@unpublished{mcallister2021kangaroo,
author = {McAllister, Sara and Berg, Benjamin and Tutuncu-Macias, Julian and Yang, Juncheng and Gunasekar, Sathya and Lu, Jimmy and Berger, Daniel S. and Beckmann, Nathan and Ganger, Gregory R.},
title = {Kangaroo: Caching Billions of Tiny Objects on Flash},
year = {2021},
month = {October},
abstract = {Many social-media and IoT services have very large working sets consisting of billions of tiny (~100 B) objects. Large, flash-based caches are important to serving these working sets at acceptable monetary cost. However, caching tiny objects on flash is challenging for two reasons: (i) SSDs can read/write data only in multi-KB pages that are much larger than a single object, stressing the limited number of times flash can be written; and (ii) very few bits per cached object can be kept in DRAM without losing flash's cost advantage. Unfortunately, existing flash-cache designs fall short of addressing these challenges: write-optimized designs require too much DRAM, and DRAM-optimized designs write flash too much.

We present Kangaroo, a new flash-cache design that optimizes both DRAM usage and flash writes to maximize cache performance while minimizing cost. Kangaroo combines a large, set-associative cache with a small, log-structured cache. The set-associative cache requires minimal DRAM, while the log-structured cache minimizes Kangaroo's flash writes. Experiments using traces from Facebook and Twitter show that Kangaroo achieves DRAM usage close to the best prior DRAM-optimized design, flash writes close to the best prior write-optimized design, and miss ratios better than both. Kangaroo's design is Pareto-optimal across a range of allowed write rates, DRAM sizes, and flash sizes, reducing misses by 29% over the state of the art. These results are corroborated with a test deployment of Kangaroo in a production flash cache at Facebook.},
url = {http://approjects.co.za/?big=en-us/research/publication/kangaroo-caching-billions-of-tiny-objects-on-flash/},
}