Optimizing Density-Based Ant Colony Stream Clustering Using FPGA-Based Hardware Accelerator

被引：0

作者：

Graf, Jeremy R. ^{[1
]}

Perera, Darshika G. ^{[1
]}

机构：

[1] Univ Colorado, Dept Elect & Comp Engn, Colorado Springs, CO 80907 USA

来源：

2023 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS | 2023年

关键词：

Ant Colony Stream Clustering; FPGAs; embedded hardware; Density-Based Clustering; OPTIMIZATION;

D O I：

10.1109/ISCAS46773.2023.10181665

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the era of IoT, a massive amount of data will be generated from various sensors and corresponding IoT devices. Density-based Ant Colony Stream Clustering (ACSC) is one of the best solutions for big data processing for real-world applications, due to its many inherent traits. Also, FPGAs are one of the best avenues to support/accelerate complex algorithms, such as ACSC. In this paper, we introduce an FPGA-based hardware accelerator for ACSC, which achieves maximum speedups of 603 and 2.5 vs. its software counterparts on embedded processor and PC, respectively, without compromising cluster accuracy. No similar FPGA-based ACSC hardware accelerator exists in the literature.

引用

页数：5

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