2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC)最新文献_第2页

AVEC: Accelerator Virtualization in Cloud-Edge Computing for Deep Learning Libraries AVEC:面向深度学习库的云边缘计算加速器虚拟化

2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC) Pub Date : 2021-03-08 DOI: 10.1109/ICFEC51620.2021.00013

J. Kennedy, B. Varghese, C. Reaño

{"title":"AVEC: Accelerator Virtualization in Cloud-Edge Computing for Deep Learning Libraries","authors":"J. Kennedy, B. Varghese, C. Reaño","doi":"10.1109/ICFEC51620.2021.00013","DOIUrl":"https://doi.org/10.1109/ICFEC51620.2021.00013","url":null,"abstract":"Edge computing offers the distinct advantage of harnessing compute capabilities on resources located at the edge of the network to run workloads of relatively weak user devices. This is achieved by offloading computationally intensive workloads, such as deep learning from user devices to the edge. Using the edge reduces the overall communication latency of applications as workloads can be processed closer to where data is generated on user devices rather than sending them to geographically distant clouds. Specialised hardware accelerators, such as Graphics Processing Units (GPUs) available in the cloud-edge network can enhance the performance of computationally intensive workloads that are offloaded from devices on to the edge. The underlying approach required to facilitate this is virtualization of GPUs. This paper therefore sets out to investigate the potential of GPU accelerator virtualization to improve the performance of deep learning workloads in a cloud-edge environment. The AVEC accelerator virtualization framework is proposed that incurs minimum overheads and requires no source-code modification of the workload. AVEC intercepts local calls to a GPU on a device and forwards them to an edge resource seamlessly. The feasibility of AVEC is demonstrated on a real-world application, namely OpenPose using the Caffe deep learning library. It is observed that on a lab-based experimental test-bed AVEC delivers up to 7.48x speedup despite communication overheads incurred due to data transfers.","PeriodicalId":436220,"journal":{"name":"2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115407599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

LEAF: Simulating Large Energy-Aware Fog Computing Environments LEAF:模拟大型能量感知雾计算环境

2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC) Pub Date : 2021-03-01 DOI: 10.1109/ICFEC51620.2021.00012

Philipp Wiesner, L. Thamsen

{"title":"LEAF: Simulating Large Energy-Aware Fog Computing Environments","authors":"Philipp Wiesner, L. Thamsen","doi":"10.1109/ICFEC51620.2021.00012","DOIUrl":"https://doi.org/10.1109/ICFEC51620.2021.00012","url":null,"abstract":"Despite constant improvements in efficiency, today’s data centers and networks consume enormous amounts of energy and this demand is expected to rise even further. An important research question is whether and how fog computing can curb this trend. As real-life deployments of fog infrastructure are still rare, a significant part of research relies on simulations. However, existing power models usually only target particular components such as compute nodes or battery-constrained edge devices.Combining analytical and discrete-event modeling, we develop a holistic but granular energy consumption model that can determine the power usage of compute nodes as well as network traffic and applications over time. Simulations can incorporate thousands of devices that execute complex application graphs on a distributed, heterogeneous, and resource-constrained infrastructure. We evaluated our publicly available prototype LEAF within a smart city traffic scenario, demonstrating that it enables research on energy-conserving fog computing architectures and can be used to assess dynamic task placement strategies and other energy-saving mechanisms.","PeriodicalId":436220,"journal":{"name":"2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123334126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Conference Organization 会议组织

2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC) Pub Date : 2019-06-01 DOI: 10.1109/acsd.2019.000-3

Wil M.P. van der Aalst, A. Kalenkova

{"title":"Conference Organization","authors":"Wil M.P. van der Aalst, A. Kalenkova","doi":"10.1109/acsd.2019.000-3","DOIUrl":"https://doi.org/10.1109/acsd.2019.000-3","url":null,"abstract":"Technical Program Committee S. Akshay, Indian Institute of Technology Bombay, India Étienne André, Laboratoire d’Informatique de Paris-Nord, France Mohamed Faouzi Atig, Upsala University, Sweden Josep Carmona, Universitat Politècnica de Catalunya, Spain Franck Cassez, Macquarie University, Australia Thomas Chatain, LSV, CNRS & ENS Paris-Saclay, France Rocco De Nicola, IMT School for Advanced Studies Lucca, Italy Joerg Desel, FernUniversitaet in Hagen, Germany Klaus Echtle, University Duisburg-Essen, Germany Alain Girault, INRIA, France Radu Grosu, Techn. Unviersity Vienna, Austria Stefan Haar, LSV, CNRS & ENS Paris-Saclay, France Loïc Hélouët, INRIA, France Ludovic Henrio, CNRS, France Loïg Jézéquel, Univ. Nantes, France Gabriel Juhás, Slovak University of Technology in Bratislava, Slovakia Joerg Keller, FernUniversitaet in Hagen, Germany (co-chair) Christoph Kessler, Linköping University, Sweden Jan Křetínský, Techn. University Munich, Germany Johan Lilius, Åbo Akademi University, Finland Gerald Luettgen, University Bamberg, Germany Roland Meyer, Techn. University Braunschweig, Germany Andrey Mokhov, Newcastle University, UK Claire Pagetti, ONERA, France Wojciech Penczek, ICS PAS & Siedlce University, Poland (co-chair) Laure Petrucci, LIPN, CNRS & Université Paris 13, France Marta Pietkiewicz-Koutny, Newcastle University, UK Dumitru Potop-Butucaru, INRIA, France Klaus Schneider, Techn. University Kaiserslautern, Germany Sandeep Shukla, Indian Institute of Technology Kanpur, India Ashutosh Trivedi, Indian Institute of Technology Bombay, India Jaco van de Pol, Aarhus University, Denmark Fei Xia, Newcastle University, UK","PeriodicalId":436220,"journal":{"name":"2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129973223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Title Page i 第1页

2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC) Pub Date : 1988-07-01 DOI: 10.1016/b978-0-12-817640-5.00016-9

引用次数: 0

Message from the ICFEC 2021 Chairs 2021年ICFEC主席致辞

2021 IEEE 5th International Conference on Fog and Edge Computing (ICFEC) Pub Date : 1900-01-01 DOI: 10.1109/icfec51620.2021.00005

引用次数: 0