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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Qiu, Yanlong Wang, Siqi Yang, Xi Qiu, Xinyuan Wu, Chengkun Cui, Yingbo Yang, Canqun National University of Defense Technology Institute for Quantum Information State Key Laboratory of High-Performance Computing College of Computer Science Hunan Changsha410073 China National Supercomputer Center in Tianjin Tianjin300457 China National University of Defense Technology National Key Laboratory of Parallel and Distributed Computing College of Computer Science Hunan Changsha410073 China National University of Defense Technology Department of Biology and Chemistry College of Science Hunan Changsha410073 China

ISBN: (纸本)9798350337488

With the exponential growth of biomedical knowledge in unstructured text repositories such as PubMed, it is imminent to establish a knowledge graph-style, efficient searchable and targeted database that can support the need of information retrieval from researchers and clinicians. To mine knowledge from graph databases, most previous methods view a triple in a graph (see Fig. 1) as the basic processing unit and embed the triplet element (i.e. drugs/chemicals, proteins/genes and their interaction) as separated embedding matrices, which cannot capture the semantic correlation among triple elements. To remedy the loss of semantic correlation caused by disjoint embeddings, we propose a novel approach to learn triple embeddings by combining entities and interactions into a unified representation. Furthermore, traditional methods usually learn triple embeddings from scratch, which cannot take advantage of the rich domain knowledge embedded in pre-trained models, and is also another significant reason for the fact that they cannot distinguish the differences implied by the same entity in the multi-interaction triples. In this paper, we propose a novel fine-tuning based approach to learn better triple embeddings by creating weakly supervised signals from pre-trained knowledge graph embeddings. The method automatically samples triples from knowledge graphs and estimates their pairwise similarity from pre-trained embedding models. The triples are then fed pairwise into a Siamese-like neural architecture, where the triple representation is fine-tuned in the manner bootstrapped by triple similarity scores. Finally, we demonstrate that triple embeddings learned with our method can be readily applied to several downstream applications (e.g. triple classification and triple clustering). We evaluated the proposed method on two open-source drug-protein knowledge graphs constructed from PubMed abstracts, as provided by BioCreative. Our method achieves consistent improvement in both t

关键词： Drug-Protein Interaction Knowledge Graph Embedding Triple Embedding Weakly Supervised Learning

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A high-performance computational resource broker for grid computing environments

A high-performance computational resource broker for grid co...

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Chao-Tung Yang Po-Chi Shih Kuan-Ching Li High-Performance Computing Laboratory Department of Computer Science and Tunghai University Taichung Taiwan Parallel and Distributed Processing Center Department of Computer Science and Information Management Providence University Taichung Taiwan

ISBN: (纸本)0769522491

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. As grid computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user's needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user's credentials. The resource broker runs on top of the Globus toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the grid.

关键词： Grid computing Resource management Bandwidth distributed computing Network servers Monitoring Information security Middleware Access protocols Java

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F3A: Fairness-Aware AI-Workloads Allocation Considering Multidimensional User Demands in JointCloud

F3A: Fairness-Aware AI-Workloads Allocation Considering Mult...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Jiacheng Yang Guodong Yi Fei Gao Peichang Shi Huaimin Wang National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

With the rapid growth of large language models, cloud computing has become an indispensable component of the AI industry. Cloud service providers(CSPs) are establishing AI data centers to service AI workloads. In the face of this surging need for AI computing power, building a connected computing environment across various clouds and forming a JointCloud presents an attractive solution. However, scheduling AI tasks across multiple AI data centers within a JointCloud environment presents a significant challenge: how to balance users’ demands while ensuring CSPs’ fairness in scheduling. Existing research primarily focuses on optimizing scheduling quality with limited consideration for fairness. Therefore, this paper proposes a Fairness-Aware AI-Workloads Allocation method (F3A), a fair cross-cloud allocation technique for AI tasks. F3A utilizes Point and Token to reflect both the resource status and historical task allocations of AI data centers, enabling the consideration of users’ multidimensional demands and facilitating fair task allocation across multiple centers. In order to better assess the fairness of scheduling, we also devised a fairness indicator(FI), based on the Gini coefficient to measure the fairness of task allocation. The experimental results demonstrate that F3A consistently maintains FI within 0.1 across various cluster sizes and different task quantities, representing an improvement of 76.45% compared to classical fair scheduling algorithms round-robin. F3A exhibits commendable performance in ensuring fairness in task allocation while also demonstrating effectiveness in cost reduction and enhancing user satisfaction.

关键词： Industries Data centers Cloud computing Job shop scheduling Costs Scheduling algorithms Large language models

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Breaking up is hard to do - Dispersion: from design to implementation

Breaking up is hard to do - Dispersion: from design to imple...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： M. Isaacs M. Anderson S. Ashworth J. Blackburn-Lynch B. Bynum J. Pearce C. Pemberton Department of Mathematics and Computer Science Berea College Mobile Robotics and Parallel Processing Laboratory Berea KY USA Center for Distributed Robotics University of Minnesota Minneapolis MN USA

This article assesses the performance of a virtual pheromone-based sectored dispersion algorithm which is implemented on a low-cost miniature mobile robotic platform using sonar sensing. The approach is a distributed one and the robotic platform and sensor array are sufficiently inexpensive that they can be employed in undergraduate research and/or for coursework in a small college environment

关键词： Educational robots Robot sensing systems Mobile robots Sensor arrays Service robots parallel robots Hardware Mobile computing Educational institutions Dispersion

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An Effective Design to Improve the Efficiency of DPUs on FPGA

An Effective Design to Improve the Efficiency of DPUs on FPG...

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International Conference on parallel and distributed Systems (ICPADS)

作者： Yutian Lei Qingyong Deng Saiqin Long Shaohui Liu Sangyoon Oh The Key Laboratory of Hunan Province for Internet of Things and Information Security The School of Computer Science Science and Technology on Parallel and Distributed Processing Laboratory Xiangtan University Xiangtan China The Artificial Intelligence Center PengCheng Laboratory shenzhen China Ajou University Suwon-si Republic of Korea

The following topics are dealt with: cloud computing; learning (artificial intelligence); resource allocation; security of data; mobile computing; neural nets; optimisation; parallel processing; scheduling; and storag... 详细信息

ISBN: (数字)9781728190747

ISBN: (纸本)9781728183824

关键词： Deep learning Schedules Multicore processing Logic gates Throughput Acceleration Field programmable gate arrays

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parallel 3D deterministic particle transport on Intel MIC architecture

Parallel 3D deterministic particle transport on Intel MIC ar...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Qinglin Wang Zuocheng Xing Jie Liu Xiaogang Qiang Chunye Gong Jiang Jiang Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China H.H. Wills Physics Laboratory University of Bristol Bristol UK Science and Technology on Space Physics Libratory Beijing China School of Microelectronics Shanghai Jiao Tong University Shanghai China

Single-node computation speed is essential in large-scale parallel solutions of particle transport problems. The Intel Many Integrated Core (MIC) architecture supports more than 200 hardware threads as well as 512-bit double precision float-point vector operations. In this paper, we use the native model of MIC in the parallelization of the simulation of one energy group time-independent deterministic discrete ordinates particle transport in 3D Cartesian geometry (Sweep3D). The implementation adopts both hardware threads and vector units in MIC to efficiently exploit multi-level parallelism in the discrete ordinates method when keeping good data locality. Our optimized implementation is verified on target MIC and can provide up to 1.99 times speedup based on the original MPI code on Intel Xeon E5-2660 CPU when flux fixup is off. Compared with the prior on NVIDIA Tesla M2050 GPU, the speedup of up to 1.23 times is obtained. In addition, the difference between the implementations on MIC and GPU is discussed as well.

关键词： Computer architecture Microwave integrated circuits Graphics processing units Tin Computational modeling Legged locomotion Equations

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Design of an Indoor Exploration and Multi-Objective Navigation System

Design of an Indoor Exploration and Multi-Objective Navigati...

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第37届中国控制会议

作者： Guoxian Zheng Lei Zhang Huaxi (Yulin) Zhang Bo Ding State Key Laboratory of Synthetical Automation for Process Industries Northeastern University MIS and INSSET Universite de Picardie Jules Verne National Laboratory for Parallel and Distributed Processing National University of Defense Technology

In this paper,we propose an indoor robot autonomous navigation *** robot firstly explores in an unknown environment,and then navigates autonomously by using the explored *** robot is equipped a 2 D laser scanner as the main *** laser scanner is used for path planning and frontier-based exploration.A 2 D global occupancy map is built for path planning,frontier-based exploration and multi-objective autonomous *** scans are transmitted into Simultaneous Localization and Mapping（SLAM） process in the exploration *** indoor environment,the exploration efficiency is improved by merging a heuristic *** using multi-threading technology and a 3 D perception approach proposed in this paper,the robot equipped with a low-cost RGBD sensor can detect all kinds of obstacles to achieve highly reliable navigation in complicated 3 D ***,we develop a multi-objective navigation application to make human-robot interaction more convenient and satisfy multi-task *** approaches are demonstrated by experimental results.

关键词： Exploration Heuristic algorithm multi-threading technology 3D Perception Multi-objective navigation

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A Semiautomatic Method to Achieve Independent and Intact Gene Ontology Slim (InitGO) and its Cytoscape Plugin Implementation

A Semiautomatic Method to Achieve Independent and Intact Gen...

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International Conference on BioMedical Engineering and Informatics (BMEI)

作者： Qijun Liu Zhenghua Wang Hanchang Sun Hao Guo Wanlin Liu Yunping Zhu National Laboratory of Parallel & Distributed Processing National University of Defence Technology Changsha China State Key Laboratory of Proteomics Beijing Proteome Research Center Beijing Institute of Radiation Medicine Beijing China

To conduct a systemic analysis of biological networks function distribution and function modules, we present a semiautomatic method to achieve independent and intact GO slim (InitGO) based on graph operations and GO hierarchy structure. Our method is packed into a user-friendly Cytoscape plugin named InitGO. The application of InitGO to yeast transcriptional factors regulatory network shows that the network has function modularity, offering evidence that our method is effective for defining function modules. InitGO plugin and source codes are available on request from the authors.

关键词： Ontologies Biological information theory Independent component analysis Fungi Data visualization Systems biology Bioinformatics Laboratories distributed processing Transfer functions

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DCSA: The Deployment Mechanism of Chained Serverless Applications in JointCloud Environment

DCSA: The Deployment Mechanism of Chained Serverless Applica...

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IEEE International Conference on Joint Cloud Computing (JCC)

作者： Yaojie Li Peichang Shi Jianfei Liu Rui Li Fei Gao Penghui Ma Dong Xie Guodong Yi National Key Laboratory of Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China Xiangjiang Lab Changsha China School of Advanced Interdisciplinary Studies Hunan University Of Technology and Business Changsha China

ISBN: (数字)9798350387339

ISBN: (纸本)9798350387346

Serverless computing, comprised of Function as a Service (FaaS) and Backend as a Service (BaaS), has garnered widespread attention owning to its features such as maintenance-free operations, pay-per-use pricing, and automatic scalability. However, practical usage encounters several challenges: 1) The diversity of user applications makes comprehensive performance evaluation difficult, as benchmark and application tests only reflect performance under specific conditions and cannot fully capture users’ actual experiences across different serverless platforms. 2) Disparities in performance and costs across different serverless platforms make it challenging to achieve optimal performance and cost efficiency through single-cloud deployment, thereby underutilizing the advantages of each platform. 3) Vendor lock-in issues restrict the migration of user applications and exacerbate dependence on a single cloud *** address these challenges, this paper proposes a collaborative mechanism, referred to as DCSA, which integrates FaaS and storage services to achieve automatic cross-cloud deployment of user applications while considering both performance and cost comprehensively. Firstly, we adapt the interfaces of different serverless platforms, effectively reducing the complexity of cross-cloud deployment. Secondly, we develop cost and latency models for the cross-cloud deployment of chained serverless applications and propose a deployment scheduling algorithm that simultaneously considers both latency and cost. Finally, we conduct experiments to evaluate the performance of the proposed algorithm. Results demonstrate that our method can effectively reduce latency (up to 2.3%) and lower costs (up to 9.9%).

关键词： Performance evaluation Adaptation models Costs Scheduling algorithms Scalability Serverless computing Collaboration

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A novel anycast-based integrated routing protocol for wireless sensor networks: Design and implementation

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Journal of Computational Information Systems 2013年第21期9卷 8611-8618页

作者： Yan, Guofeng Peng, Yuxing Chen, Shuhong School of Computer and Communication Hunan Institute of Engineering China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha 410073 China School of Computer National University of Defense Technology Changsha 410073 China School of Information Science and Engineering Central South University Changsha 410083 China

In this paper, we consider novel anycast-based integrated routing protocol (AIRP) to reduce the cost in delay performance of communications in multihop WSNs. Without tight time synchronization or known geographic information, AIRP provides low-delay cost route. We implement a low-overhead AIRP module in TinyOS kernel by modifying BLIP protocol stack, i. e., the Berkeley Low-power IP stack;as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. We describe the format of AIRP message, the dynamic updating process of MAP table information, and anycast data flow in detail under TinyOS. And then, we present the anycast group management system. Finally, we show the performance of AIRP where AIRP communication is used to distribute load among a set of servers through a study case. © 2013 Binary Information Press.

关键词： Wireless sensor networks

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