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3rd International Conference on Electronic Information Engineering and Computer, EIECT 2023

作者： Li, Zihao Xu, Liyang Jin, Ruochun Chen, Huan Tang, Yuhua National University of Defense Technology Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology Changsha410073 China

ISBN: (纸本)9798350357707

To enhance the query efficiency of relational databases and build a unified computing backend, Meta has developed Velox, a vectorized execution engine library based on columnar storage, Currently, there is no standardized specification for computation engine, and storage in graph databases, leading to failed to effectively utilize the vectorized processing capability of modern CPU. In this paper, we propose a middleware that primarily focuses on (1) non-invasively integrating Velox into the TinkerPop framework to provide unified vectorized engine acceleration for all graph databases supporting the TinkerPop specification;(2) conducting graph queries based on the relational data storage model, eliminating the overhead of transforming the storage model into a graph storage model;(3) validating the acceleration effect of the vectorized engine on interactive workload of graph queries under a single-node environment. © 2023 IEEE.

关键词： Engines

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Hybrid forecasting of demand flexibility: A top-down approach for thermostatically controlled loads

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Energy and AI 2025年 20卷

作者： Massidda, Luca Marrocu, Marino CRS4 Center for Advanced Studies Research and Development in Sardinia Italy National Research Center in High Performance Computing Big Data and Quantum Computing Italy

Demand-side flexibility is crucial to balancing supply and demand, as renewable energy sources are increasingly integrated into the energy mix, and heating and transport systems are becoming more and more electrified. Historically, this balancing has been managed from the supply side. However, the shift towards renewable energy sources limits the controllability of traditional fossil fuel plants, increasing the importance of demand response (DR) techniques to achieve the required flexibility. Aggregators participating in flexibility markets need to accurately forecast the adaptability they can offer, a task complicated by numerous influencing variables. Based on a top-down approach, this study addresses the problem of forecasting electricity demand in the presence of flexibility from thermostatically controlled loads. We propose a hybrid model that combines data-driven techniques for probabilistic estimation of electricity consumption with a disaggregation of electricity consumption to identify the fraction of thermal loads, subject to flexibility, which is simulated by a virtual battery model. The technique is applied to a synthetic dataset that simulates the response of a European neighborhood to demand response interventions. The results demonstrate the model's ability to accurately predict both the reduction in electricity demand during DR events and the subsequent rebound in consumption. The model achieves a mean absolute percentage error (MAPE) lower than 17.0%, comparable to the accuracy without flexibility. The results obtained are compared with a direct data-driven approach, demonstrating the validity and effectiveness of our model. © 2025

关键词： Demand response

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Skyrmion transport driven by pure voltage generated strain gradient

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Chinese Physics B 2022年第11期31卷 566-570页

作者： Shan Qiu Jia-Hao Liu Ya-Bo Chen Yun-Ping Zhao Bo Wei Liang Fang Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Hunan University of Humanities Science and Technology Loudi 417000China

The magnetic skyrmion transport driven by pure voltage-induced strain gradient is proposed and studied via micromagnetic *** combining the skyrmion with multiferroic heterojunction,a voltage-induced uniaxial strain gradient is adjusted to move *** the system,a pair of short-circuited trapezoidal top electrodes can generate the symmetric *** to the symmetry of strain,the magnetic skyrmion can be driven with a linear motion in the middle of the nanostrip without *** calculate the strain distribution generated by the trapezoidal top electrodes pair,and further investigate the influence of the strain intensity as well as the strain gradient on the skyrmion *** findings provide a stable and low-energy regulation method for skyrmion transport.

关键词： skyrmion strain gradient multiferroic heterojunction spintronics

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Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing

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Journal of Materiomics 2023年第4期9卷 787-797页

作者： Yan Kang Yabo Chen Yinlong Tan Hao Hao Cheng Li Xiangnan Xie Weihong Hua Tian Jiang College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha410073China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha410073China Institute for Quantum Science and Technology College of ScienceNational University of Defense TechnologyChangsha410073China

Activation of silent synapses is of great significance for the extension of neural plasticity related to learning and *** by the activation of silent synapses via receptor insertion in neural synapses,we propose an efficient method for activating artificial synapses through the intercalation of Sn in layered a-MoO_(3).Sn intercalation is capable of switching on the response of layered a-MoO_(3)to the stimuli of visible and near infrared light by decreasing the *** mimics the receptor insertion process in silent neural *** Sn-intercalated MoO_(3)(Sn-MoO_(3))exhibits persistent photoconductivity due to the donor impurity induced by Sn *** enables the two-terminal Sn-MoO_(3)device promising optoelectronic synapse with an ultrahigh paired pulse facilitation(PPF)up to 199.5%.On-demand activation and tunable synaptic plasticity endow the device great potentials for extensible neuromorphic *** performance of the extensible artificial neural network(ANN)based on the Sn-MoO_(3)synapses are demonstrated in pattern ***,the recognition accuracy increases from 89.7%to 94.8%by activating more nodes into the *** is consistent with the recognition process of physical neural network during brain *** intercalation engineering of MoO_(3)may provide inspirations for the design of high-performance neuromorphic computing architectures.

关键词： Activation of silent synapse Intercalation Layered materials Neuromorphic computing

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An Optimized Hole Cutting Approach for Overset Grid Method with Rigid Body Motion in OpenFOAM 3

An Optimized Hole Cutting Approach for Overset Grid Method w...

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3rd International Conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2023

作者： Zhao, Ran Li, Chao Guo, Xiaowei Institution of Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9781643684581

The overset grid is an effective method to handle the moving boundary problem with complex geometries or massed movement in Computational Fluid Dynamics (CFD) simulations. As a critical part of the method, the Overset Grid Assembly (OGA) determines the point types. Hole cutting is one of the key processes of OGA to find out the hole points, which will not participate in the subsequent calculation of the simulation. However, repeated hole cutting is required when the boundary moves, restricting the assembly efficiency. In this paper, we propose a Block Corresponding Cutting (BCC) method to accelerate the process by reducing the redundancy of hole cutting with Rigid-body motion. Based on the open-source platform OpenFOAM, the experiments demonstrate that, compared with the classic SAM hole cutting method, the efficiency of BCC-based hole cutting is improved by 28.1% on average. © 2023 The Authors.

关键词： Computational fluid dynamics

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Developing a proxy application for an industrial unstructured CFD software: preliminary results 29

Developing a proxy application for an industrial unstructure...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Wang, Qingsong Xu, Chuanfu Zhang, Jian Deng, Liang Dai, Zhe Qiu, Haozhong Dai, Weixi Lin, Yongzhen Ding, Yue Che, Yonggang National University of Defense Technology Institute for Quantum Information State Key Laboratory of High Performance Computing Changsha China China Aerodynamic Research and Development Center Mianyang China

ISBN: (纸本)9798350330717

As programming models and architectures evolve in the exa-scale era, porting large-scale HPC applications are becoming increasingly difficult and expensive. In HPC community, mini-apps are often developed to mimic real-world applications, and it offers an easy way to benchmark new HPC platforms. In this paper, we design and implement a mini-app MiniFS as a proxy for an industry-level unstructured Computational Fluid Dynamics (CFD) software FlowStar. The main purpose of MiniFS is to evaluate different shared memory approaches on emerging multi/many-core architectures, because data conflicts and data dependencies in unstructured CFD pose tough challenges for shared memory parallelization. Results show that our mini-app can represent the performance characteristic of the original application. However, the existing approaches are unscalable on modern multi/many-cores. It is imperative to develop novel scalable shared memory approaches for unstructured CFD. © 2023 IEEE.

关键词： mini-app shared memory unstructured CFD

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PancakeFS: A Write Efficiently and Read Optimized Filesystem 4

PancakeFS: A Write Efficiently and Read Optimized Filesystem

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4th International Conference on Consumer Electronics and Computer Engineering, ICCECE 2024

作者： Wang, Yongkang Liu, Yang Chen, Zhiguang School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Institute for Quantum Information College of Computer National University of Defense Technology State Key Laboratory of High-Performance Computing Changsha China

ISBN: (纸本)9798350384062

With the development of emerging technologies such as cloud computing and large AI models (such as LLM), many applications have placed higher demands on the intensive read and write processing of massive data. Addressing the limitations of traditional file systems, we propose PancakeFS, an LSM-Tree-based file system. Leveraging the write-friendly characteristics of LSM-Tree, PancakeFS exhibits efficient write performance. We improve read performance through the design of an inode allocation algorithm based on subtree partitioning and optimization of the disk layout for hot data reconstruction. Our experimental results demonstrate that PancakeFS outperforms Ext4 and TableFS in terms of both read and write performance. © 2024 IEEE.

关键词： Data handling

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Lightweight Operating System Services for Incremental Checkpointing in Speculative Discrete Event Simulation on Linux Platforms

Lightweight Operating System Services for Incremental Checkp...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Federica Montesano Romolo Marotta Francesco Quaglia DICII Tor Vergata University of Rome Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

One way for supporting incremental checkpointing is the exploitation of classical memory protection services—in particular the mprotect (…) system call offered by Posix compliant operating systems—for intercepting memory-writes and identifying dirty pages in the address space. However, this solution involves Inter-Processor-Interrupt (IPI) and the associated handling mechanisms, which show costs that increase when scaling up the level of parallelism in the underlying hardware architecture. For HPC contexts like speculative (aka optimistic) parallel discrete event simulation, where checkpointing and state restore massively take place in order to maintain causality among the concurrent simulation objects, these costs may impact performance in a non-negligible manner. In this work, we present the design of operating system services that enable write-protection and the tracing of dirtied pages via per CPU setup of the MMU (Memory Management Unit), completely avoiding the usage of IPI and their management. Hence, we provide a solution where the cost for setting up the incremental checkpointing support of a simulation object processed by a specific thread at a given time is definitely limited, compared to the aforementioned classical case. Our design has been devised for Linux, although it can be ported to other operating systems, and has been integrated for its testing in the USE (Ultimate Share Everything) open source parallel simulation environment.

关键词： Checkpointing Context Costs Operating systems Linux Instruction sets Scalability Memory management Discrete event simulation Testing

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Qualitative and Quantitative Model Checking Against Recurrent Neural Networks

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Journal of Computer Science & Technology 2024年第6期39卷 1292-1311页

作者： Zhen Liang Wan-Wei Liu Fu Song Bai Xue Wen-Jing Yang Ji Wang Zheng-Bin Pang Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China School of Information Science and Technology ShanghaiTech UniversityShanghai 201210China Institute of Software Chinese Academy of SciencesBeijing 100190China

Recurrent neural networks (RNNs) have been heavily used in applications relying on sequence data such as time series and natural languages. As a matter of fact, their behaviors lack rigorous quality assurance due to the black-box nature of deep learning. It is an urgent and challenging task to formally reason about the behaviors of RNNs. To this end, we first present an extension of linear-time temporal logic to reason about properties with respect to RNNs, such as local robustness, reachability, and some temporal properties. Based on the proposed logic, we formalize the verification obligation as a Hoare-like triple, from both qualitative and quantitative perspectives. The former concerns whether all the outputs resulting from the inputs fulfilling the pre-condition satisfy the post-condition, whereas the latter is to compute the probability that the post-condition is satisfied on the premise that the inputs fulfill the pre-condition. To tackle these problems, we develop a systematic verification framework, mainly based on polyhedron propagation, dimension-preserving abstraction, and the Monte Carlo sampling. We also implement our algorithm with a prototype tool and conduct experiments to demonstrate its feasibility and efficiency.

关键词： recurrent neural network model checking temporal logic qualitative/quantitative verification

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A Cross-domain Radar Emitter Recognition Method with Few-shot Learning 4

A Cross-domain Radar Emitter Recognition Method with Few-sho...

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4th International Symposium on Computer Engineering and Intelligent Communications, ISCEIC 2023

作者： Luo, Yixian Liu, Tianrui Li, Xueqiong Liu, Hengzhu Institute for Quantum Information State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9798350306323

In many realistic scenarios, it is necessary but challenging to acquire a large number of annotated radar emitter samples for training a recognition model. This study proposes a cross-domain radar emitter recognition method with few-shot learning, which introduces model-agnostic meta-learning (MAML) to recognize radar emitter and improves it to adapt to various types of radar emitter in different domains without spending a lot of time and data to retrain the model. This method can learn an ideal initialization parameter with a few source domain samples, and then initialize with this parameter on a completely different target domain. It can obtain good generalization effect by fine-tuning with fewer samples, so as to realize cross-domain recognition of radar emitter. Simulation results show that the accuracy of the proposed method can reach more than 90% in high-noise target domains with completely different data distribution from the source domain, which shows its superiority in recognition performance and sample size compared with other radar emitter recognition methods. © 2023 IEEE.

关键词： Learning systems

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