Overview of TRIPOLI-5, a Monte Carlo code for HPC by Mancusi Davide, Brun Emeric, Dechenaux Benjamin, Fröhlicher Kévin, Gonçalves Thomas, Jinaphanh Alexis, Kowalski Mikolaj Adam, Larmier Coline, Malvagi Fausto, Millasseau Grégory, Monange Wilfried, Petit Odile, Zoia Andrea

“…CEA, IRSN and EDF have joined forces and started the development of the TRIPOLI-5® Monte Carlo particle transport code in 2022, with the goal of performing massively parallel simulations on hybrid computing architectures. TRIPOLI-5 benefits from the experience gained from previous investigations conducted on the PATMOS mini-app, concerning the portability of particle-transport algorithms in High Performance Computing environments. …”
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Multidimensional QoS cloud computing resource scheduling method based on stakeholder perspective by Mingfeng SU, Guojun WANG, Renfa LI

“…A multidimensional cloud computing architecture is designed and a multidimensional cloud resource scheduling model is constructed based on the stakeholder perspective of cloud users and cloud service providers to meet the high QoS requirements of cloud users (such as task execution time and task completion time) with low computing costs (such as energy consumption,economic costs and system availability).For the second-level cloud resource scheduling,an MQoS cloud resource scheduling algorithm based on multiple Greedy algorithm is proposed.The experimental results show that under the four cloud computing application scenarios with no aftereffects,the MQoS cloud resource scheduling algorithm has an overall increase of 206.42%~228.99% and 34.26%~56.93 in terms of multidimensional QoS degree compared with FIFO and M2EC algorithms.It has an average overall reduction of 0.48~0.49 and 0.20~0.27 in terms of cloud data center load balance difference.…”
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Optical single-shot readout of spin qubits in silicon by Andreas Gritsch, Alexander Ulanowski, Jakob Pforr, Andreas Reiserer

“…To this end, spin qubits with optical interfaces offer key advantages: they can minimize the heat load and give access to modular quantum computing architectures that eliminate cross-talk and offer a large connectivity. …”
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The Advances in Neuromorphic Computing and Brain-Inspired Systems (ANCBIS). by DanielRaj K, Ponseka G, Bharath Sanjai Lordwin D J3

“…This field seeks to bridge the gap between traditional computing architectures and biological neural networks by replicating brain-like functionalities. …”
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From Sports Collectibles to the Digital Humanities: the Evolution of Technology and the Transformation of Consciousness by Luca Baraldi

“…But in today’s growing digital ecosystem, historical memory has turned into data, computer architectures, and algorithmic interpretations. It is important not to approach this in purely technological terms, but instead as a real epistemological revolution. …”
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LSKE: Lightweight Secure Key Exchange Scheme in Fog Federation by Yashar Salami, Vahid Khajehvand

“…The fog computing architecture allows data exchange with the vehicle network, sensor networks, etc. …”
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Research on motion target detection based on infrared biomimetic compound eye camera by Linhan Li, Xiaoyu Wang, Teng Lei, Juan Yue, Sili Gao, Yang Yu, Haifeng Su

“…To address this issue, we propose an improved elementary motion detector model that combines a double-layer ON_OFF channel and a cross-type computational architecture, which is able to suppress a stationary background and enhance moving targets. …”
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GPGPU COMPUTING by BOGDAN OANCEA, TUDOREL ANDREI, RALUCA MARIANA DRAGOESCU

“…In this paper we will focus on the CUDA parallel computing architecture and programming model introduced by NVIDIA. …”
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From Sports Collectibles to the Digital Humanities: the Evolution of Technology and the Transformation of Consciousness by Luca Baraldi

“…But in today’s growing digital ecosystem, historical memory has turned into data, computer architectures, and algorithmic interpretations. It is important not to approach this in purely technological terms, but instead as a real epistemological revolution. …”
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Research on task offloading algorithm of mobile edge computing based on deep reinforcement learning in SDCN by Shouhua JIANG, Yiwu WANG

“…With the continuous development of network technology, the network topology distributed network control mode based on Fat-Tree gradually reveals its limitations.Software-defined data center network (SDCN) technology, as an improved technology of Fat-Tree network topology, has attracted more and more researchers’ attention.Firstly, an edge computing architecture in SDCN and a task offloading model based on the three-layer service architecture of the mobile edge computing (MEC) platform were built, combined with the actual application scenarios of the MEC platform.Through the same strategy experience playback and entropy regularization, the traditional deep Q-leaning network (DQN) algorithm was improved, and the task offloading strategy of MEC platform was optimized.An improved DQN algorithm based on same strategy empirical playback and entropy regularization (RSS2E-DQN) was compared with three other algorithms in load balancing, energy consumption, delay and network usage.It is verified that the improved algorithm has better performance in the above four aspects.…”
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Dissipative Protection of a GKP Qubit in a High-Impedance Superconducting Circuit Driven by a Microwave Frequency Comb by L.-A. Sellem, A. Sarlette, Z. Leghtas, M. Mirrahimi, P. Rouchon, P. Campagne-Ibarcq

“…Qubit initialization, readout, and control via Clifford gates can be performed while maintaining the code stabilization, paving the way toward the assembly of GKP qubits in a fault-tolerant quantum computing architecture.…”
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Multitask Learning-Based Pipeline-Parallel Computation Offloading Architecture for Deep Face Analysis by Faris S. Alghareb, Balqees Talal Hasan

“…Moreover, a speedup of 62.48% is achieved compared to the sequential-based edge computing architecture. Meanwhile, 25.96% speed performance acceleration is realized when implementing the proposed pipeline-parallel architecture only on the server edge compared to the sever sequential implementation. …”
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The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing by Wen-Chung Shih, Zheng-Yao Wang, Endah Kristiani, Yi-Jun Hsieh, Yuan-Hsin Sung, Chia-Hsin Li, Chao-Tung Yang

“…Overall, the findings contribute valuable insights into building efficient edge computing architectures that support real-time video processing and streaming.…”
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Layer ensemble averaging for fault tolerance in memristive neural networks by Osama Yousuf, Brian D. Hoskins, Karthick Ramu, Mitchell Fream, William A. Borders, Advait Madhavan, Matthew W. Daniels, Andrew Dienstfrey, Jabez J. McClelland, Martin Lueker-Boden, Gina C. Adam

“…Abstract Artificial neural networks have advanced due to scaling dimensions, but conventional computing struggles with inefficiencies due to memory bottlenecks. In-memory computing architectures using memristor devices offer promise but face challenges due to hardware non-idealities. …”
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Multi-functional broadband diffractive neural network with a single spatial light modulator by Bolin Li, Yinfei Zhu, Jinlei Fei, Runshi Zheng, Min Gu, Jian Lin

“…Diffractive neural networks (DNNs) are emerging as a novel optical computing architecture that combines wave optics with deep-learning methods for high-speed parallel information processing. …”
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Optimizing the Agricultural Internet of Things (IoT) with Edge Computing and Low-Altitude Platform Stations by Deshan Yang, Jingwen Wu, Yixin He

“…First, we introduce an LAPS-aided edge computing architecture for the agricultural IoT, in which each task is segmented into several interdependent subtasks for processing. …”
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Every Second Counts: Integrating Edge Computing and Service Oriented Architecture for Automatic Emergency Management by Lei Chen, Cristofer Englund

“…Applying the concept of multiaccess edge computing architecture, as well as choreography of the service oriented architecture, the system allows seamless coordination between multiple organizations in a distributed way through standard web services. …”
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Service migration of heterogeneous cloud computing platform by Feng WEI, Fei DING, Pengju JIAO, Yang LI, Yanshan CHEN, Dengyin ZHANG

“…With the rapid development of 5G communication technology,Internet+ and the Internet of things (IoT),cloud computing as an Internet-based virtual resource management and a distributed computing technology,provides services to users in a dynamic,on-demand and measurable manner.The solution of migrating the service platform to the cloud computing platform can realize rapid service deployment and effectively save service innovation and operating cost.With the research of the cloud computing platform-based service migration technology,the China Mobile’s OpenStack-based cloud computing architecture was taken as an example.The technical principles and core points of the mainstream service migration schemes were analyzed,such as offline migration,online migration based on platform functions,online service migration based on the agent block level and online service migration based on agent file level.The general service migration process and method were also given.Finally,three types of online migration schemes were experimentally verified through the actual platform.The technical advantages and adaptation scenarios were analyzed separately to guide the production practice of future business migration.…”
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Twinkle: A GPU-based Binary-lens Microlensing Code with the Contour Integration Method by Suwei Wang, Lile Wang, Subo Dong

“…We have advanced the state of the art by optimizing Twinkle specifically for heterogeneous computing devices by taking into account the unique task and cache memory dispatching patterns of GPUs, while the compatibility with the traditional computing architectures of CPUs is still maintained. Twinkle has demonstrated an acceleration of approximately 2 orders of magnitude (≳10 ^2 ×) on contemporary GPUs. …”
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High-Bandwidth and Energy-Efficient Memory Interfaces for the Data-Centric Era: Recent Advances, Design Challenges, and Future Prospects by Joo-Hyung Chae

“…In the current computing architecture, the memory input and output (I/O) bandwidth is becoming a bottleneck for improving computing performance; therefore, high-bandwidth memory interfaces are essential. …”
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