Currently, the landscape of computer hardware architecture presents the characteristics of heterogeneity and diversity, prompting widespread attention to cross-platform portable parallel programming techniques. Most e...
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Federated Learning (FL) has progressed, providing a distributed mechanism where data need not be consolidated, thereby enhancing the privacy and security of sensitive healthcare data. Recent advancements in multimodal...
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In response to the burgeoning interest in Vehicle-to-Everything (V2X) communications and its pivotal role in enhancing road transportation efficiency and safety, this paper presents a novel scheme for the formation of...
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Natural Language Processing (NLP) research has predominantly focused on the English language, leading to a wealth of resources and advancements tailored to English. However, there is a growing need to extend these cap...
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Capsule network is a new type of neural network encoding features into capsules and constructing the part-whole relationships, which demonstrated good performance in image classification. However, it has some issues s...
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As modern industrial chains grow increasingly complex and time-sensitive, traditional transportation planning methods face efficiency bottlenecks. To address this, we propose a parallelization method based on Sparse M...
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P2P, grid, Cloud and Internet computing technologies have been very fast established as breakthrough paradigms for solving complex problems by enabling aggregation and sharing of an increasing variety of distributed c...
ISBN:
(纸本)3319491083;9783319491080
P2P, grid, Cloud and Internet computing technologies have been very fast established as breakthrough paradigms for solving complex problems by enabling aggregation and sharing of an increasing variety of distributed computational resources at large scale. The aim of this volume is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to P2P, grid, Cloud and Internet computing as well as to reveal synergies among such large scale computing paradigms. This proceedings volume presents the results of the 11th internationalconference on P2P, parallel, grid, Cloud And Internet computing (3PGCIC-2016), held November 5-7, 2016, at Soonchunhyang University, Asan, Korea
Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including...
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ISBN:
(数字)9783982633619
Power gateways in the form of a microgrid can incorporate multiple distributed energy resources (DER) in either grid forming or grid following mode and support high performance computing (HPC) power profiles including the large load-follow requirements observed in multi-user HPC systems. The microgrid's flexibility to operate in either grid forming or grid following mode and to actively switch between these modes enables baseline power from multiple non-baseline DER while maintaining high power quality metrics for the HPC system. But this enormous flexibility in demand response and time of use shifting is generally programmed independently of any integration with an HPC job scheduler, which can better inform the load shaping by the microgrid. While there are many existing approaches where the HPC job scheduler takes in information from the grid to make queue scheduling decisions, this work takes the opposite view and explores three strategies where the forecast of jobs in the queue can change the settings of the grid. Three strategies are tested where the forecast of jobs in the queue adjusts the settings of a microgrid designed for a datacenter, in this case with three classes of HPC architectures. The strategies are demonstrated using a microgrid with 64 kW of solar capacity and 320 kWh of battery over a period of 21 days operating with significant load-follow swings, a throttled grid, cloudy conditions, switching between grid following and grid forming modes, and a wide range of battery states-of-charge, all while maintaining high quality power metrics. The strategies presented provide a mechanism for the forecast of jobs in the queue to influence and adjust the settings of a microgrid and to improve HPC power outcomes such as maximizing renewable energy usage.
Extra-high voltage transmission lines and cables are subject to irregular vibration due to icing or unusual weather conditions, which is potentially hazardous to the safety of the towers and the structural strength of...
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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.
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