Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Field |
|---|---|---|
2015 | FAST | Flash file system,FIFO (computing and electronics),Cache capacity,Workload,Cache,Computer science,Parallel computing,Cache algorithms,Real-time computing,Priority queue,Throughput |
DocType | Citations | PageRank |
Conference | 25 | 0.72 |
References | Authors | |
34 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Linpeng Tang | 1 | 25 | 1.05 |
| Qi Huang | 2 | 235 | 15.66 |
| Wyatt Lloyd | 3 | 714 | 27.53 |
| Sanjeev Kumar | 4 | 2727 | 139.04 |
| Kai Li | 5 | 5345 | 435.41 |