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A parallel pipeline connected-component labeling method for on-orbit space target monitoring
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作者 LI Zongling ZHANG Qingjun +1 位作者 LONG Teng ZHAO Baojun 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2022年第5期1095-1107,共13页
The paper designs a peripheral maximum gray differ-ence(PMGD)image segmentation method,a connected-compo-nent labeling(CCL)algorithm based on dynamic run length(DRL),and a real-time implementation streaming processor ... The paper designs a peripheral maximum gray differ-ence(PMGD)image segmentation method,a connected-compo-nent labeling(CCL)algorithm based on dynamic run length(DRL),and a real-time implementation streaming processor for DRL-CCL.And it verifies the function and performance in space target monitoring scene by the carrying experiment of Tianzhou-3 cargo spacecraft(TZ-3).The PMGD image segmentation method can segment the image into highly discrete and simple point tar-gets quickly,which reduces the generation of equivalences greatly and improves the real-time performance for DRL-CCL.Through parallel pipeline design,the storage of the streaming processor is optimized by 55%with no need for external me-mory,the logic is optimized by 60%,and the energy efficiency ratio is 12 times than that of the graphics processing unit,62 times than that of the digital signal proccessing,and 147 times than that of personal computers.Analyzing the results of 8756 images completed on-orbit,the speed is up to 5.88 FPS and the target detection rate is 100%.Our algorithm and implementation method meet the requirements of lightweight,high real-time,strong robustness,full-time,and stable operation in space irradia-tion environment. 展开更多
关键词 Tianzhou-3 cargo spacecraft(TZ-3) connected-component labeling(CCL)algorithms parallel pipeline processing on-orbit space target detection streaming processor
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四川大学大模型底层系统方向研究论文在VLDB 2025 发表
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《信息网络安全》 2025年第9期1475-1475,共1页
四川大学计算机学院学生团队在大规模语言模型参数高效微调系统研究方向取得重要进展,其研究成果“mLoRA:Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs”在国际数据库学术会议VLDB 2025 Rese... 四川大学计算机学院学生团队在大规模语言模型参数高效微调系统研究方向取得重要进展,其研究成果“mLoRA:Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs”在国际数据库学术会议VLDB 2025 Research Track正式发表。VLDB(International Conference on Very Large Data Bases)是数据库领域的重要国际学术会议之一,涵盖数据库管理系统、数据密集型系统与大规模数据处理等方向。该工作已在多个国内外互联网企业的实际生产环境中部署应用,并获得一项中国发明专利和一项美国发明专利的受理。 展开更多
关键词 LoRA Adapters Fine-Tuning mLoRA pipeline Parallelism
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