A Comprehensive Performance Evaluation of Procedural Geometry Workloads on Resource-Constrained Devices

Edon, Govori; Murturi, Ilir; Dustdar, Schahram

doi:10.1109/EDGE60047.2023.00049

Published May 22, 2024 | Version v1

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A Comprehensive Performance Evaluation of Procedural Geometry Workloads on Resource-Constrained Devices

1. TU Wien
2. Vienna University of Technology

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2023 IEEE International Conference on Edge Computing and Communications (EDGE) Date of Conference: 02-08 July 2023 Date Added to IEEE Xplore: 01 September 2023 ISBN Information: ISSN Information: DOI: 10.1109/EDGE60047.2023.00049 Publisher: IEEE Conference Location: Chicago, IL, USA I. Introduction Applications such as those within Augmented or Virtual Reality (AR/VR) have unique software architecture requirements that must be able to handle latency, data transmission, and performance. Visualizing and representing high-quality 3D digital models are computationally intensive, requiring significant data transfer to clients. While these applications are susceptible to latency delay, processing data on cloud servers involves high latency caused by data transmission over multiple networks, and heterogeneous devices [1]. In order to tackle these challenges, recent advancements have resulted in applications that can operate across all three computing tiers, including the edge, fog, and cloud computing tiers [2], [3]. Sign in to Continue Reading Authors Figures References Citations Keywords Metrics Footnotes More Like This 3D Model Retrieval Using Constructive Solid Geometry in Virtual Reality 2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Published: 2020 Performance Evaluation of 3D Reconstruction Tool over Cloud Computing Virtualized Environment IEEE Latin America Transactions Published: 2016 Show More (EDGE), Chicago, USA, 02-08 July, 2023

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Created: May 22, 2024
Modified: July 5, 2024

A Comprehensive Performance Evaluation of Procedural Geometry Workloads on Resource-Constrained Devices

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EDGE_2023___Benchmarking_Procedural_Workloads (12).pdf

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