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检索条件"任意字段=13th IEEE International Symposium on Parallel and Distributed Processing with Applications"

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A Multi-threaded Accelerated Drug Combination Pathway Network Implementation 18

A Multi-Threaded Accelerated Drug Combination Pathway Networ...

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18th ieee Int Symp on parallel and distributed Proc with Applicat (ISPA) / 10th ieee Int Conf on Big Data and Cloud Comp (BDCloud) / ieee Int Symp on Social Comp and Networking (SocialCom) / ieee Int Conf on Sustainable Comp and Commun (SustainCom)

作者： Ye, Haolei Liu, Shu Xiao, Wei McCreath, Eric C. Zhang, Xinzhuang Australian Natl Univ Res Sch Comp Sci Canberra ACT Australia Chinese Med Pharmaceut Proc State Key Lab New Tech Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781665414852

A Drug Combination Pathway Network is a new approach to predict the most efficient concentration ratio between two or more compounds. the state of the art implementation of the pathway network was introduced by Jiangyong and Wei, et al. in 2016. However, the time complexity of this implementation is O(CV3), where V is the number of nodes in the network and C is the number of concentrations. In this paper, we describes an approach that takes advantage of a multi-core CPU for calculating the result of the pathway network. the time complexity of our implementation is O(EV + V(2)logV) under PRAM model assuming C processors, where E is the number of edges in the network. Experimental results on an AMD Ryzen (TM) 3900X CPU show performance improvement of more than 156 times faster than the original C++ implementation.

关键词： Drug Combination Pathway Network Multi-threaded parallel processing Multi-Core CPU Massive-Core CPU

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Adaptive Page Migration for Irregular Data-intensive applications under GPU Memory Oversubscription 34

Adaptive Page Migration for Irregular Data-intensive Applica...

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34th ieee international parallel and distributed processing symposium (IPDPS)

作者： Ganguly, Debashis Zhang, Ziyu Yang, Jun Melhem, Rami Univ Pittsburgh Dept Comp Sci Pittsburgh PA 15260 USA Univ Pittsburgh Elect & Comp Engn Pittsburgh PA 15260 USA

ISBN: (纸本)9781728168760

Unified Memory in heterogeneous systems serves a wide range of applications. However, limited capacity of the device memory becomes a first order performance bottleneck for data-intensive general-purpose applications with increasing working sets. the performance overhead under memory oversubscription depends on the memory access pattern of the corresponding workload. While a regular application with sequential, dense memory access suffers from long latency write-backs, performance of a irregular application with sparse, seldom access to large data-sets degrades due to page thrashing. Although smart spatio-temporal prefetching and large page eviction yield good performance in general, remote zero-copy access to host-pinned memory proves to be beneficial for irregular, data-intensive applications. Further, new generation GPUs introduced hardware access counters to delay page migration and reduce memory thrashing. However, the responsibility of deciding what strategy is the best fit for a given application relies heavily on the programmer based on thorough understanding of the memory access pattern through intrusive profiling. In this work, we propose a programmer-agnostic runtime that leverages the hardware access counters to automatically categorize memory allocations based on the access pattern and frequency. the proposed heuristic adaptively navigates between remote zero-copy access to host-pinned memory and first-touch page migration based on the trade-off between low latency remote access and high-bandwidth local access. We show that although designed to address memory oversubscription, our scheme has no impact on performance when working sets fit in the device-local memory. Experimental results show that our scheme provides performance improvement of 22% to 78% for irregular applications under 125% memory oversubscription compared to the state of the art. At the same time, regular applications are not impacted by the framework.

关键词： page migration pinning memory management CPU-GPU Unified Memory

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Cost-Efficient Request Dispatching in Geo-distributed Cloud Gaming Infrastructure 18

Cost-Efficient Request Dispatching in Geo-distributed Cloud ...

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作者： Li, Yusen Wu, Jinping Ma, Bingzheng Wang, Gang Liu, Xiaoguang Nankai Univ Coll Comp Sci Tianjin Peoples R China

ISBN: (纸本)9781665414852

Cloud gaining is a recent approach to galling, where processing for the games occurs on well-equipped servers within the cloud and a video stream is returned to the user, meaning users can play high-end games on devices that lack computational power. Different games require different amounts of computational resources and computation times. It would be desirable to efficiently pack a number of servers with multiple games at once, however this is complicated within a geo-distributed cloud system as we must consider that not every data center can fulfil every game request due to latency requirements. Within this work, we present shadow routing algorithms to distribute game requests to cloud data centers and also to pack the servers within the data centers with these game requests. these algorithms are designed to operate in order to minimize total cost from server hire and bandwidth usage, and we prove their performance is asymptotically close to optimal. An experiment using realistic arrival rates is given, and the results verify our theory within a realistic context. Also shown using proof and experimentation is that the algorithms can adapt themselves to periodic changes as demand raises and falls while remaining close to the optimal, which is a particular weak point of other schemes.

关键词： Cloud Gaming Geo-distributed Resource Cost Request Dispatching Shadow Routing

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Probabilistic Data Allocation in Pervasive Computing applications 18

Probabilistic Data Allocation in Pervasive Computing Applica...

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作者： Kolomvatsos, Kostas Univ Thessaly Dept Informat & Telecommun Papasiopoulou 2-4 Lamia 35131 Greece

ISBN: (纸本)9781665414852

Pervasive Computing (PC) deals with the placement of services and applications around end users for facilitating their everyday activities. Current advances on the Internet of things (IoT) and the Edge Computing (EC) provide the room for adopting their infrastructures and hosting the desired services for supporting PC applications. Numerous devices present in IoT and EC infrastructures give the opportunity to record and process data through the interaction with users and their environment. Upon these data, the appropriate processing should be realized as requested by end users or applications. It is efficient to process such requests as close as possible to end users to limit the latency in the provision of responses. the research community, identifying this need, proposes the use of the EC as the appropriate place to perform the discussed processing which has the form of tasks or queries. Tasks/queries set specific conditions for data they desire imposing a number of requirements for the dataset upon which the desired processing should be executed. It is wise to pre-process the data and detect their statistics to know beforehand if it is profitable to have any dataset as part of the requested processing. this paper focuses on a model that is responsible to efficiently distribute the collected data to the appropriate datasets. We store similar data to the same datasets and keep their statistics solid (i.e., we meet a low deviation) through the use of a probabilistic approach. the second part of the proposed approach is related to an aggregation scheme upon multiple outlier detection methods. We decide to transfer outliers to Cloud avoiding to store them locally as they will jeopardize the solidity of datasets. If data are going to be locally stored, we provide a mechanism for selecting the most appropriate dataset to host them while we perform a controlled replication to support a fault tolerant system. the performance of the proposed models is evaluated by a high n

关键词： Pervasive Computing Internet of things Edge Computing Data Storage Accuracy Probabilistic Model

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A cross-blockchain based distributed crowdsouring system for Internet of things 18

A cross-blockchain based distributed crowdsouring system for...

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作者： Peng, Min Miao, QinYang Lin, Hui Wang, XiaoDing Fujian Normal Univ Sch Math & Informat Fuzhou Peoples R China

ISBN: (纸本)9781665414852

With the development of Internet of things (IoT) technologies, the mobile crowdsourcing has become the most effective and reliable method for data collection and processing. However, as huge amounts of data are generated in mobile crowdsourcing services, data privacy and security has become a key challenge for IoT. To address this challenge, a Cross-Blockchain based distributed mobile Crowdsourcing System, named CBDCS, is proposed in this paper. In CBDCS, to overcome the privacy leakage problem caused by a single-point failure, the blockchain is used as a crowdsourcing task server, based on which an improved multi-subchain structure is designed. then, based on multi-subchain, a task hierarchical storage mechanism is proposed, which stores different levels of tasks in corresponding subchains to improve privacy protection. In addition, CBDCS meet the demands of workers for tasks through a cross-subchain mechanism based on root&sub CA and smart contracts, while guaranteeing data privacy. Extensive simulation results demonstrate that the CBDCS can obtain high throughput, low overhead, and data privacy under various IoT scenarios.

关键词： Blockchain Cross-subchain Mobile Crowdsouring Internet of things

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the underlying causal network from global dyadic events: allies and rivals in international relations 18

The underlying causal network from global dyadic events: all...

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作者： Jiang, Lei Microsoft Bellevue WA 98004 USA

ISBN: (纸本)9781665414852

the ever-increasing amount of web information usually leads to more discovery of implicit relations using data-driven methods. While country-country relations are not exactly new for human learning, we illustrate that one can extract the knowledge of such sophisticated relations solely from data. Using the global dyadic events data that record the involving parties and timestamp, we identify the underlying causal network with common initiators or reactors, as well as the nature of pairwise relations as a counterfactual reasoning problem, thereby deriving the significance of causal effects in the network. To formalize the discovery process, we first validate some country-country relations in a small-world network structure after exploitative runs over the entire data set, suggesting the traditional allies and rivals as we know in the real world. Further, we use sentimental analysis based on Wikipedia text data to match the significance of bilateral relations in the causal discovery. Our results show that using time series data of dyadic event counts alone, combined with lexical-based validation, can extract the knowledge of bilateral and multilateral relations and has potential to be a means to measuring and monitoring the climate of complex geopolitics.

关键词： causal network dyadic events GDELT counterfactual bilateral relation

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Optimizing High-Performance Computing Systems for Biomedical Workloads 34

Optimizing High-Performance Computing Systems for Biomedical...

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34th ieee international parallel and distributed processing symposium (IPDPS)

作者： Kovatch, Patricia Gai, Lili Cho, Hyung Min Fluder, Eugene Jiang, Dansha Icahn Sch Med Mt Sinai Genet & Genom Sci New York NY 10029 USA Icahn Sch Med Mt Sinai Off Dean New York NY 10029 USA

ISBN: (纸本)9781728174457

the productivity of computational biologists is limited by the speed of their workflows and subsequent overall job throughput. Because most biomedical researchers are focused on better understanding scientific phenomena rather than developing and optimizing code, a computing and data system implemented in an adventitious and/or non-optimized manner can impede the progress of scientific discovery. In our experience, most computational, life-science applications do not generally leverage the full capabilities of high-performance computing, so tuning a system for these applications is especially critical. To optimize a system effectively, systems staff must understand the effects of the applications on the system. Effective stewardship of the system includes an analysis of the impact of the applications on the compute cores, file system, resource manager and queuing policies. the resulting improved system design, and enactment of a sustainability plan, help to enable a long-term resource for productive computational and data science. We present a case study of a typical biomedical computational workload at a leading academic medical center supporting over $100 million per year in computational biology research. Over the past eight years, our high-performance computing system has enabled over 900 biomedical publications in four major areas: genetics and population analysis, gene expression, machine learning, and structural and chemical biology. We have upgraded the system several times in response to trends, actual usage, and user feedback. Major components crucial to this evolution include scheduling structure and policies, memory size, compute type and speed, parallel file system capabilities, and deployment of cloud technologies. We evolved a 70 teraflop machine to a 1.4 petaflop machine in seven years and grew our user base nearly 10-fold. For long-term stability and sustainability, we established a chargeback fee structure. Our overarching guiding principle for eac

关键词： high performance computing computational biology genomics system optimization scheduling parallel file systems cloud technologies sustainability

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Honeyeye: A Network Traffic Collection Framework for distributed ICS Honeynets 18

Honeyeye: A Network Traffic Collection Framework for Distrib...

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作者： Sheng, Chuan Yao, Yu Li, Dongbiao An, Hongna Yang, Wei Northeastern Univ Sch Comp Sci & Engn Shenyang Peoples R China Northeastern Univ Software Coll Shenyang Peoples R China

ISBN: (纸本)9781665414852

the honeynet, as an important security resource, is increasingly used in the industrial field in order to detect, analyze, and prevent network attacks against industrial control systems (ICSs). However, conventional network traffic collection methods used in honeynets cannot meet the more and more complex requirements of large-scale and distributed honeynets. this paper presents a new network traffic collection framework for distributed ICS honeynets called Honeyeye. Honeyeye can provide some different running modes for different application scenarios and purposes. Honeyeye can not only collect and save network traffic, but also parse it into readable data and convert it into the required format. By this way, Honeyeye tends to provide network administrators and intrusion detection systems (IDSs) with more understandable and directly available data rather than captured opaque binary data. Experimental results show that the framework is effective in parsing, converting, and transmitting ICS honeynet traffic.

关键词： Industrial Control System distributed ICS Honeynet Network Traffic Collection

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Maritime Broadband Communications: applications, Challenges and an Offshore 5G-virtual MIMO Paradigm 18

Maritime Broadband Communications: Applications, Challenges ...

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作者： Yu, Cunqian Li, Jingyu Zhang, Chunfang Li, Hang He, Rongxi Lin, Bin Dalian Maritime Univ Coll Informat Sci & Technol Dalian Peoples R China

ISBN: (纸本)9781665414852

Orienting to the competitive exploration of marine resources and the ship intelligent navigation, the broadband and stable maritime communications has regarded as a matter of concern. Due to the particularity of the ocean environment, the maritime communication network is severely restricted compared to the terrestrial one. By understanding the requirement of maritime business, this article deepens the research on maritime communications at offshore areas and ocean and makes a summary of the urgent problems and mainstream communication technologies. Besides, an experimental type of maritime network paradigm based on the coast-5G network involving virtual MIMO technology is present, with a view to providing open issues for the offshore maritime broadband communications.

关键词： maritime broadband communication virtual MIMO 5G network open platform structure

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Pacon: Improving Scalability and Efficiency of Metadata Service through Partial Consistency 34

Pacon: Improving Scalability and Efficiency of Metadata Serv...

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34th ieee international parallel and distributed processing symposium (IPDPS)

作者： Liu, Yubo Lu, Yutong Chen, Zhiguang Zhao, Ming Sun Yat Sen Univ Guangzhou Peoples R China Arizona State Univ Tempe AZ 85287 USA

ISBN: (纸本)9781728168760

Traditional distributed file systems (DFS) use centralized service to manage metadata. Many studies based on this centralized architecture enhanced metadata processing capability by scaling the metadata server cluster, which is however still difficult to keep up with the growing number of clients and the increasingly metadata-intensive applications. Some solutions abandoned the centralized metadata service and improved scalability by embedding a private metadata service in an HPC application, but these solutions are suitable for only some specific applications and the absence of global namespace makes data sharing and management difficult. this paper addresses the shortcomings of existing studies by optimizing the consistency model of client-side metadata cache for the HPC scenario using a novel partial consistency model. It provides the application with strong consistency guarantee for only its workspace, thus improving metadata scalability without adding hardware or sacrificing the versatility and manageability of DFSes. In addition, the paper proposes batch permission management to reduce path traversal overhead, thereby improving metadata processing efficiency. the result is a library (Pacon) that allows existing DFSes to achieve partial consistency for scalable and efficient metadata management. the paper also presents a comprehensive evaluation using intensive benchmarks and representative application. For example, in file creation, Pacon improves the performance of BeeGFS by more than 76.4 times, and outperforms the state-of-the-art metadata management solution (IndexFS) by more than 4.6 times.

关键词： metadata scalability efficiency distributed file system consistency

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