Computational Storage offers near-data acceleration, and it is gaining popularity with recent commercialization and standardization efforts. In this talk, we present how Computational Storage can be used to scale the performance of a key-value storage engine and deep learning training workloads. We propose a new key-value storage engine, named RETINA, where Computational Storage, Samsung SmartSSD, accelerates its data processing and user-defined processing pipelines. RETINA adopts a cross-layered approach between the host CPU and Computational Storage to leverage the host’s flexibility, fine-grained control and Computational Storage’s near-data acceleration. We show how RETINA can improve the performance and efficiency of key-value storage and deep learning workloads.
RETINA: Exploring Computational Storage (SmartSSD) Usecase
- Introduction of Computational Storage Architecture
- Real use-case of Computational Storage (esp, Samusng SmartSSD) for key-value storage engine and Deep Learning pipeline
- Computation Storage Ecosystem development
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SNIA Developer Conference
September 15-17, 2025
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