ACM Transactions on Storage · 2017 · 159 citations · 37 references
ComputingComputer EngineeringComputer ScienceFault ToleranceFault-tolerant ComputingStorage SystemsGarbage CollectionLatency OptimizationSolid-state Drive ArchitectureSolid-state StorageStorage Fault ToleranceFlash Memory DevicesFlush ControlFlush OperationsLatency Reduction TechniquesStorage Garbage CollectionStorage Performance OptimizationTail LatencyTail Latency Reduction
Flash storage dominates, yet SSDs often fail to meet performance expectations because garbage collection induces long‑tail latencies. The authors propose tt Flash, a tiny‑tail SSD designed to eliminate GC‑induced tail latencies. tt Flash achieves this through four strategies—plane‑blocking GC, rotating GC, GC‑tolerant read, and GC‑tolerant flush—leveraging modern SSD controllers, parity redundancy, capacitor‑backed RAM, and intra‑plane copyback. Evaluation shows tt Flash approaches a no‑GC scenario, being only 1.0–2.6× slower than no‑GC between the 99th and 99.99th percentiles, compared to 5–138× slowdowns for a baseline approach.
Flash storage has become the mainstream destination for storage users. However, SSDs do not always deliver the performance that users expect. The core culprit of flash performance instability is the well-known garbage collection (GC) process, which causes long delays as the SSD cannot serve (blocks) incoming I/Os, which then induces the long tail latency problem. We present tt F lash as a solution to this problem. tt F lash is a “tiny-tail” flash drive (SSD) that eliminates GC-induced tail latencies by circumventing GC-blocked I/Os with four novel strategies: plane-blocking GC, rotating GC, GC-tolerant read, and GC-tolerant flush. These four strategies leverage the timely combination of modern SSD internal technologies such as powerful controllers, parity-based redundancies, and capacitor-backed RAM. Our strategies are dependent on the use of intra-plane copyback operations. Through an extensive evaluation, we show that tt F lash comes significantly close to a “no-GC” scenario. Specifically, between the 99 and 99.99th percentiles, tt F lash is only 1.0 to 2.6× slower than the no-GC case, while a base approach suffers from 5–138× GC-induced slowdowns.
37
Giuseppe DeCandia, Deniz Hastorun, Madan Jampani et al. · 2007 · 3.5K citations
Luiz André Barroso · Communications of the ACM · 2013 · 1.7K citations
Design tradeoffs for SSD performance
Nitin Agrawal, Vijayan Prabhakaran, Ted Wobber et al. · 2008 · 886 citations