Skyline Computation for Low-Latency Image-Activated Cell Identification
| Autor: | Kenichi Koizumi, Kei Hiraki, Mary Inaba |
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| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Proceedings of the AAAI Conference on Artificial Intelligence. 32 |
| ISSN: | 2374-3468 2159-5399 |
| DOI: | 10.1609/aaai.v32i1.12134 |
| Popis: | High-throughput label-free single cell screening technology has been studied for noninvasive analysis of various kinds of cells. We tackle the cell identification task in the cell sorting system as a continuous skyline computation. Skyline Computation is a method for extracting interesting entries from a large population with multiple attributes. Jointed rooted-tree (JR-tree) is continuous skyline computation algorithm that manages entries using a rooted-tree structure. JR-tree delays extend the tree to deeper levels to accelerate tree construction and traversal. In this study, we proposed the JR-tree-based parallel skyline computation accelerator. We implemented it on a field-programmable gate array (FPGA). We evaluated our proposed software and hardware algorithms against an existing software algorithm using synthetic and real-world datasets. |
| Databáze: | OpenAIRE |
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