DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hong, Injoon | ko |
dc.contributor.author | Clemons, Jason | ko |
dc.contributor.author | Venkatesan, Rangharajan | ko |
dc.contributor.author | Frosio, Iuri | ko |
dc.contributor.author | Khailany, Brucek | ko |
dc.contributor.author | Keckler, Stephen W | ko |
dc.date.accessioned | 2023-10-11T10:00:21Z | - |
dc.date.available | 2023-10-11T10:00:21Z | - |
dc.date.created | 2023-10-11 | - |
dc.date.issued | 2016-06 | - |
dc.identifier.citation | 53rd Annual ACM IEEE Design Automation Conference, DAC 2016 | - |
dc.identifier.issn | 0738-100X | - |
dc.identifier.uri | http://hdl.handle.net/10203/313205 | - |
dc.description.abstract | Superpixel generation is a common preprocessing step in vision processing aimed at dividing an image into non-overlapping regions. Simple Linear Iterative Clustering (SLIC) is a commonly used superpixel algorithm that offers a good balance between performance and accuracy. However, the algorithm's high computational and memory bandwidth requirements result in performance and energy efficiency that do not meet the requirements of real-time embedded applications. In this work, we explore the design of an energy-efficient superpixel accelerator for real-time computer vision applications. We propose a novel algorithm, Subsampled SLIC (S-SLIC), that uses pixel subsampling to reduce the memory bandwidth by 1.8×. We integrate S-SLIC into an energy-efficient superpixel accelerator and perform an in-depth design space exploration to optimize the design. We completed a detailed design in a 16nm FinFET technology using commercially-available EDA tools for high-level synthesis to map the design automatically from a C-based representation to a gate-level implementation. The proposed S-SLIC accelerator achieves real-time performance (30 frames per second) with 250× better energy efficiency than an optimized SLIC software implementation running on a mobile GPU. | - |
dc.language | English | - |
dc.publisher | ACM Special Interest Group on Design Automation (SIGDA) | - |
dc.title | A real-time energy-efficient superpixel hardware accelerator for mobile computer vision applications | - |
dc.type | Conference | - |
dc.identifier.wosid | 000390302500095 | - |
dc.identifier.scopusid | 2-s2.0-84977103539 | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | 53rd Annual ACM IEEE Design Automation Conference, DAC 2016 | - |
dc.identifier.conferencecountry | US | - |
dc.identifier.conferencelocation | Austin, TX | - |
dc.identifier.doi | 10.1145/2897937.2897974 | - |
dc.contributor.localauthor | Hong, Injoon | - |
dc.contributor.nonIdAuthor | Clemons, Jason | - |
dc.contributor.nonIdAuthor | Venkatesan, Rangharajan | - |
dc.contributor.nonIdAuthor | Frosio, Iuri | - |
dc.contributor.nonIdAuthor | Khailany, Brucek | - |
dc.contributor.nonIdAuthor | Keckler, Stephen W | - |
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