Multivariate time series anomaly detection (MTAD) poses a challenge due to temporal and feature dependencies. The critical aspects of enhancing the detection performance lie in accurately capturing the dependencies be...
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Transitive closure computation is a fundamental operation in graph theory with applications in various domains. However, the increasing size and complexity of real-world graphs make traditional algorithms inefficient,...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
Transitive closure computation is a fundamental operation in graph theory with applications in various domains. However, the increasing size and complexity of real-world graphs make traditional algorithms inefficient, especially when dealing with large datasets. This paper investigates the optimisation of transitive closure algorithms for high performance computing (HPC) applications. We implement and compare three different methods for computing the adjacency matrix of the transitive closure, based on three different Python libraries (NetworkX, PyTorch and NumPy). Our approach is benchmarked on seven real-world datasets of varying size and density to evaluate performance and scalability. The results show that NumPy achieves the best performance for large and dense graphs. The paper concludes with a discussion of the potential benefits of algorithmic optimization in HPC and security.
This paper presents SPARE, a novel serverless platform that supports self-adaptive resource allocation and reconfiguration, thereby increasing the availability of computing resources for time-critical tasks in urgent ...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
This paper presents SPARE, a novel serverless platform that supports self-adaptive resource allocation and reconfiguration, thereby increasing the availability of computing resources for time-critical tasks in urgent events. In emergency scenarios, SPARE reallocates resources by forwarding serverless function invocations to the nearest edge nodes having sufficient capacity. Additionally, the platform employs the use of unikernels and lightweight virtualization through Firecracker, which helps to reduce cold start times and improve function responsiveness. The experimental results demonstrate that SPARE is capable of releasing up to one-third of edge nodes within a serverless edge platform, while only experiencing a mild increase in latency, thus maintaining service continuity.
Synthetic Aperture Radar (SAR) tomography is an advanced technique for monitoring deformations of the Earth’s surface. However, the computational complexity of SAR tomography algorithms often restricts their applicat...
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ISBN:
(数字)9798331524937
ISBN:
(纸本)9798331524944
Synthetic Aperture Radar (SAR) tomography is an advanced technique for monitoring deformations of the Earth’s surface. However, the computational complexity of SAR tomography algorithms often restricts their application to large-scale datasets. To address this issue, we introduce a multi-level parallel implementation of a single scatterer detection algorithm specifically designed to exploit the capabilities of modern heterogeneous High-Performance computing (HPC) systems. By efficiently distributing the computational workload at different levels across multiple processing units, our parallel approach significantly reduces processing time, facilitating the analysis of extensive SAR datasets. We assess the performance of our parallel implementation using real-world SAR data, showcasing its effectiveness in enhancing both the efficiency and scalability of SAR tomography. Our work contributes to advancing remote sensing techniques and offers valuable insights into the application of HPC for large-scale environmental monitoring.
The integration of distributed Generation (DG) in grid-connected systems presents challenges in maintaining reliable protection schemes, particularly in coordinating Directional Overcurrent Relays (DOCR). This paper p...
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ISBN:
(数字)9798331530402
ISBN:
(纸本)9798331530419
The integration of distributed Generation (DG) in grid-connected systems presents challenges in maintaining reliable protection schemes, particularly in coordinating Directional Overcurrent Relays (DOCR). This paper proposes an Adaptive Protection scheme that optimizes the coordination of DOCRs using a Micro-genetic Algorithm ($\mu \mathbf{G A}$). The proposed method enhances the resilience and adaptability of protection mechanisms against variable fault conditions and DG contributions. Through simulation studies, the performance of the $\mu$ GA-based approach is evaluated against traditional coordination methods, demonstrating improved fault detection and minimized relay operating times. Results indicate significant reductions in coordination time intervals, ensuring reliable operation of protection systems in the presence of DG. This research offers a framework for enhancing the operational reliability of power systems while accommodating the increasing prevalence of distributed energy resources.
This paper studies rule-based blocking in Entity Resolution (ER). We propose Hyper Blocker, a GPU-accelerated system for blocking in ER. As opposed to previous blocking algorithms and parallel blocking solvers, Hyper ...
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Sparse triangular solve (SpTRSV) is a vital component in various scientific applications, and numerous GPU-based SpTRSV algorithms have been proposed. Synchronization-free SpTRSV is currently the mainstream algorithm ...
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Artificial Intelligence of Things (AIoT) systems are widely utilized in various domains such as smart logistics and smart health. In AIoT systems, computational tasks earmarked for offloading by IoT devices often have...
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Self-supervised time series anomaly detection (TSAD) demonstrates remarkable performance improvement by extracting high-level data semantics through proxy tasks. Nonetheless, most existing self-supervised TSAD techniq...
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Finance informatization is an important method that helps managers in companies to enhance the decision-making quality along with their efficiency. The finance ERP system enriched with the help of the grid algorithms ...
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ISBN:
(纸本)9798400712425
Finance informatization is an important method that helps managers in companies to enhance the decision-making quality along with their efficiency. The finance ERP system enriched with the help of the grid algorithms facilitates data analytics and the following of funds, with the assistance of such computational resources, the status of which is that the deployment of computational resources is done effectively and the task scheduling model is efficient. During looking at these grid algorithms on a more detailed level, these are results that were obtained when classification methods such as dynamic scheduling algorithms and load balancing algorithms were performed, the ones of which can particularly be used for parallel and distributedcomputing along with a multitude of services or enhancing the financial system performance. An experiment's design included explicit environmental setups that were outlined and a myriad of test datasets, which facilitated the assessment of comparative efficiency. The response time and processing efficiency the ERP system achieves using grid algorithms are the main causes of enhanced system performance metrics (far beyond the traditional thresholds). Besides the smoothness and cost-effectiveness of the system, the new system will result in an economic advantage in the market for a design concept that also will provide enterprises with the outline of and help in the implementation of the system that will solve a variety of financial issues they face. The study result indicates refreshed views and suggestions for the future economic management, the result of which will be efficient financial decisions and better use of the resources.
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