Vector-Based Dedicated Processor Architecture for Efficient Tracking in VSLAM Systems

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Embedded Systems Letters Pub Date : 2023-09-25 DOI:10.1109/LES.2023.3298900
Dejian Li;Xi Feng;Chongfei Shen;Qi Chen;Lixin Yang;Sihai Qiu;Xin Jin;Meng Liu
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Abstract

This letter introduces a dedicated processor architecture, called MEGACORE, which leverages vector technology to enhance tracking performance in visual simultaneous localization and mapping (VSLAM) systems. By harnessing the inherent parallelism of vector processing and incorporating a floating point unit (FPU), MEGACORE achieves significant acceleration in the tracking task of VSLAM. Through careful optimizations, we achieved notable improvements compared to the baseline design. Our optimizations resulted in a 14.9% reduction in the area parameter and a 4.4% reduction in power consumption. Furthermore, by conducting application benchmarks, we determined that the average speedup ratio across all stages of the tracking process is 3.25. These findings highlight the effectiveness of MEGACORE in improving the efficiency and performance of VSLAM systems, making it a promising solution for real-world implementations in embedded systems.
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基于矢量的VSLAM系统高效跟踪专用处理器体系结构
本文介绍了一种名为MEGACORE的专用处理器架构,该架构利用矢量技术来提高视觉同步定位和映射(VSLAM)系统的跟踪性能。通过利用矢量处理固有的并行性并结合浮点单元(FPU), MEGACORE在VSLAM跟踪任务中实现了显着的加速。通过仔细的优化,与基线设计相比,我们取得了显著的改进。我们的优化使面积参数降低了14.9%,功耗降低了4.4%。此外,通过执行应用程序基准测试,我们确定跟踪过程所有阶段的平均加速比为3.25。这些发现突出了MEGACORE在提高VSLAM系统的效率和性能方面的有效性,使其成为嵌入式系统中实际实现的有前途的解决方案。
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来源期刊
IEEE Embedded Systems Letters
IEEE Embedded Systems Letters Engineering-Control and Systems Engineering
CiteScore
3.30
自引率
0.00%
发文量
65
期刊介绍: The IEEE Embedded Systems Letters (ESL), provides a forum for rapid dissemination of latest technical advances in embedded systems and related areas in embedded software. The emphasis is on models, methods, and tools that ensure secure, correct, efficient and robust design of embedded systems and their applications.
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