TY - GEN
T1 - RIPQ
T2 - 13th USENIX Conference on File and Storage Technologies, FAST 2015
AU - Tang, Linpeng
AU - Huang, Qi
AU - Lloyd, Wyatt
AU - Kumar, Sanjeev
AU - Li, Kai
N1 - Funding Information:
Acknowledgments We are grateful to our shepherd Philip Shilane, the anonymous reviewers of the FAST program committee, Xin Jin, Xiaozhou Li, Kelvin Zou, Mohsin Ali, Ken Birman, and Robbert van Renesse for their extensive comments that substantially improved this work. We are also grateful to Brian Pane, Bryan Alger, Peter Ruibal, and other Facebook engineers who gave feedback that improved our designs. Our work is supported by Facebook, NSF grant BCS-1229597, Intel, DARPA MRC program, and Princeton fellowship.
PY - 2015
Y1 - 2015
N2 - Facebook uses flash devices extensively in its photo-caching stack. The key design challenge for an efficient photo cache on flash at Facebook is its workload: many small random writes are generated by inserting cache-missed content, or updating cache-hit content for advanced caching algorithms. The Flash Translation Layer on flash devices performs poorly with such a workload, lowering throughput and decreasing device lifespan. Existing coping strategies under-utilize the space on flash devices, sacrificing cache capacity, or are limited to simple caching algorithms like FIFO, sacrificing hit ratios. We overcome these limitations with the novel Restricted Insertion Priority Queue (RIPQ) framework that supports advanced caching algorithms with large cache sizes, high throughput, and long device lifespan. RIPQ aggregates small random writes, co-locates similarly prioritized content, and lazily moves updated content to further reduce device overhead. We show that two families of advanced caching algorithms, Segmented-LRU and Greedy-Dual-Size-Frequency, can be easily implemented with RIPQ. Our evaluation on Facebook’s photo trace shows that these algorithms running on RIPQ increase hit ratios up to ~20% over the current FIFO system, incur low overhead, and achieve high throughput.
AB - Facebook uses flash devices extensively in its photo-caching stack. The key design challenge for an efficient photo cache on flash at Facebook is its workload: many small random writes are generated by inserting cache-missed content, or updating cache-hit content for advanced caching algorithms. The Flash Translation Layer on flash devices performs poorly with such a workload, lowering throughput and decreasing device lifespan. Existing coping strategies under-utilize the space on flash devices, sacrificing cache capacity, or are limited to simple caching algorithms like FIFO, sacrificing hit ratios. We overcome these limitations with the novel Restricted Insertion Priority Queue (RIPQ) framework that supports advanced caching algorithms with large cache sizes, high throughput, and long device lifespan. RIPQ aggregates small random writes, co-locates similarly prioritized content, and lazily moves updated content to further reduce device overhead. We show that two families of advanced caching algorithms, Segmented-LRU and Greedy-Dual-Size-Frequency, can be easily implemented with RIPQ. Our evaluation on Facebook’s photo trace shows that these algorithms running on RIPQ increase hit ratios up to ~20% over the current FIFO system, incur low overhead, and achieve high throughput.
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M3 - Conference contribution
AN - SCOPUS:85077094349
T3 - Proceedings of the 13th USENIX Conference on File and Storage Technologies, FAST 2015
SP - 373
EP - 386
BT - Proceedings of the 13th USENIX Conference on File and Storage Technologies, FAST 2015
PB - USENIX Association
Y2 - 16 February 2015 through 19 February 2015
ER -