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15th National Conference of Operational and Systems Research, BOS 2018 and 17th International Workshop on Intuitionistic Fuzzy Sets and General Nets, IWIFSGN 2018

作者： Czerniak, Jacek M. Zarzycki, Hubert Ewald, Dawid Augustyn, Piotr Department of Computer Science Casimir the Great University in Bydgoszcz ul. Chodkiewicza 30 Bydgoszcz85-064 Poland University of Information Technology and Management Copernicus ul. Inowroclawska 56 Wroclaw53-648 Poland

ISBN: (纸本)9783030470234

In the article, the authors propose a new optimization method inspired directly by the behavior of the Duroc pig herd, which was bred in New England. the new metaheuristics called Artificial Duroc Pigs Optimization (ADPO) is an example of the successful implementation of Ordered Fuzzy Numbers into a swarm optimization method. the notation of OFN is suitable for describing the behavior of the pig herd in the article. the experiments were carried out for eight benchmark functions with many extremes. For comparison, experiments with PSO, BA and GA methods were carried out on the same functions. In most tests, the results obtained by ADPO were the best. © 2021, Springer Nature Switzerland AG.

关键词： Fuzzy logic

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AoI Aware VNF Scheduling with Parallel Transmission for Delay-Sensitive Applications

AoI Aware VNF Scheduling with Parallel Transmission for Dela...

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IEEE International Conference on high performance computing and Communications (HPCC)

作者： Lingjie Yu Long Qu Faculty of EECS Ningbo University Ningbo China

For delay-sensitive network services, Age of Information (AoI) is appropriate to represent the freshness of information. Meanwhile, with the joint development of Network Function Virtualization (NFV) and Software Defined Network (SDN) technology, these network services can be managed as Service Function Chains (SFCs), composed of a collection of Virtual Network Functions (VNFs). Because the standard SFC architectures have been challenging to accommodate the low AoI demand for information in new scenarios like the Industrial Internet of things (IIoT) and telemedicine, new SFC structures are constantly being proposed. In this paper, AoI is minimized by utilizing parallel paths to forward data between VNF instances. We formulate it as an Integer Linear Programming (ILP) problem. Moreover, a heuristic algorithm based on Particle Swarm Optimization (PSO) is proposed to solve it in large-scale networks. According to the simulation results analysis, our strategy can reduce the overall AoI of flows by at least 15% when compared to the conventional SFC architectures.

关键词： Job shop scheduling Smart cities Service function chaining Simulation Telemedicine computer architecture Routing

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A Data Download Scheme Based on Vehicle Mobile Information in Internet of Vehicles 15th

A Data Download Scheme Based on Vehicle Mobile Information i...

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15th China Conference on Wireless Sensor Networks (CWSN)

作者： Sun, Yabo Shi, Lei Bi, Xiang Ding, Xu Wei, Zhenchun Hefei Univ Technol Sch Comp Sci & Informat Engn Intelligent Interconnected Syst Lab Anhui Prov Hefei 230009 Peoples R China Minist Educ Engn Res Ctr Safety Crit Ind Measurement & Contro Hefei 230009 Peoples R China

ISBN: (纸本)9789811681745;9789811681738

Due to the high mobility and limited transmission range of vehicles, the data download capacity of single vehicle is greatly limited, which brings poor performance to users. In this paper, we divide the data into blocks. We want to design a data block broadcasting scheme so that all vehicles can receive data blocks as many as possible in a base station(BS) range. We first give the mathematical model and find it is difficult to be solved directly. then we design a heuristic algorithm for solving the problem. the main idea of our algorithm is to give each data block a weight. the data block with the largest weight is broadcast by BS, and several vehicles are selected to broadcast the remaining data blocks. We call our algorithm as the Iterative Strategy for Data Allocation(ISDA) algorithm. then considering the actual situation, we subsequently propose the online algorithm. through experiments and simulations, we prove that our scheme can effectively improve the data download rate and reduce the download delay.

关键词： Data downloading Cooperative communication Edge computing Internet of vehicles

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SOFF: An OpenCL high-Level Synthesis Framework for FPGAs 20

SOFF: An OpenCL High-Level Synthesis Framework for FPGAs

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47th ACM/IEEE Annual International symposium on computer architecture (ISCA)

作者： Jo, Gangwon Kim, Heehoon Lee, Jeesoo Lee, Jaejin ManyCoreSoft Seoul 08826 South Korea Seoul Natl Univ Dept Comp Sci & Engn Seoul 08826 South Korea

ISBN: (纸本)9781728146614

Recently, OpenCL has been emerging as a programming model for energy-efficient FPGA accelerators. However, the state-of-the-art OpenCL frameworks for FPGAs suffer from poor performance and usability. this paper proposes a high-level synthesis framework of OpenCL for FPGAs, called SOFF. It automatically synthesizes a datapath to execute many OpenCL kernel threads in a pipelined manner. It also synthesizes an efficient memory subsystem for the datapath based on the characteristics of OpenCL kernels. Unlike previous high-level synthesis techniques, we propose a formal way to handle variable-latency instructions, complex control flows, OpenCL barriers, and atomic operations that appear in real-world OpenCL kernels. SOFF is the first OpenCL framework that correctly compiles and executes all applications in the SPEC ACCEL benchmark suite except three applications that require more FPGA resources than are available. In addition, SOFF achieves the speedup of 1.33 over Intel FPGA SDK for OpenCL without any explicit user annotation or source code modification.

关键词： Accelerator architectures FPGAs high level synthesis parallel programming pipeline processing

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基于国产处理器的智能大数据一体机架构及应用研究

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南京邮电大学学报（自然科学版） 2024年第4期44卷 1-16页

作者：陈国良汤晓宇尤帅姚小良梅超君林时俊刘尚东吴少刚孙雅薇王汝传季一木南京邮电大学计算机学院江苏南京210023 南京邮电大学高性能计算与大数据处理研究所江苏南京210023 国家高性能计算中心南京分中心江苏南京210023 龙芯中科技术股份有限公司北京101111 北方信息控制研究院集团有限公司江苏南京211153

分析比较国内外智能芯片产品现状,概述智能芯片的相关软硬件技术栈,针对国内大数据与人工智能产业支撑体系尚不完善、尚未建立国产化信息处理安全保障体系的问题,提出基于国产芯片自主研发的智能大数据一体机研究与设计。解决基础设施... 详细信息

分析比较国内外智能芯片产品现状,概述智能芯片的相关软硬件技术栈,针对国内大数据与人工智能产业支撑体系尚不完善、尚未建立国产化信息处理安全保障体系的问题,提出基于国产芯片自主研发的智能大数据一体机研究与设计。解决基础设施的运维部署、海量数据存储以及时效性处理等问题,通过对比异构计算系统的分析研究,文中提出的基于国产CPU和NPU异构硬件加速的一体化计算平台具有信息安全、领域普适性强、运行效率高等特点。

关键词：国产芯片大数据一体机大数据处理智能计算信息安全

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Optimization Techniques for Scheduling IoT tasks in Fog-based Environments

Optimization Techniques for Scheduling IoT tasks in Fog-base...

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International symposium on high Capacity Optical Networks and Enabling Technologies, HONET

作者： Rija Tariq Hareem Ashraf Maira Sohail Hasan Ali Khattak School of Electrical Engineering and Computer Science National University of Sciences and Technology (NUST) Islamabad Pakistan

ISBN: (纸本)9781665461986

Cloud computing has been around us for a while now, and everywhere we look around, data surrounds us. Data is transferred over a network and computed over some cloud platform. the concept of the fog layer has also been around, and there have been multiple implementations of how these two sets of layers can work together and implement an excellent and optimized structure. Numerous factors are involved in creating an architecture like that, including time, energy, network bandwidth, etc. Every solution presented tries to cater to most of these factors and gives the best possible outcome. But there has been a trade-off always. Such architecture has been here for many years. these solutions and many new ones are implemented to find a common optimal point. Such solutions can be divided into categories like bio-inspired algorithms, evolution-based algorithms, etc. there can also be a division based on these algorithms' heuristic and metaheuristic nature. this paper focuses on all these techniques and compares the objectives and limitations of previous implementations. this paper also pointed out majorly used algorithms repeatedly seen during this research and simulated on the same set of parameters to determine which solution presents a more efficient performance.

关键词： Cloud computing Costs Processor scheduling Smart cities Heuristic algorithms Metaheuristics computer architecture

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Practical error modeling toward realistic NISQ simulation 19

Practical error modeling toward realistic NISQ simulation

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19th IEEE-computer-Society Annual symposium on VLSI (ISVLSI)

作者： Tanimoto, Teruo Matsuo, Shuhei Kawakami, Satoshi Tabuchi, Yutaka Hirokawa, Masao Inoue, Koji Kyushu Univ Nishi Ku 744 Motooka Fukuoka 8190395 Japan Univ Tokyo Meguro Ku 4-6-1 Komaba Tokyo 1538904 Japan

ISBN: (数字)9781728157757

ISBN: (纸本)9781728157757

In quantum computing, research and development of devices, architecture, optimization techniques, algorithms, and applications are evolving with eagerness in parallel. To make these work mutually beneficial, practical and accurate quantum computer simulators as system-wide design frameworks are necessary. In this paper, we focus on measurement and initialization errors of qubits. these errors are inevitable because these procedures are interfaces between classical and quantum information processing. We model the quantum non-demolition detection technique as measurement and initialization methods and implement them on Intel-QS, a high-performance quantum simulator. Our case study with quantum Fourier transform on 8 qubits configuration demonstrates the importance of taking these errors into account. that is, post-selection, which improves the initialization fidelity, can enlarge the gap between the theoretical result and incorrect outputs by 3.35 times.

关键词： Measurement uncertainty Quantum computing Computational modeling Logic gates Measurement errors computer architecture Noise measurement

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Texture Blending for Photorealistic Composition on Mobile AR Platform

Texture Blending for Photorealistic Composition on Mobile AR...

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International symposium on Medical Information & Communication Technology (ISMICT)

作者： Guilin Li Pan Chen Shihui Guo School of Informatics Xiamen University Xiamen China

this work establishes a client-cloud collaborative computing framework, realizing the augmented reality synthesis of photos on the mobile platform. this framework solves the bottleneck of unrealistic image rendering caused by the insufficient computing power of mobile hardware in augmented reality synthesis. On the client side, a real-time preview function is provided for users to perceive the final result. On the cloud side, a complete rendering pipeline with high computing is used to achieve highly realistic picture rendering and composition. On the basis of augmenting reality, this framework increases the interaction between humans and virtual models. We propose a method to integrate user interaction input and image semantic information to solve the limitation of inaccurate estimation of depth information in distant area. Finally, this work takes the augmented reality display of virtual cherry tree as an example to build a sample program. the result shows that the framework is of high practicability and can automatically compose highly realistic photos.

关键词： Solid modeling Cloud computing three-dimensional displays Semantics Lighting Collaboration Rendering (computer graphics)

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FPGA-Based Computational Fluid Dynamics Simulation architecture via high-Level Synthesis Design Method 16th

FPGA-Based Computational Fluid Dynamics Simulation Architect...

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16th International symposium on Applied Reconfigurable computing

作者： Du, Changdao Firmansyah, Iman Yamaguchi, Yoshiki Univ Tsukuba Tsukuba Ibaraki 3058577 Japan

ISBN: (纸本)9783030445331;9783030445348

Today's high-performance computing (HPC) systems often use GPUs as dedicated hardware accelerators to meet the computation requirements of applications such as neural networks, genetic decoding, and hydrodynamic simulations. Meanwhile, FPGAs have also been considered as alternative suitable hardware accelerators due to their advancing computational capabilities and low power consumption. Moreover, the developments of high-Level Synthesis (HLS) allow users to generate FPGA designs directly from mainstream languages, e.g., C, C++, and OpenCL. However, writing efficient high-level programs with good performance is still a time-consuming task, and the lack of knowledge about FPGA architecture can lead to poor scalability and portability. In this paper, we propose an architecture design for Computational Fluid Dynamics (CFD) simulations based on the HLS method. Our design can adjust the performance by utilizing the parallelism inside both temporal and spatial domains of CFD simulations. We also discuss the data reuse buffer optimization choices while considering the potability of HLS codes. A performance model is introduced to guide the design space exploration under the constraints of available resources on FPGA. We evaluate our design via a Xilinx VCU1525 FPGA board and compare the results with other state-of-the-art studies. Experiment results show that VCU1525 can achieve 629.6 GFLOP/s in D2Q9 LBM-BGK model and the design and optimization methods can be used for developing various CFD applications.

关键词： HPC FPGA HLS CFD

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On the performance of Deep Learning Models for Time Series Classification in Streaming 15th

On the Performance of Deep Learning Models for Time Series C...

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15th International Conference on Soft computing Models in Industrial and Environmental Applications, SOCO 2020

作者： Lara-Benítez, Pedro Carranza-García, Manuel Martínez-Álvarez, Francisco Riquelme, José C. Division of Computer Science University of Sevilla Seville41012 Spain Data Science & Big Data Lab Pablo de Olavide University Seville41013 Spain

ISBN: (纸本)9783030578015

Processing data streams arriving at high speed requires the development of models that can provide fast and accurate predictions. Although deep neural networks are the state-of-the-art for many machine learning tasks, their performance in real-time data streaming scenarios is a research area that has not yet been fully addressed. Nevertheless, there have been recent efforts to adapt complex deep learning models for streaming tasks by reducing their processing rate. the design of the asynchronous dual-pipeline deep learning framework allows to predict over incoming instances and update the model simultaneously using two separate layers. the aim of this work is to assess the performance of different types of deep architectures for data streaming classification using this framework. We evaluate models such as multi-layer perceptrons, recurrent, convolutional and temporal convolutional neural networks over several time-series datasets that are simulated as streams. the obtained results indicate that convolutional architectures achieve a higher performance in terms of accuracy and efficiency. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

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