  As its price per bit drops, SSD is increasingly becoming the default storage
medium for cloud application databases. However, it has not become the
preferred storage medium for key-value caches, even though SSD offers more than
10x lower price per bit and sufficient performance compared to DRAM. This is
because key-value caches need to frequently insert, update and evict small
objects. This causes excessive writes and erasures on flash storage, since
flash only supports writes and erasures of large chunks of data. These
excessive writes and erasures significantly shorten the lifetime of flash,
rendering it impractical to use for key-value caches. We present Flashield, a
hybrid key-value cache that uses DRAM as a "filter" to minimize writes to SSD.
Flashield performs light-weight machine learning profiling to predict which
objects are likely to be read frequently before getting updated; these objects,
which are prime candidates to be stored on SSD, are written to SSD in large
chunks sequentially. In order to efficiently utilize the cache's available
memory, we design a novel in-memory index for the variable-sized objects stored
on flash that requires only 4 bytes per object in DRAM. We describe Flashield's
design and implementation and, we evaluate it on a real-world cache trace.
Compared to state-of-the-art systems that suffer a write amplification of 2.5x
or more, Flashield maintains a median write amplification of 0.5x without any
loss of hit rate or throughput.

Operating Systems