this paper presents a configurable approximate quantum multiplier that integrates approximate and exact controlled adders with a truncation scheme to balance accuracy and circuit complexity in noisy quantum environmen...
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ISBN:
(纸本)9798400706295
this paper presents a configurable approximate quantum multiplier that integrates approximate and exact controlled adders with a truncation scheme to balance accuracy and circuit complexity in noisy quantum environments. It achieves significant enhancements in error metrics over an exact multiplier, demonstrating its potential for noise-resilient quantum computing in noisy quantum devices.
Bias detection and mitigation is an active area of research in machine learning. this work extends previous research done by the authors Van Busum and Fang (proceedings of the 38thacm/sigappsymposium on applied Comp...
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the demand for low latency, bandwidth efficiency, and privacy has driven distributed applications to the network edge, where heterogeneous, and untrusted, and uncontrolled networks pose challenges. this paper presents...
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ISBN:
(纸本)9798400706295
the demand for low latency, bandwidth efficiency, and privacy has driven distributed applications to the network edge, where heterogeneous, and untrusted, and uncontrolled networks pose challenges. this paper presents a software-defined overlay networking (SDON) middleware that simplifies application development through centralized control of edge resources while addressing many challenges prevalent at the edge. SDON enables applications to specify high-level requirements, such as service placement and communication goals. these are automatically translated into device-specific configurations and deployed on appropriate edge resources. the middleware is implemented as fully functional software, published as open-source, and will be evaluated in multiple edge computing use cases, to demonstrate its application optimization potential.
In this paper, we focus on how the main operations in evolutionary algorithms spend energy in two different languages: C++ and zig. By setting up a methodology that gives us a precise measure of the energy spent by ke...
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ISBN:
(纸本)9798400706295
In this paper, we focus on how the main operations in evolutionary algorithms spend energy in two different languages: C++ and zig. By setting up a methodology that gives us a precise measure of the energy spent by key evolutionary algorithm functions, we can give the scientific software engineer some actionable insights on how to write energy-conscious evolutionary algorithms. Our experiments show that C++ using the well-known GNU compiler can achieve a 50% reduction in energy consumption for some integer-based fitness functions, as well as very good performance on classical genetic operators.
Efficient data replica placement at the network edge is crucial for minimizing data access latency and enhancing user experience. Current solutions are mostly popularity oriented, assuming that users in close proximit...
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ISBN:
(纸本)9798400706295
Efficient data replica placement at the network edge is crucial for minimizing data access latency and enhancing user experience. Current solutions are mostly popularity oriented, assuming that users in close proximity share similar interests. While this strategy is effective for widely accessed data, it overlooks the specificity of user interests and their affinities, especially in diverse environments managed by different edge servers: data popular in region A may not be relevant in region B but be highly valuable in region *** introduce Paprika, an online heuristic-based hybrid algorithm that combines the strengths of Genetic Algorithms and Tabu Search to address replica selection and placement in edge computing environments. Paprika takes into account data popularity, pair-wise affinity between regions, and server storage capacity. Our evaluation demonstrates that the hybrid approach outperforms traditional heuristic methods by better balancing user interests across regions and favoring regions with stronger affinities.
Connected autonomous vehicles (CAVs) require extensive data processing to make real-time decisions such as obstacle detection, collision avoidance, and route optimization. To enable fast and accurate decision-making i...
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ISBN:
(纸本)9798400706295
Connected autonomous vehicles (CAVs) require extensive data processing to make real-time decisions such as obstacle detection, collision avoidance, and route optimization. To enable fast and accurate decision-making in CAVs, services traditionally executed in cloud data centers are being moved to the edge to minimize data transfer from vehicles to the cloud. We present a framework called Q-Edge that utilizes quantum computing at the network edge to improve the speed and effectiveness of data analysis for CAVs. By integrating quantum computing principles such as superposition, entanglement, and teleportation with edge computing, we propose a solution to address the latency and bandwidth issues inherent in traditional cloud computing methods. this approach, leveraging quantum software engineering practices, enables realtime decision-making, optimizing CAV performance and enhancing traffic management, urban mobility, and road safety.
this paper presents C2|Q>, a quantum software framework designed to bridge the gap between classical and quantum programming, specifically aimed at traditional developers who lack quantum computing expertise but wa...
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ISBN:
(纸本)9798400706295
this paper presents C2|Q>, a quantum software framework designed to bridge the gap between classical and quantum programming, specifically aimed at traditional developers who lack quantum computing expertise but want to leverage the potential benefits of quantum computers. C2|Q> transforms classical code written in high-level languages into quantum representations, enabling execution on Noisy Intermediate-Scale Quantum (NISQ) computers or simulators, and provides a user-friendly interface. the framework focuses on problems where quantum computing offers advantages, particularly nondeterministic polynomial-time complete (NP-complete) problems, which are considered classically *** key components of C2|Q> include a parser that identifies problem categories, extracts inputs, and converts classical inputs into quantum formats; a reducer that reformulates NP problems into 3-satisfiability problems (3SAT) when necessary; and an algorithm generator that constructs corresponding Hamiltonians and recommends feasible quantum algorithms. Additionally, the C2|Q> backend includes modules to optimize and compile quantum circuits, request and select suitable quantum hardware, and interpret computational results. the proposed framework empowers researchers and practitioners without prior quantum experience to harness the potential of hybrid quantum computation.
We present Xook-Flow, a model for constructing input/output systems for managing the data exchange in computing continuum environments. these systems are based on data distribution patterns created by structures calle...
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ISBN:
(纸本)9798400706295
We present Xook-Flow, a model for constructing input/output systems for managing the data exchange in computing continuum environments. these systems are based on data distribution patterns created by structures called abstract communication channels (ACCs). To prevent resource overload during execution, Xook-Flow automatically selects the appropriate communication channel based on user-defined criteria (e.g., throughput or resource utilization). We implemented this model in a prototype evaluated in a case study focused on managing medical data in HDF5 format across different environments.
this paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum Co...
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ISBN:
(纸本)9798400706295
this paper introduces a vision for Quantum Software Development lifecycle, proposing a hybrid full-stack iterative model that integrates quantum and classical computing. Addressing the current challenges in Quantum computing (QC) such as the need for integrating diverse programming languages and managing the complexities of quantum-classical systems, this model is rooted in the principles of DevOps and continuous software engineering. It presents a comprehensive lifecycle for quantum software development, encompassing quantum-agnostic coding, testing, deployment, cloud computing services, orchestration, translation, execution, and interpretation phases. Each phase is designed to accommodate the unique demands of QC, enabling traditional software developers to engage with QC environments without needing in-depth QC expertise. the paper presents a detailed implementation roadmap, utilizing a range of existing tools and frameworks, thereby making quantum software development more accessible and efficient. the proposed model not only addresses current challenges in quantum software development but also makes a substantial contribution to the field of Quantum Software Engineering (QSE). By proposing a structured and accessible model, it sets the stage for further advancements and research in QSE, enhancing its practicality and relevance in a wide range of applications.
Stochastic computing (SC) has garnered a great interest due to its energy efficiency and robustness against external noise, yet a long latency on stochastic computations and considerable overheads caused by conversion...
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ISBN:
(纸本)9798400706295
Stochastic computing (SC) has garnered a great interest due to its energy efficiency and robustness against external noise, yet a long latency on stochastic computations and considerable overheads caused by conversions between binary numbers and stochastic numbers persist as notable challenges. this paper introduces a novel parallel random number generator (RNG) and accumulative parallel counters (APCs) to address both challenges. In particular, we propose a new parallel RNG design based on Omega network to bolster the randomness of generated numbers, thereby enhancing accuracy and reducing latency. Additionally, we introduce a novel APC design technique leveraging approximate 4-2 compressors to improve hardware efficiency while preserving the accuracy of SC computations. When implemented using a 65-nm CMOS technology, our proposed SC architecture outperforms other SC alternatives in terms of both hardware efficiency and computation accuracy. Specifically, our APC designs exhibit substantial enhancements of up to 30.1×, 26.6×, 5.9×, and 151× in area, power, delay, and energy, respectively, compared to traditional APCs. Also, we validate the efficacy of the proposed SC design through an image processing application, demonstrating superior processing quality alongside significantly enhanced hardware efficiency.
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