Presentation
Pushing Computing-in-memory towards Computational Storage to Accelerate In-Orbit Remote Sensing Satellite Image Processing
DescriptionIn the context of remote sensing satellites, power consumption has always posed a significant challenge for storage systems and in-orbit computing. This research pushes computing-in-memory (CIM) towards computational storage to accelerate in-orbit remote sensing satellite image processing.The first improvement involves utilizing CIM to address the energy efficiency problem associated with neural network computing in computational storage. The second enhancement involves the introduction of Zoned Namespace (ZNS) Solid State Drives (SSDs) to further optimize storage bandwidth. Lastly, a semantic retrieval function is designed at the file system layer to enhance the retrieval capability of the in-orbit satellite storage system. Experimental results demonstrate that the proposed CIM-ZCSD system achieves a three-fold increase in writing bandwidth and nearly 20 times improvement in computational energy efficiency compared to traditional systems.
Event Type
Work-in-Progress Poster
TimeTuesday, June 256:00pm - 7:00pm PDT
LocationLevel 2 Lobby
AI
Autonomous Systems
Cloud
Design
EDA
Embedded Systems
IP
Security