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22nd IEEE International Symposium on parallel and Distributed Processing with Applications, ISPA 2024

作者： Ma, Yi Chen, Xin Guo, Heng Li, Fang Liu, Xin Tsinghua University Beijing China National Research Center of Parallel Computer Engineering and Technology Beijing China

ISBN: (纸本)9798331509712

Load imbalance often occurs in particle-in-cell simulations on parallel computing, which seriously affects the efficiency of applications. Due to the characteristics of multilevel parallelism and communication asymmetry of compute nodes in domestic heterogeneous manycore architecture, the impact of load imbalance is more prominent. The paper proposes a multilevel load-balancing algorithm for domestic heterogeneous manycore architecture. Inside the supernode, computing tasks are redivided based on manycore acceleration. Between the supernodes, a greedy-based communication mode is designed to minimize communication across supernodes. The experimental results show that the proposed algorithm achieves almost ideal dynamic load balance, and improves the performance of the evaporation module in two-phase flow simulation by 10.9-19.7 times for the 50 million-sized grid. © 2024 IEEE.

关键词： parallel architectures

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Big Data Mining of Maritime Shipping Flows Based on Dependency Relationships 9

Big Data Mining of Maritime Shipping Flows Based on Dependen...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Fu, Yude Li, Xiang Lu, Xiongyi Yu, Mengjun Huangpeng, Qizi Duan, Xiaojun College of Science National University of Defense Technology Changsha China National Research Center of Parallel Computer Engineering and Technology Beijing China

ISBN: (纸本)9798350376548

This research utilizes higher-order dependency relationships for the modeling of higher-order dependency networks from voluminous maritime flow data and introduces higher-order dependency mining to uncover critical port information in the China-Southeast Asia region as well as the coopetition relationships between ports. Analysis of maritime data from the years 2018 and 2023 indicates that global ports maintain stability and competitiveness through their evolution, with Singapore serving as the central hub connecting China and Southeast Asia. Subsequent analysis employing dependency paths indicates that in recent years, the dependency relationships among ports between China and Southeast Asia have achieved higher orders and greater complexity. © 2024 IEEE.

关键词： competition and cooperation dependency relationships flow data maritime network

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Efficient alltoall_inplace communication algorithms with limited buffer space

Efficient alltoall_inplace communication algorithms with lim...

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2022 International Conference on computer Application and Information Security, ICCAIS 2022

作者： Fang, Yanfei Li, Yanbing Dong, Enming Qi, Fengbin He, Wangquan Wang, Yunfei Xu, Zhengmao National Research Center of Parallel Computer Engineering and Technology Beijing100190 China

ISBN: (纸本)9781510663459

Alltoall is an important collective communication mode that is widely used in scientific and engineering computing applications. In applications such as FFT, using as much memory space as possible can improve applications' efficiency and expand the scale of problems to be solved. High-bandwidth alltoall_inplace communication under space-constrained buffer conditions can significantly improve the performance of such applications. In this paper, two alltoall_inpalce communication algorithms under the condition of limited buffer space are designed for the domestic parallel computing system based on Sunway many-core processor. The alltoall_inpalce communication interfaces for both the core array and the whole CPU node are realized. The experimental results show that algorithms implemented in this paper can achieve high bandwidth using limited buffer space. © 2023 SPIE.

关键词： Bandwidth

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Behaviour-diverse automatic penetration testing:a coverage-based deep reinforcement learning approach

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Frontiers of computer Science 2025年第3期19卷 15-24页

作者： Yizhou YANG Longde CHEN Sha LIU Lanning WANG Haohuan FU Xin LIU Zuoning CHEN Zhongguancun Laboratory Beijing 100081China Zhejiang Lab Hangzhou 311121China National Research Centre of Parallel Computer Engineering and Technology Wuxi 214000China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China Department of Earth System Science Tsinghua UniversityBeijing 100084China

Reinforcement Learning(RL)is gaining importance in automating penetration testing as it reduces human effort and increases ***,given the rapidly expanding scale of modern network infrastructure,the limited testing scale and monotonous strategies of existing RLbased automated penetration testing methods make them less effective in practical *** this paper,we present CLAP(Coverage-Based Reinforcement Learning to Automate Penetration Testing),an RL penetration testing agent that provides comprehensive network security assessments with diverse adversary testing behaviours on a massive *** employs a novel neural network,namely the coverage mechanism,to address the enormous and growing action spaces in large *** also utilizes a Chebyshev decomposition critic to identify various adversary strategies and strike a balance between *** results across various scenarios demonstrate that CLAP outperforms state-of-the-art methods,by further reducing attack operations by nearly 35%.CLAP also provides enhanced training efficiency and stability and can effectively perform pen-testing over large-scale networks with up to 500 ***,the proposed agent is also able to discover pareto-dominant strategies that are both diverse and effective in achieving multiple objectives.

关键词： network security penetration testing reinforcement learning artificial intelligence

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Scalability and efficiency challenges for the exascale supercomputing system:practice of a parallel supporting environment on the Sunway exascale prototype system

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Frontiers of Information technology & Electronic engineering 2023年第1期24卷 41-58页

作者： Xiaobin HE Xin CHEN Heng GUO Xin LIU Dexun CHEN Yuling YANG Jie GAO Yunlong FENG Longde CHEN Xiaona DIAO Zuoning CHEN National Research Center of Parallel Computer Engineering and Technology Beijing 100190China

With the continuous improvement of supercomputer performance and the integration of artificial intelligence with traditional scientific computing,the scale of applications is gradually increasing,from millions to tens of millions of computing cores,which raises great challenges to achieve high scalability and efficiency of parallel applications on super-large-scale *** the Sunway exascale prototype system as an example,in this paper we first analyze the challenges of high scalability and high efficiency for parallel applications in the exascale *** overcome these challenges,the optimization technologies used in the parallel supporting environment software on the Sunway exascale prototype system are highlighted,including the parallel operating system,input/output(I/O)optimization technology,ultra-large-scale parallel debugging technology,10-million-core parallel algorithm,and mixed-precision *** operating systems and I/O optimization technology mainly support largescale system scaling,while the ultra-large-scale parallel debugging technology,10-million-core parallel algorithm,and mixed-precision method mainly enhance the efficiency of large-scale ***,the contributions to various applications running on the Sunway exascale prototype system are introduced,verifying the effectiveness of the parallel supporting environment design.

关键词： parallel computing Sunway Ultra-large-scale Supercomputer

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Hybrid Approach to Optimize MPI Collectives by In-network-computation and Point-to-Point Messages 7

Hybrid Approach to Optimize MPI Collectives by In-network-co...

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7th International Conference on computer and Communication Systems, ICCCS 2022

作者： Chen, Shuping He, Wangquan Qi, Fengbin Zheng, Yan Yu, Kang National Research Center of Parallel Computer Engineering and Technology Bejing China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

Using in-network-computation capabilities of the network devices (also called hardware collectives) to optimize MPI collectives has become popular in high-performance computing, and shows significant performance advantages. However, the hardware collectives are not flawless in practical use scenarios. One of the problems is that it is difficult to use. In order to obtain the performance advantage of hardware collectives, the network management software need to create dedicated aggregate tree for each MPI communicator, which is a complicated task. One solution is to make MPI communicators sharing the global imprecise aggregate trees created by the management software when initiating networks, but it leads to heavy interference between MPI communicators and causes significant performance degradation. So we have to make tradeoff between performance and ease of use. We propose a hybrid approach to optimize MPI collectives by in-network-computation and point-to-point messages. On the one hand, we use the pre-created aggregate trees in each super-node, rather than sending requests to the network management software to create dedicated aggregate trees. On the other hand, the hardware collectives are transferred only in the local super-node, so it cannot disturb the jobs running on other super-nodes. We provide a cost model to evaluate the overhead of the hybrid collective algorithms. We also test its performance in the new generation Sunway supercomputer. The results show that our approach reduces the median latency by 18%~74% compared to collectives implemented by point-to-point messages, although the performance decrease slightly compared to the original hardware collectives. In addition, the tail latency of our approach is significantly lower than that of the original hardware collectives in the presence of heavy interference. © 2022 IEEE.

关键词： Aggregates

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Establishing a Modeling System in 3-km Horizontal Resolution for Global Atmospheric Circulation triggered by Submarine Volcanic Eruptions with 400 Billion Smoothed Particle Hydrodynamics 23

Establishing a Modeling System in 3-km Horizontal Resolution...

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2023 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2023

作者： Huang, Shenghong Chen, Junshi Zhang, Ziyu Hao, Xiaoyu Gu, Jun An, Hong Zhao, Chun Hu, Yan Wang, Zhanming Chen, Longkui Luo, Yifan Yao, Jineng Zhang, Yi Zhao, Yang Wang, Zhihao Jia, Dongning Jin, Zhao Song, Changming Luo, Xisheng He, Xiaobin Chen, Dexun Hefei China Laoshan Laboratory Qingdao China National Research Center of Parallel Computer Engineering and Technology Beijing China

ISBN: (纸本)9798400701092

People are increasingly concerned about how tectonic processes affect climate and vice versa. We establish a cross-sphere modeling system for volcanic eruptions and atmosphere circulation on a new Sunway supercomputer with a spatial resolution from 10m locally to 3km globally, using an improved multimedium and multiphase smoothed particle hydrodynamics (SPH) combined with a fully coupled meteorology-chemistry global atmospheric modeling scheme. We achieve 400 billion particles and 80% parallel efficiency using 39,000,000 processor cores. The simulation captures the whole dynamic process of the Tonga eruption from shock waves, earthquakes, tsunamis, mushroom clouds to the following 6 - 7 days of transport and diffusion of ash and water vapor, and preliminarily obtains the influence effect of full coupling of volcano, earthquake, ocean and atmosphere. This work is of great significance for deeply understanding the interaction between tectonic processes and climate change, and establishing an early warning simulation system for similar global hazard events. © 2023 ACM.

关键词： Supercomputers

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Towards Efficient Short-Range Pair Interaction on Sunway Many-Core Architecture

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Journal of computer Science & technology 2021年第1期36卷 123-139页

作者： Jun-Shi Chen Hong An Wen-Ting Han Zeng Lin Xin Liu School of Computer Science and Technology University of Science and Technology of ChinaHefei 230026China National Research Center of Parallel Computer Engineering and Technology Beijing 100080China

The short-range pair interaction consumes most of the CPU time in molecular dynamics(MD)*** inherent computation sparsity makes it challenging to achieve high-performance kernel on the emerging many-core *** this paper,we present a highly efficient short-range force kernel on the Sunway,a novel many-core architecture with many unique *** parallel efficiency of this algorithm on the Sunway many-core processor is strongly limited by the poor data locality and write *** enhance the data locality,we adopt a super cluster based neighbor list with an appropriate granularity that fits in the local memory of computing *** the absence of a low overhead locking mechanism,using data-privatization force array is a more feasible method to avoid write conflicts,but results in the large overhead of data *** adopt a dual-slice partitioning scheme for both hardware resources and computing tasks,which utilizes the on-chip data communication to reduce data reduction overhead and provide load ***,we exploit the single instruction multiple data(SIMD)parallelism and perform instruction reordering of the force kernel on this many-core *** experimental results show that the optimized force kernel obtains a performance speedup of 226x compared with the reference implementation and achieves 20%of peak flop rate on the Sunway many-core processor.

关键词： molecular dynamics sunway many-core pair interaction parallel algorithm

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Convolutional Neural Network Based Approach for Automatic Detection of Diseases from Pomegranate Plants 8

Convolutional Neural Network Based Approach for Automatic De...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Rana, Harsh Singh Manjunatha, N. Pokhare, Somnath S. Marathe, Rajiv A. Rajan, Jeny National Institute of Technology Karnataka Dept. of Computer Science and Engineering Surathkal India ICAR National Research Centre on Pomegranate Solapur India

ISBN: (纸本)9798350350593

Recent advancements in Artificial Intelligence, particularly Convolutional Neural Networks (CNNs), have significantly enhanced computer vision tasks, including plant disease detection. India is a global leader in pomegranate cultivation and production. Pomegranate is a vital horticultural commodity with significant export potential but is highly susceptible to various diseases, leading to substantial economic losses. Existing research on automatic pomegranate disease detection has limitations, as it typically analyzes either fruits or leaves in isolation and uses datasets with plain backgrounds that do not reflect real-world complexities such as lighting variations and overlapping foliage. This study proposes a novel hybrid deep learning approach that addresses these limitations. We utilized a hybrid CNN model specifically developed using the pomegranate dataset provided by the ICAR-national research centre on Pomegranate. This comprehensive collection includes 1,632 high-resolution images captured from orchards across India, categorized into three classes: healthy, bacterial diseases, and fungal diseases. Our model achieves an impressive accuracy rate of 98.46%, demonstrating its potential for real-world application in pomegranate disease detection and improved agricultural outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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A Simulation Study of n-ZnO/Perovskite/p-Cu2SnS3 Based Self-Powered Photodetector: Design and optimisation

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Materials research Innovations 2023年第7期27卷 503-510页

作者： Yadav, Sanjeev Mani Pandey, Amritanshu Department of Electronics and Computer Science National Institute of Advanced Manufacturing Technology Jharkhand Ranchi India Centre for Research in Microelectronics Department of Electronics Engineering IIT-BHU Varanasi India

Perovskite has been widely used in the field of optoelectronics owing to its superb optoelectronic properties. The simplest fabrication along with low-temperature handling of perovskite-based planner structures (p-i-n or n-i-p) has drawn their potential impact in organic–inorganic lead halide optoelectronic devices. The poor conductivity, stability, and high processing cost of absorber materials hinder the optical performance of the device. The sandwiching of the perovskite as absorber materials between two inorganic materials working as electron transport layer (ETL) and hole transport layer (HTL) may be a possible solution. An active absorber perovskite (CH3NH3PbI3) assisted by two n-ZnO and p-CTS materials working as an ETL and HTL, respectively, has been used to maximize the overall performance of the proposed device. The resultant optimized device shows the maximum responsivity of ∼0.35 (A/W) for a broad visible spectrum (300–900 nm), while the EQE (%) reported in the range of 25–80%. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Photodetectors

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