SLAM-CIM: A Visual SLAM Backend Processor With Dynamic-Range-Driven-Skipping Linear-Solving FP-CIM Macros
文献类型：期刊论文
| 作者 | Li, Mengjie1; Zhu, Haozhe1; He, Siqi1; Zhang, Hongyi1; Liao, Jie1; Zhai, Danfeng1; Chen, Chixiao1; Liu, Qi1; Zeng, Xiaoyang1; Sun, Ninghui2 |
| 刊名 | IEEE JOURNAL OF SOLID-STATE CIRCUITS
 |
| 出版日期 | 2024-05-30 |
| 页码 | 13 |
| 关键词 | Simultaneous localization and mapping Sorting In-memory computing Visualization Energy efficiency Optimization Common Information Model (computing) Compute in memory (CIM) floating point (FP) linear system solver simultaneous localization and mapping (SLAM) |
| ISSN号 | 0018-9200 |
| DOI | 10.1109/JSSC.2024.3402808 |
| 英文摘要 | Simultaneous localization and mapping (SLAM), a pivotal technology in robotics, autonomous vehicles, and surveillance, has gained prominence with the emergence of edge intelligence. Developing energy-efficient, low-latency SLAM systems is essential due to resource constraints and real-time demands. Compute-in-memory (CIM) architectures have been proven to be efficient for matrix multiplications. However, applications for SLAM raise new challenges in memory access and computation aspects: the linear system solving (LS) requires row transformation and causes frequent CIM updates, while the backend optimization causes redundant memory access; back-end optimization dominates SLAM's computation and requires high precision and high dynamic range. Thus, we propose SLAM-CIM, a visual SLAM backend processor for edge robotics. A dynamic-range-driven-skipping CIM macro is designed to realize energy-efficient floating point (FP)-multiply-and-accumulate (MAC) operations. A preconditional-conjugate-gradient-based in-memory linear solver (PILARS) is designed to achieve LS without additional row transformations. This reduces memory access by 2.08 $\times$ and linear-system-solving latency by 3.84 x. SLAM-CIM further minimizes CIM weight updates through incremental bundle adjustment (BA), increasing average CIM utilization by 2.8 x. A silicon prototype is fabricated using 28-nm CMOS technology. The measurements show that SLAM-CIM achieves accurate and efficient SLAM operations with an average energy efficiency of 31.53 TFLOPS/W. |
| 资助项目 | Major Project of the Science and Technology Innovation 2030 |
| WOS研究方向 | Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:001236627600001 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/40050]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhu, Haozhe; Chen, Chixiao |
| 作者单位 | 1.Fudan Univ, State Key Lab Integrated Chips & Syst, Shanghai 200433, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Mengjie,Zhu, Haozhe,He, Siqi,et al. SLAM-CIM: A Visual SLAM Backend Processor With Dynamic-Range-Driven-Skipping Linear-Solving FP-CIM Macros[J]. IEEE JOURNAL OF SOLID-STATE CIRCUITS,2024:13. |
| APA | Li, Mengjie.,Zhu, Haozhe.,He, Siqi.,Zhang, Hongyi.,Liao, Jie.,...&Liu, Ming.(2024).SLAM-CIM: A Visual SLAM Backend Processor With Dynamic-Range-Driven-Skipping Linear-Solving FP-CIM Macros.IEEE JOURNAL OF SOLID-STATE CIRCUITS,13. |
| MLA | Li, Mengjie,et al."SLAM-CIM: A Visual SLAM Backend Processor With Dynamic-Range-Driven-Skipping Linear-Solving FP-CIM Macros".IEEE JOURNAL OF SOLID-STATE CIRCUITS (2024):13. |
入库方式： OAI收割
来源：计算技术研究所
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