Containerized In-Storage Processing and Computing-Enabled SSD Disaggregation
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arXiv
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| Hauptverfasser: | , , , , , , , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| author | Kwon, Miryeong Gouk, Donghyun Na, Eunjee Kim, Jiseon Kim, Junhee Woo, Hyein Ryu, Eojin Choi, Hyunkyu Baek, Jinwoo Bae, Hanyeoreum Kandemir, Mahmut Jung, Myoungsoo |
| author_facet | Kwon, Miryeong Gouk, Donghyun Na, Eunjee Kim, Jiseon Kim, Junhee Woo, Hyein Ryu, Eojin Choi, Hyunkyu Baek, Jinwoo Bae, Hanyeoreum Kandemir, Mahmut Jung, Myoungsoo |
| contents | ISP minimizes data transfer for analytics but faces challenges in adaptation and disaggregation. We propose DockerSSD, an ISP model leveraging OS-level virtualization and lightweight firmware to enable containerized data processing directly on SSDs. Key features include Ethernet over NVMe for network-based ISP management and Virtual Firmware for secure, efficient container execution. DockerSSD supports disaggregated storage pools, reducing host overhead and enhancing large-scale services like LLM inference. It achieves up to 2.0x better performance for I/O-intensive workloads, and 7.9x improvement in distributed LLM inference. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_06769 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Containerized In-Storage Processing and Computing-Enabled SSD Disaggregation Kwon, Miryeong Gouk, Donghyun Na, Eunjee Kim, Jiseon Kim, Junhee Woo, Hyein Ryu, Eojin Choi, Hyunkyu Baek, Jinwoo Bae, Hanyeoreum Kandemir, Mahmut Jung, Myoungsoo Hardware Architecture ISP minimizes data transfer for analytics but faces challenges in adaptation and disaggregation. We propose DockerSSD, an ISP model leveraging OS-level virtualization and lightweight firmware to enable containerized data processing directly on SSDs. Key features include Ethernet over NVMe for network-based ISP management and Virtual Firmware for secure, efficient container execution. DockerSSD supports disaggregated storage pools, reducing host overhead and enhancing large-scale services like LLM inference. It achieves up to 2.0x better performance for I/O-intensive workloads, and 7.9x improvement in distributed LLM inference. |
| title | Containerized In-Storage Processing and Computing-Enabled SSD Disaggregation |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2506.06769 |