Distributed On-Sensor Compute System for AR/VR Devices: A\n Semi-Analytical Simulation Framework for Power Estimation Article Swipe
Jorge Marx Gómez
,
Saavan Patel
,
Syed Shakib Sarwar
,
Ziyun Li
,
Raffaele Capoccia
,
Zhao Wang
,
Reid Pinkham
,
Andrew Berkovich
,
Tsung-Hsun Tsai
,
B. De Salvo
,
Chiao Liu
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.07474
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2203.07474
Augmented Reality/Virtual Reality (AR/VR) glasses are widely foreseen as the\nnext generation computing platform. AR/VR glasses are a complex "system of\nsystems" which must satisfy stringent form factor, computing-, power- and\nthermal- requirements. In this paper, we will show that a novel distributed\non-sensor compute architecture, coupled with new semiconductor technologies\n(such as dense 3D-IC interconnects and Spin-Transfer Torque Magneto Random\nAccess Memory, STT-MRAM) and, most importantly, a full hardware-software\nco-optimization are the solutions to achieve attractive and socially acceptable\nAR/VR glasses. To this end, we developed a semi-analytical simulation framework\nto estimate the power consumption of novel AR/VR distributed on-sensor\ncomputing architectures. The model allows the optimization of the main\ntechnological features of the system modules, as well as the computer-vision\nalgorithm partition strategy across the distributed compute architecture. We\nshow that, in the case of the compute-intensive machine learning based Hand\nTracking algorithm, the distributed on-sensor compute architecture can reduce\nthe system power consumption compared to a centralized system, with the\nadditional benefits in terms of latency and privacy.\n
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Metadata
- Type
- preprint
- Landing Page
- http://arxiv.org/abs/2203.07474
- https://arxiv.org/pdf/2203.07474
- OA Status
- green
- Cited By
- 12
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4226165489
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Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4226165489Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2203.07474Digital Object Identifier
- Title
-
Distributed On-Sensor Compute System for AR/VR Devices: A\n Semi-Analytical Simulation Framework for Power EstimationWork title
- Type
-
preprintOpenAlex work type
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-14Full publication date if available
- Authors
-
Jorge Marx Gómez, Saavan Patel, Syed Shakib Sarwar, Ziyun Li, Raffaele Capoccia, Zhao Wang, Reid Pinkham, Andrew Berkovich, Tsung-Hsun Tsai, B. De Salvo, Chiao LiuList of authors in order
- Landing page
-
https://arxiv.org/abs/2203.07474Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2203.07474Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2203.07474Direct OA link when available
- Concepts
-
Computer science, Virtual reality, Augmented reality, Distributed computing, Virtual machine, Partition (number theory), Embedded system, Real-time computing, Artificial intelligence, Combinatorics, Operating system, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
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2025: 1, 2024: 4, 2023: 5, 2022: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.optimization | 97 |
| abstract_inverted_index.Spin-Transfer | 52 |
| abstract_inverted_index.and\nthermal- | 28 |
| abstract_inverted_index.architecture, | 41 |
| abstract_inverted_index.architecture. | 117 |
| abstract_inverted_index.framework\nto | 82 |
| abstract_inverted_index.interconnects | 50 |
| abstract_inverted_index.requirements. | 29 |
| abstract_inverted_index.semiconductor | 45 |
| abstract_inverted_index.Hand\nTracking | 129 |
| abstract_inverted_index.Random\nAccess | 55 |
| abstract_inverted_index.architectures. | 92 |
| abstract_inverted_index.Reality/Virtual | 1 |
| abstract_inverted_index.semi-analytical | 80 |
| abstract_inverted_index.the\nadditional | 147 |
| abstract_inverted_index.acceptable\nAR/VR | 72 |
| abstract_inverted_index.compute-intensive | 125 |
| abstract_inverted_index.main\ntechnological | 100 |
| abstract_inverted_index.technologies\n(such | 46 |
| abstract_inverted_index.on-sensor\ncomputing | 91 |
| abstract_inverted_index.distributed\non-sensor | 39 |
| abstract_inverted_index.computer-vision\nalgorithm | 110 |
| abstract_inverted_index.hardware-software\nco-optimization | 63 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 11 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.800000011920929 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.77702296 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |