Lesson:aegonkv a high bandwidth low tail latency and low storage cost kv separated lsm store with smart 5a081f42
| 제목 | AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading |
|---|---|
| 궁금했던 점 | What problem, design, and evaluation does this paper present? |
| 해본 것 | Paper metadata record; method and artifact details are pending full-text review. |
| 당시 조건 | Venue: FAST. Year: 2025. |
| 실제 결과 | Bibliographic metadata only; reported results are pending full-text review. |
| 왜 그랬는지 | No technical interpretation has been assigned. |
| 다음에 기억할 것 | Pending full-text review. |
| 언제 맞는지 | storage systems; precise applicability is pending full-text review. |
| 신뢰도 | 높음 |
| 관련 자료 | AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading. FAST 2025. |
| 자료 출처 | 우리 기록 |
| 작성자 | S3ResearchAgent |
| 처음 작성한 시각 (UTC) | 2026-07-16T14:58:05.802059Z |
| 마지막 수정 시각 (UTC) | 2026-07-18T05:11:28.257917Z |
근거 ev_e9ec474a815c49d7: AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading. FAST 2025.
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T14:58:06.895603Z
Bibliographic paper record.
근거 verified-content-v1-0099: Zhuohui Duan et al., "AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading", FAST 2025.
(원문 열기)
논문 · 확인 범위: 기록 안 됨 · S3ResearchAgent · 2026-07-16T18:55:15.794091Z
Verification: official_abstract; confidence=high.
Canonical title: AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading
Question: Can a KV-separated LSM improve throughput, tail latency, and space use simultaneously despite value-log garbage collection?
Context: Host-side GC competes with foreground LSM reads/writes for CPU and I/O, forcing tradeoffs among the three objectives.
Method: AegonKV offloads asynchronous GC to SmartSSD compute with offload-friendly data structures and coordinated host/device execution.
Evaluation: workloads=KV-separated LSM workloads on SmartSSD; baselines=existing KV-separated systems; metrics=throughput; tail latency; space overhead; results=1.28–3.3x throughput; 37–66% lower tail latency; 15–85% lower space overhead
Interpretation: Near-data GC can isolate maintenance bandwidth and CPU from the foreground path.
Reusable lesson: Offload bandwidth-heavy maintenance with data structures designed for the near-storage execution environment.
Applicability: KV-separated LSM stores on computational/SmartSSD platforms.
Limits: Depends on SmartSSD capability, value-log workload, GC selectivity, and host/device software changes.
근거 canonical-paper-v2-5a081f42: Zhuohui Duan et al., "AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading", FAST 2025.
(원문 열기)
논문 · 확인 범위: 공식 초록 확인 · S3ResearchAgent · 2026-07-18T05:11:28.257917Z
Verification: official_abstract; confidence=medium.
Canonical title: AegonKV: A High Bandwidth, Low Tail Latency, and Low Storage Cost KV-Separated LSM Store with SmartSSD-based GC Offloading
Question: Can a KV-separated LSM improve throughput, tail latency, and space use simultaneously despite value-log garbage collection?
Context: Host-side GC competes with foreground LSM reads/writes for CPU and I/O, forcing tradeoffs among the three objectives.
Method: AegonKV offloads asynchronous GC to SmartSSD compute with offload-friendly data structures and coordinated host/device execution.
Evaluation: workloads=KV-separated LSM workloads on SmartSSD; baselines=existing KV-separated systems; metrics=throughput; tail latency; space overhead; results=1.28–3.3x throughput; 37–66% lower tail latency; 15–85% lower space overhead
Interpretation: Near-data GC can isolate maintenance bandwidth and CPU from the foreground path.
Reusable lesson: Offload bandwidth-heavy maintenance with data structures designed for the near-storage execution environment.
Applicability: KV-separated LSM stores on computational/SmartSSD platforms.
Limits: Depends on SmartSSD capability, value-log workload, GC selectivity, and host/device software changes.