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19th International Conference on Algorithms and architectures for Parallel Processing (ICA3PP)

作者： Froemmer, Jens Bannow, Nico Aue, Axel Grimm, Christoph Schneider, Klaus Robert Bosch GmbH D-70442 Stuttgart Germany Univ Kaiserslautern D-67663 Kaiserslautern Germany

ISBN: (纸本)9783030389918;9783030389901

In order to enable control units to run future algorithms, such as advanced control theory, advanced signal processing, data-based modeling, and physical modeling, the control units require a substantial step-up in computational power. In case of an automotive Engine Control Unit (ECU), safety requirements and cost constraints are just as important. Existing solutions to increase the performance of a micro-controller are either not suitable for a subset of the expected algorithms, or too expensive in terms of area. Hence, we introduce the novel data flow architecture (DFA) for embedded hardware accelerators. The DFA is flexible from the concept level to the individual functional units to achieve a high performance per size ratio for a wide variety of data intensive algorithms. Compared to hardwired implementations, the area can be as little as 1.4 times higher at the same performance.

关键词： Hardware accelerator data flow architecture Coarse-Grained Reconfigurable architecture Embedded system Automotive Microcontroller

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BIM data flow architecture with AR/VR technologies: Use cases in architecture, engineering and construction

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AUTOMATION IN CONSTRUCTION 2022年第0期134卷 104054-104054页

作者： Schiavi, Barbara Havard, Vincent Beddiar, Karim Baudry, David LINEACT CESI F-76800 St Etienne Du Rouvray France VINCI Construct France F-92000 Nanterre France LINEACT CESI F-44000 Nantes France

The construction of a building comprises several phases and involves many stakeholders. As projects have become more and more complex, the Building Information Modeling (BIM) methodology was proposed to unify projects around a Digital Twin of the information necessary for collaboration. In recent years, Augmented Reality (AR) and Virtual Reality (VR) have shown their relevance in assisting in various construction activities. However, their use requires additional refinement for them to be integrated into the BIM process. This literature review is an analysis of the cutting-edge applications of AR and VR in architecture Engineering Construction (AEC) projects and prevailing trends in their usage. This review focuses on publications related to BIM's safety applications (such as risk prevention and site operations during construction phase), as well as on data flow architectures between BIM and AR or VR applications.

关键词： architecture engineering construction (AEC) data flow architecture Building information Modeling (BIM) Augmented reality (AR) Virtual reality (VR) Systematic literature review (SLR)

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EXECUTING A PROGRAM ON THE MIT TAGGED-TOKEN data-flow architecture

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IEEE TRANSACTIONS ON COMPUTERS 1990年第3期39卷 300-318页

作者： ARVIND NIKHIL, RS Lab. for Comput. Sci. MIT Cambridge MA USA

The MIT Tagged-Token dataflow Project has an unconventional, but integrated approach to general-purpose high-performance parallel computing. Rather than extending conventional sequential languages, Id, a high-level language with fine-grained parallelism and determinacy implicit in its operational semantics, is used. Id programs are compiled to dynamic dataflow graphs, which constitute a parallel machine language. dataflow graphs are directly executed on the MIT tagged-token dataglow architecture (TTDA), a multiprocessor architecture. An overview of current thinking on dataflow architecture is provided by describing example Id programs, their compilation to dataflow graphs, and their execution on the TTDA. Related work and the status of the project are described

关键词： MASSACHUSETTS INSTITUTE OF TECHNOLOGY MULTIPROCESSOR architecture GTF2H5 gene data flow PARALLEL PROCESSING (COMPUTERS) Id Legal Executions data flow architecture language level Collected papers

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High Performance Packet Processor architecture for Network Virtualization Programmable Packet Processor architecture as a data flow Machine 18

High Performance Packet Processor Architecture for Network V...

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International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)

作者： Rim, Steven Y. Cui, Zhenguo Qian, Lin Korea Univ Ind Cooperat Technol Res Ctr Dept Informat & Commun Seoul South Korea Korea Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781450366250

Network Processing differs from conventional computing such that it involves three steps;packet header parsing, lookup table match and action, de-parsing. Recently a language for programmable packet processors have been proposed. However, micro-architecture of existing packet processors still remains unchanged from the previous generation which has fundamental issue to support virtualization and separation of hardware and processes. This paper talks about one way of designing a packet processor based on data-flow micro-architecture to resolve two issues: Resource virtualization and Parallelism for packet processing. The research is still on-going, and presentation will cover the conceptual architecture of a packet processor which includes block level data-flow including connectivity and operators of the block.

关键词： Programmable Packet Processor architecture Network Virtualization SDN NFV data flow architecture

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Extending data flow architectures for Convolutional Neural Networks to Multiple FPGAs 22

Extending Data Flow Architectures for Convolutional Neural N...

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22nd International Conference on Field Programmable Technology (ICFPT)

作者： Ibrahim, Mohamed Zhao, Zhipeng Hall, Mathew Betz, Vaughn Univ Toronto Toronto ON Canada Carnegie Mellon Univ Pittsburgh PA 15213 USA Microsoft Redmond WA USA Vector Inst AI Toronto ON Canada Intel Corp Toronto ON Canada

ISBN: (纸本)9798350359114

Convolutional Neural Networks (CNNs) are the state-of-the-art Artificial Intelligence frameworks that are used for a variety of applications including autonomous driving, surveillance and object detection. Since CNNs are very compute intensive, Field-Programmable Gate Array (FPGA)-based accelerators such as HPIPE have been used to speed up CNN computations. Although such accelerators show significant improvements in CNN performance, large CNNs such as ResNet152 still pose a challenge due to their high compute and memory requirements. This article discusses how we augment and extend HPIPE, the state-of-the-art CNN inference accelerator for FPGAs. We propose an automated CAD flow to partition large CNNs across multiple FPGAs that communicate via 100 Gb Ethernet. We utilize this CAD flow to estimate the performance improvements when scaling HPIPE to multiple FPGAs on six different CNNs. Moreover, we demonstrate through a prototype system that doubling the number of FPGAs results in 2x performance improvement on three CNNs: MobileNet-V1, MobileNet-V2, and ResNet-50.

关键词： Artificial Intelligence CNN Acceleration Convolutional Neural Networks data flow architecture FPGA Machine Learning Multi-FPGA

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Resilient Edge data Management Framework

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IEEE TRANSACTIONS ON SERVICES COMPUTING 2020年第4期13卷 663-674页

作者： Lujic, Ivan De Maio, Vincenzo Brandic, Ivona Vienna Univ Technol Inst Informat Syst Engn A-1040 Vienna Austria

Transferring and processing huge amounts of data in the cloud can violate the low latency requirements of modern IoT applications, considering underlying network infrastructure limitations. Edge data analytics is a promising solution. However, edge resources have usually less computational capabilities than cloud nodes, resulting in a higher failure rate of IoT systems. Consequently, near-real-time decisions are often based on limited and incomplete data. State-of-the-art solutions, such as operational/workload flows, data reduction, reconstruction, focus mostly on resource and network optimization, while approaches for incomplete data recovery employ a single specific method, despite diverse data characteristics. data quality impact on accuracy of the decision-making processes is often neglected. We propose EDMFrame, a framework featuring a generic mechanism for recovery of multiple gaps in incomplete datasets, using single-technique recovery (STR) and multiple-technique recovery (MTR) involving projection recovery maps (PRMs). We further devise an adaptive storage management mechanism for reducing data stored at the edge, keeping only the data necessary for predictive analytics. We conduct experiments using time series from smart buildings, (i) automatically recovering various multiple gaps and reducing errors up to 65.48 percent with MTR compared to STR;(ii) reducing amounts of data stored to 39.9 percent on average, keeping prediction accuracy around 98.83 percent.

关键词： Internet of Things Cloud computing Monitoring Storage management Intelligent sensors Edge computing Internet of Things data storage forecasting solution reference architectures data flow architecture

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Personal storage Grid architecture: consuming cloud data space resources

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INTERNATIONAL JOURNAL OF GRID AND HIGH PERFORMANCE COMPUTING 2010年第3期2卷 17-30页

作者： Lim, Mian-Guan Wu, Sining Simon, Tomasz Rashid, Md Helian, Na Cranfield Univ Cranfield Beds England Univ Hertfordshire Hatfield Herts England

On-demand cloud applications like online email accounts and online virtual disk space are becoming widely available in various forms. In cloud applications, one can see the importance of underlying resources, such as disk space, that is available to the end-user but not easily accessible. In the authors' study, a modern file system developed in linux is proposed, which enables consuming of cloud applications and making the underlying disk space resource available to the end-user. This system is developed as a web service to support cross operation system support. A free online mail account was used to demonstrate this solution, and an IMAP protocol to communicate with remote data spaces was used so that this method can mount onto any email system that supports IMAP. The authors' definition of infinite storage as the user is able to mount file systems as a single logical drive.

关键词： Cloud Applications Cloud Computing data flow architecture data Management Grid Computing

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A Unified View on data Path Aspects for Sensing Applications at a Smart City Scale

A Unified View on Data Path Aspects for Sensing Applications...

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IEEE 27th International Conference on Advanced Information Networking and Applications Workshops (WAINA)

作者： Gazis, Vangelis Strohbach, Martin Akiva, Navot Walther, Maximilian AGT Grp R&D GmbH D-64295 Darmstadt Germany

ISBN: (纸本)9780769549521;9781467362399

Founded upon the Internet of Things (IoT), the technological landscape of Smart Cities brings a wide range of operational parameters which pose significant challenges for architectural concerns. Herein we provide a unified view on the data path issues of sensing applications in terms of generic capabilities. We touch information granularity and semantic load concerns, discussing the escalation of detail from raw data to event indicators and, ultimately, deductions. Furthermore, we discuss customization and non-functional optimizations associated to particular application domains. In this regard, we identify key components in the data path. We conclude with design insights for an accommodating and efficient design of the data path for IoT applications.

关键词： sensing applications data flow architecture unified data models social sensors Internet of Things

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Optimal Natural Convection Heat Transfer Improvement by Combining Periodic Heating Temperature, Cavity Inclination, and Nanofluid

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HEAT TRANSFER ENGINEERING 2017年第10期38卷 931-947页

作者： Hati, Mourad Raji, Abdelghani Hasnaoui, Mohammed Naimi, Mohamed El Abdallaoui, Mohamed Cadi Ayyad Univ Lab Fluid Mech & Energet Marrakech Morocco Sultan Moulay Slimane Univ Lab Flows & Transfers Modeling Beni Mellal Morocco

Natural convection within a square inclined cavity filled with Al2O3-water nanofluid is investigated numerically. The temperature of the cooled surface is maintained constant, while that of the opposite surface (heating temperature) is varied sinusoidally in time. The remaining walls are considered adiabatic. The parameters governing the problem are the amplitude and the period of the variable temperature, the Rayleigh number, the inclination of the cavity, and the solid volume fraction. A substantial enhancement of heat transfer is obtained by combining the beneficial effects of the variable heating temperature (via its period and amplitude), the inclination of the cavity, and the nanoparticles fraction. In comparison with the constant heating conditions, it is found that both the variable heating temperature and the inclination of the cavity may lead to drastic changes in the flow structure and the corresponding heat transfer. The resonance phenomenon, observed for critical periods of the exciting temperature, is amplified by adding Al2O3 nanoparticles to the base fluid.

关键词： Heat transfer data flow architecture angle in inclination Critical Period (Psychology) heating temperature Rayleigh number Natural convection Amplitude Nanofluidics natural convection heat transfer

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Panoramic sensor calibration

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PATTERN RECOGNITION LETTERS 1998年第5-6期19卷 483-490页

作者： Benosman, R Maniere, T Devars, J Lab LIS T66 F-75252 Paris 05 France

This paper presents a new method of camera calibration for a panoramic stereovision sensor based on cylindrical projective geometry. The panoramic sensor allows us to get peripheral information about unknown environments, the architecture simplifies computation considerably. The device needs no calculation of epipolar lines. The calibration method derives directly from the benefits of the chosen architecture of the sensor and is not based on computation of vanishing points like former methods, which can only be an approximation and introduces uncertainty in the calibration process. Our calibration is based on the theory of projec tive vectors but uses simple geometry based on colinearity and orthogonality of vectors existing in the scene. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： panoramic vision stereovision camera calibration projective geometry data flow architecture

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