs;a closer look at detectable objects for persistent memory;a closer look at detectable objects for persistent memory;and research summary: deterministic, explainable and efficient stream processing.
This special issue includes a selection of the artefacts presented at the 18th International Federated Conference on distributedcomputing Techniques (DiScoTec 2023), held at the NOVA University Lisbon (Lisbon, Portug...
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This special issue includes a selection of the artefacts presented at the 18th International Federated Conference on distributedcomputing Techniques (DiScoTec 2023), held at the NOVA University Lisbon (Lisbon, Portugal), in June 18-23, 2023. The federated conference included: COORDINATION 2023, the 25th International Conference on Coordination models and languages);DAIS 2023, the 23rd International Conference on distributed Applications and Interoperable Systems;and FORTE 2023, the 43rd International Conference on Formal Techniques for distributed Objects, Components, and Systems. All the three conferences welcomed submissions describing technological artefacts, including innovative prototypes supporting the modelling, development, analysis, simulation, or testing of systems in the broad spectrum of distributedcomputing subjects. The artefact evaluation chairs have selected a subset of high- quality accepted artefacts to be invited for submission to this special issue. Following the revision process, nine artefacts have been accepted to be part of this special issue. The published contributions include different types of artefacts, including programming libraries, frameworks, as well as tools for the analysis, verification, and simulation of distributed systems.
We describe the design and implementation of Must, a framework for modeling and automatically verifying distributed systems. Must provides a concurrency API that supports multiple communication models, on top of a mai...
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We describe the design and implementation of Must, a framework for modeling and automatically verifying distributed systems. Must provides a concurrency API that supports multiple communication models, on top of a mainstream programming language, such as Rust. Given a program using this API, Must verifies it by means of a novel, optimal dynamic partial order reduction algorithm that maintains completeness and optimality for all communication models supported by the API. We use Must to design and verify models of distributed systems in an industrial context. We demonstrate the usability of Must's API by modeling high-level system idioms (e.g., timeouts, leader election, versioning) as abstractions over the core API, and demonstrate Must's scalability by verifying systems employed in production (e.g., replicated logs, distributed transaction management protocols), the verification of which lies beyond the capacity of previous model checkers.
Intermediate representations (IRs) are fundamental to classical and quantum computing, bridging high-level quantum programminglanguages and the hardware-specific instructions required for execution. This paper review...
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Intermediate representations (IRs) are fundamental to classical and quantum computing, bridging high-level quantum programminglanguages and the hardware-specific instructions required for execution. This paper reviews the development of quantum IRs, focusing on their evolution and the need for abstraction layers that facilitate portability and optimization. Monolithic quantum IRs, such as QIR (Lubinski et al. in Front Phys 10:940293, 2022. https://***/10.3389/fphy.2022.940293), QSSA (Peduri et al. in proceedings of the 31st ACM SIGPLAN international conference on compiler construction. CC 2022. Association for computing Machinery, New York, 2022), or Q-MLIR (McCaskey and Nguyen in proceedings-2021 IEEE International Conference on Quantum computing and Engineering, QCE, 2021), their effectiveness in handling abstractions, and their hybrid support between quantum-classical operations are evaluated. However, a key limitation is their inability to address qubit locality, an essential feature for distributed quantum computing (DQC). To overcome this, InQuIR (Nishio and Wakizaka in InQuIR: Intermediate Representation for Interconnected Quantum Computers, 2023. https://***/abs/2302.00267) was introduced as an IR specifically designed for distributed systems, providing explicit control over qubit locality and inter-node communication. While effective in managing qubit distribution, InQuIR's dependence on manual manipulation of communication protocols increases complexity for developers. NetQIR (V & aacute;zquez-P & eacute;rez et al. in NetQIR: An Extension of QIR for distributed Quantum computing, 2024. https://***/abs/2408.03712), an extension of QIR for DQC, emerges as a solution to achieve the abstraction of quantum communications protocols. This review emphasizes the need for further advancements in IRs for distributed quantum systems, which will play a crucial role in the scalability and usability of future quantum networks.
In this paper, we propose a new library for storing arrays in a distributed fashion on distributed memory systems. From a programmer's perspective, these arrays behave for arbitrary reads as if they were allocated...
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ISBN:
(纸本)9798400706202
In this paper, we propose a new library for storing arrays in a distributed fashion on distributed memory systems. From a programmer's perspective, these arrays behave for arbitrary reads as if they were allocated in shared memory. When it comes to writes into these arrays, the programmer has to ensure that all writes are restricted to a fixed range of address that are "owned" by the node executing the writing operation. We show how this design, despite the owner-compute restriction can aid programmer productivity by enabling straight-forward parallelisations of typical array-manipulating codes. Furthermore, we delineate an open-source implementation of the proposed library named Shray. Using the programming interface of Shray, we compare possible hand-parallelised codes of example applications with implementations in other DSM/PGAS systems demonstrating the programming style enabled by Shray, and providing some initial performance figures.
Large language models (LLMs) like ChatGPT are changing computing education and may create additional barriers to those already faced by non-native English speakers (NNES) learning computing. We investigate an opportun...
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ISBN:
(纸本)9798400704239
Large language models (LLMs) like ChatGPT are changing computing education and may create additional barriers to those already faced by non-native English speakers (NNES) learning computing. We investigate an opportunity for a positive impact of LLMs on NNES through multilingual programming exercise generation. Following previous work with LLM exercise generation in English, we prompt OpenAI GPT-3.5 in 4 natural languages (English, Tamil, Spanish, and Vietnamese) to create introductory programming problems, sample solutions, and test cases. We evaluate these problems on their sensibility, readability, translation, sample solution accuracy, topicality, and cultural relevance. We find that problems generated in English, Spanish, and Vietnamese are largely sensible, easily understood, and accurate in their sample solutions. However, Tamil problems are mostly non-sensible and have a much lower passing test rate, indicating that the abilities of LLMs for problem generation are not generalizable across languages. Our analysis suggests that these problems could not be given verbatim to students, but with minimal effort, most errors can be fixed. We further discuss the benefits of these problems despite their flaws, and their opportunities to provide personalized and culturally relevant resources for students in their native languages.
Swarm programming is focused on the design and implementation of algorithms for large-scale systems, such as fleets of robots, ensembles of IoT devices, and sensor networks. Writing algorithms for these systems requir...
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ISBN:
(纸本)9783031626968;9783031626975
Swarm programming is focused on the design and implementation of algorithms for large-scale systems, such as fleets of robots, ensembles of IoT devices, and sensor networks. Writing algorithms for these systems requires skills and familiarity with programminglanguages, which can be a barrier for non-expert users. Even if visual programming environments have been proposed for swarm systems, they are often limited to specific platforms or tasks, and do not provide a high-level programming model that can be used to design algorithms for a wide range of swarm systems. Therefore, in this paper, we propose a low-code swarm programming environment, called ScaFi-Blocks, which allows users to design and implement swarm algorithms visually. ScaFi-Blocks is based on the ScaFi aggregate computing framework, which provides a high-level programming model for the design of distributed algorithms. Aggregate computing is based on the concept of field-based coordination, and it allows users to design algorithms by composing simple building blocks, which motivates the design of the proposed artefact. The environment is designed to be user-friendly and to support the design of a wide range of collective applications. In this paper, we present the architecture of ScaFi-Blocks, discuss its features and capabilities, and provide a preliminary evaluation of the programming environment
Compared to the wide array of advanced Monte Carlo methods supported by modern probabilistic programminglanguages (PPLs), PPL support for variational inference (VI) is less developed: users are typically limited to a...
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Compared to the wide array of advanced Monte Carlo methods supported by modern probabilistic programminglanguages (PPLs), PPL support for variational inference (VI) is less developed: users are typically limited to a predefined selection of variational objectives and gradient estimators, which are implemented monolithically (and without formal correctness arguments) in PPL backends. In this paper, we propose a more modular approach to supporting variational inference in PPLs, based on compositional program transformation. In our approach, variational objectives are expressed as programs, that may employ first-class constructs for computing densities of and expected values under user-defined models and variational families. We then transform these programs systematically into unbiased gradient estimators for optimizing the objectives they define. Our design enables modular reasoning about many interacting concerns, including automatic differentiation, density accumulation, tracing, and the application of unbiased gradient estimation strategies. Additionally, relative to existing support for VI in PPLs, our design increases expressiveness along three axes: (1) it supports an open-ended set of user-defined variational objectives, rather than a fixed menu of options;(2) it supports a combinatorial space of gradient estimation strategies, many not automated by today's PPLs;and (3) it supports a broader class of models and variational families, because it supports constructs for approximate marginalization and normalization (previously introduced only for Monte Carlo inference). We implement our approach in an extension to the Gen probabilistic programming system (***, implemented in JAX), and evaluate our automation on several deep generative modeling tasks, showing minimal performance overhead vs. hand-coded implementations and performance competitive with well-established open-source PPLs.
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