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共 140 条记录，以下是91-100 订阅

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Optimizing Depthwise Convolutions on ARMv8 Architecture 23rd

Optimizing Depthwise Convolutions on ARMv8 Architecture

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23rd international conference on Parallel and distributed computing, Applications, and Technologies, PDCAT 2022

作者： Hao, Ruochen Wang, Qinglin Yin, Shangfei Zhou, Tianyang Zhang, Qingyang Mei, Songzhu Shen, Siqi Liu, Jie Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410073 China College of Computer National University of Defense Technology Changsha410073 China Xiamen University Xiamen China

ISBN: (纸本)9783031299261

Depthwise convolutions are widely used in lightweight convolutional neural networks (CNNs). The performance of depthwise convolutions is mainly bounded by the memory access rather than the arithmetic operations for classic convolutions so that direct algorithms are often more efficient than indirect ones (matrix multiplication-, Winograd-, and FFT-based convolutions) with additional memory accesses. However, the existing direct implementations of depthwise convolutions on ARMv8 architectures feature a bad trade-off between register-level reuse of different tensors, which usually leads to sub-optimal performance. In this paper, we propose a new direct implementation of depthwise convolutions by means of implicit padding, register tiling, etc. Compared to the existing ones, our new implementations can incur much less communication overhead between registers and cache. Experimental results on two ARMv8 CPUs show that our implementation can averagely deliver 4.88 × performance improvement over the existing direct ones in open-source libraries. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Convolution

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Data Structures for Routing Table of the distributed Key-Value Store Based on Order Preserving Linear Hashing and Skip Graph with the Load Balancing Method

Data Structures for Routing Table of the Distributed Key-Val...

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Summer Virtual conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing (SNPD-Summer), ACIS international

作者： Ken Higuchi Ami Miyazaki Kenya Hasegawa Tatsuo Tsuji Center for Data Science and Artificial Intelligence University of Fukui Fkui Japan School of Engineering University of Fukui Fkui Japan

ISBN: (纸本)9798350396386

In this paper, data structures for reducing redundancy of routing information on the distributed key-value store based on order preserving linear hashing and Skip Graph with the load balancing method are proposed and evaluated. In this system, data are divided by order preserving linear hashing and Skip Graph is used for overlay network. For load balancing, by storing many Skip Graph nodes in one physical node, any highest-load Skip Graph can be divided. By this method, load balancing can be done. But the number of Skip Graph nodes becomes very many and redundant routing information exists. But this redundant routing information has regularity. In this paper, two types of data structure for reducing redundant routing elements are proposed. They are tree structure and array structure. By calculating space for them and searching time, the proposed data structures are experimentally evaluated.

关键词： Overlay networks Redundancy Routing Load management Arrays Artificial intelligence Software engineering

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Multi-GPU Scaling of a Conservative Weakly Compressible Solver for Large-Scale Two-Phase Flow Simulation 23rd

Multi-GPU Scaling of a Conservative Weakly Compressible So...

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23rd international conference on Parallel and distributed computing, Applications, and Technologies, PDCAT 2022

作者： Yang, Kai Aoki, Takayuki Department of Mechanical Engineering Tokyo Institute of Technology O-okayama Meguro-ku 2-12-1 i7-3 Tokyo152-8550 Japan Global Scientific Information and Computing Center Tokyo Institute of Technology O-okayama Meguro-ku 2-12-1 i7-3 Tokyo152-8550 Japan

ISBN: (纸本)9783031299261

To address the demand for high-performance large-scale simulation of two-phase flows, a momentum-conserving weakly compressible Navier-Stokes solver with multi-GPU computation is proposed. Following the principle of consistent transport, the phase-field model and VOF method are coupled with the momentum equation respectively. Combined with the evolving pressure projection method to damp the acoustic wave, this solver aims at a robust and accurate computation of violent two-phase flows with a high density ratio, while taking advantage of fully explicit time integration of the weakly compressible Navier-Stokes equations. Factors affecting the performance and scalability of multi-GPU computing, including domain partitioning, communication hiding, and solver choice, are discussed and analyzed. Finally, the conservative solver is used to simulate the Rayleigh-Taylor instability, milk crown and liquid jet atomization problems. Accurate and delicate evolution process of the two-phase interface is demonstrated. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Two phase flow

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Improving the Performance of Lattice Boltzmann Method with Pipelined Algorithm on A Heterogeneous Multi-zone Processor 23rd

Improving the Performance of Lattice Boltzmann Method with...

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23rd international conference on Parallel and distributed computing, Applications, and Technologies, PDCAT 2022

作者： Zhang, Qingyang Xu, Lei Chen, Rongliang Chen, Lin Chen, Xinhai Wang, Qinglin Liu, Jie Yang, Bo Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha410000 China Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha410000 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9783031299261

Lattice Boltzmann method (LBM) has become a powerful method in computational fluid dynamics and has drawn more and more attention in high-performance computing due to its particulate nature and local dynamics, especially on recent multi-core or many-core platforms. This paper develops a parallel software framework for 3D LBM simulation on a heterogeneous multi-zone processor, MT-3000. An improved pipelined algorithm named Pencil-H is proposed, which can not only fully exploit the advantages of each component of MT-3000 but also overlap the time of calculation and communication. Moreover, an architecture-aware multi-level parallelization algorithm is developed to fully utilize the computational performance of MT-3000. A benchmark test is performed to verify the reliability and test the performance of the LBM code. Experimental results show that the optimized code achieves a 32.02 × speedup compared with using 16 CPU cores and achieves a performance of 286.03MLUPS which reaches 72.3% of the theoretical peak performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational fluid dynamics

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Boosting Bandwidth Convergence: Optimizing Resource Allocation in Satellite-Terrestrial Integrated Networks 23

Boosting Bandwidth Convergence: Optimizing Resource Allocati...

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23rd IEEE international conference on Communication Technology, ICCT 2023

作者： Li, Dongbo Zhang, Jiajun Tian, Puyang Yin, Zhisheng Cheng, Siyao Liu, Jie Harbin Institute of Technology IoT and Ambient Intelligence Research Center Faculty of Computing Harbin China International Research Institute for Ai Harbin Institute of Technology Shenzhen Cyber-Physical Systems Research Center Shenzhen China School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China School of Communication Engineering Xidian University Xi'an China International Research Institute for Ai Harbin Institute of Technology Shenzhen Shenzhen China

ISBN: (纸本)9798350325959

Satellite-Terrestrial Integrated Network (STIN) is a multidimensional network that integrates satellites and terrestrial netwoks, providing information services globally. However, facing time-varying network topology and transmission resources, STIN is limited by the uneven network resources in each network segment. Therefore, it is difficult for STIN to achieve optimal network performance during data transmission. In response to the above challenges, this paper proposes a soft-defined STIN based multipath selection and resource allocation method. We build a soft-defined network architecture for STIN, establish satellite-terrestrial dynamic network topology, and deploy distributed controller nodes. The proposed method models multiple factors that affect throughput performance in the network as a link transmission cost matrix, defining bandwidth resources, computing resources, and latency parameters for modeling. Finally, construct the optimal resource objective function for soft-defined STIN. Meanwhile, we propose a Boosting Bandwidth Convergence (BBC) method. This method merges all transmission paths using a recursive method, and obtains the optimal objective function solution. STK, Mininet, and Ryu are adopted as a joint simulation platform to simulate the three-layer network architecture of soft-defined STIN. The simulation results show that the proposed method outperforms default Ryu switch algorithm and Shortest Path Bridging (SPB) algorithm in terms of throughput, even in the presence of network interference. It exhibits comparable average delay but maintains consistent delay throughout the transmission process, unlike the fluctuating delays observed in the other two algorithms due to buffer accumulation. © 2023 IEEE.

关键词： resource allocation Satellite-Terrestrial Integrated Network soft-defined network throughput

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Assembly code translation from ARM64 to RISC-V

Assembly code translation from ARM64 to RISC-V

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Summer Virtual conference on Software Engineering, Artificial Intelligence, networking and Parallel/distributed computing (SNPD-Summer), ACIS international

作者： Tatsuya Tsuchiya Kanemitsu Ootsu Takashi Yokota Shun Kojima Graduate School of Regional Development and Creativity Utsunomiya University Utsunomiya Tochigi Japan

ISBN: (纸本)9798350396386

SIMD instruction-based processing is effective in speeding up highly data-parallel processing such as image recognition. However, processing using the SIMD instruction set requires reconstructed the machine code when changing the number of computing units. Therefore, we have developed RISC-V with vector extensions, a scalable vector extension that can change the number of concurrent parallel operations without changing the machine code, referring to the ARM SVE. There is a problem that RISC-V vectorized machine code cannot be generated due to the lack of a compiler that supports vector extensions. The solution to this problem is to use the assembly code generated by the vectorization compiler for ARM SVE to generate assembly code for RISC-V with vector extensions. By assembling it, we generate RISC-V vectorization machine code. As the first step of implementation, we implement an assembly code translator that performs assembly code translation between the basic instruction set from ARM64 to RISC-V. Since the translated RISC-V program could be executed, it was confirmed that the translation proposed in this study was performed properly.

关键词： Codes Reduced instruction set computing Image recognition Artificial intelligence Image reconstruction Software engineering

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A Novel Maritime Edge computing System for Internet of Vessels 23

A Novel Maritime Edge Computing System for Internet of Vesse...

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23rd IEEE international conference on Communication Technology, ICCT 2023

作者： Lyu, Tengxiao Dou, Xinyu Ren, Xiaohan Ma, Teng Lin, Bin School of Information Science and Technology Dalian Maritime University Dalian China

ISBN: (纸本)9798350325959

In this paper, a novel maritime edge computing system is proposed and demonstrated. In the proposed system, a cloud-edge-end architecture is deployed, and computing functions are included at both the 'edge' and 'end' sides. Therefore, the computing capabilities of the edge computing system are enhanced by increasing the number of computing nodes and assigning tasks to different computing locations. The system adopts Unmanned Surface Vehicles (USVs) and buoys as the edge computing carriers at the 'end' side, and they are equipped with video acquisition cameras, hydrological information sensors, supporting edge computing units and communication units to enable information collection, computation and task uploading. At the same time, the 'edge' refers to the shore and islands near the USV, and is equipped with more powerful edge computing and communication units to realize the collection and computation of the broadband data that cannot be computed at the 'end' side, as well as uploading computing results to the cloud. Finally, the 'cloud' is the client which centrally displays the real-time video information, hydrological information and computing results from both the 'edge' and 'end' sides to provide the support for decision makers. In addition, communication units in the proposed system can establish a flexible communication network to ensure that the nodes in the edge computing system are always online, which provides a guarantee for information transmission. Finally, we trained the edge computing unit of the system and implemented field experiments on multi-object identification under various scenarios to verify the feasibility of the system. The system can provide new solutions for maritime rescue and exploration, and has an important significance on ocean digitization and intelligence. © 2023 IEEE.

关键词： cloud-edge-end computing architecture flexible networking maritime edge computing multi-objective identification

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A System-Wide Communication to Couple Multiple MPI Programs for Heterogeneous computing 23rd

A System-Wide Communication to Couple Multiple MPI Programs...

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23rd international conference on Parallel and distributed computing, Applications, and Technologies, PDCAT 2022

作者： Sumimoto, Shinji Arakawa, Takashi Sakaguchi, Yoshio Matsuba, Hiroya Yashiro, Hisashi Hanawa, Toshihiro Nakajima, Kengo The University of Tokyo Kashiwa Japan CliMTech Inc. Funabashi Japan Fujitsu Ltd. Tokyo Japan Hitachi Ltd. Tokyo Japan National Institute for Environmental Studies Tsukuba Japan RIKEN CCS Kobe Japan

ISBN: (纸本)9783031299261

This paper proposes a system-wide communication library to couple multiple MPI programs for heterogeneous coupling computing called h3-Open-SYS/WaitIO-Socket (WaitIO-Socket for short). WaitIO-Socket provides an inter-program communication environment among MPI programs and supports different MPI libraries with various interconnects and processor types. We have developed the WaitIO-Socket communication library and tested it on the Wisteria/BDEC-01 supercomputing system, including Odyssey (Fujitsu A64FX-aarch64/Fujitsu-MPI/Tofu) and Aquarius (Intel Xeon-x86_64+NVIDIA-A100/Intel MPI/InfiniBand). As a result of the evaluation, WaitIO-Socket can execute large-scale programs on the Wisteria system, our first target system. The Odyssey and Aquarius MPI programs are able to communicate using WaitIO-Socket and achieve 53.2 GB/s using multiple streams throughout the system. We also show that the application NICAM/ADA is able to run with the h3-Open-UTIL/MP coupler 35% faster on the combination of Odyssey with Arm CPU and Aquarius with NVIDIA GPU than Odyssey with Arm CPU. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Deep learning

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Client Scheduling for Unreliable Semi-Decentralized Federated Learning 23

Client Scheduling for Unreliable Semi-Decentralized Federate...

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23rd IEEE international conference on Communication Technology, ICCT 2023

作者： Tan, Yuhao Zhao, Haitao Xia, Wenchao Wang, Qin Guo, Kun Xu, Bo Quek, Tony Q. S. Nanjing University of Posts and Telecommunications Jiangsu Key Laboratory of Wireless Communications Nanjing210003 China Chongqing Institute of East China Normal University Chongqing Key Laboratory of Precision Optics Chongqing401120 China Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore

ISBN: (纸本)9798350325959

The Industrial Internet of Things (IIoT) is emerging as a promising technology that can accelerate the application of industrial intelligence. Because of the sensitive nature of user data, federated learning (FL) which performs distributed machine learning while preserving data privacy, is developed to meet the accuracy and privacy requirements of IIoT end devices/clients. However, the unreliable communications in IIoT may negatively affect the training efficiency. In this paper, we study on the client scheduling problem in a multi-server FL framework for the communication reliability and training efficiency improvement. A client-server association optimization problem is formulated, with the objective of minimizing the global training loss. Resorting to the convergence analysis of SD-FL, the original problem is simplified and transformed to guide us to design a high-efficiency client scheduling scheme. Finally, simulation results show that the proposed scheme significantly outperforms the baselines in terms of the test accuracy and training loss. © 2023 IEEE.

关键词： client scheduling edge association edge computing federated learning industrial internet of things

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Exposing IoT Platforms Securely and Anonymously Behind CGNAT

Exposing IoT Platforms Securely and Anonymously Behind CGNAT

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Roedunet international conference (RoEduNet)

作者： Daniel-Florin Hriţcan Doru Balan Dept. of Computers Automation and Electronics University “Stefan cel Mare” Suceava Suceava Romania

ISBN: (数字)9798331540388

ISBN: (纸本)9798331540395

The swift expansion of Internet of Things (IoT) devices has resulted in considerable progress in connectivity and automation, yet it has simultaneously brought about notable security weaknesses. This paper presents a novel approach to securing IoT platforms through a comprehensive architecture that integrates a double reverse proxy setup, leveraging Oracle Cloud Virtual Private Servers (VPS), NGINX Proxy Manager, Cloudflare, and Tailscale encrypted peer-to-peer (P2P) tunneling. The proposed solution employs Oracle Cloud VPS to host and manage IoT applications, ensuring robust performance and scalability. NGINX Proxy Manager is utilized to facilitate efficient and secure load balancing and reverse proxy functions. Cloudflare provides additional security layers, including distributed Denial of Service (DDoS) protection, SSL/TLS encryption, and traffic management. To further enhance security, the encryption of Tailscale P2P tunneling creates a secure mesh network between devices, ensuring data integrity and confidentiality. This architecture not only fortifies the security posture of IoT platforms but also improves the resilience and reliability of data transmission.

关键词： Cloud computing Scalability Tunneling Encryption Peer-to-peer computing Internet of Things Servers Reliability Computer crime Resilience

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