2 research outputs found
Modelling and Managing SSD Write-amplification
How stable is the performance of your flash-based Solid State Drives (SSDs)?
This question is central for database designers and administrators, cloud
service providers, and SSD constructors. The answer depends on
write-amplification, i.e., garbage collection overhead. More specifically, the
answer depends on how write-amplification evolves in time.
How then can one model and manage write-amplification, especially when
application workloads change? This is the focus of this paper. Managing
write-amplification boils down to managing the surplus physical space, called
over-provisioned space. Modern SSDs essentially separate the physical space
into several partitions, based on the update frequency of the pages they
contain, and divide the over-provisioned space among the groups so as to
minimize write-amplification. We introduce Wolf, a block manager that allocates
over-provisioned space to SSD partitions using a near-optimal closed-form
expression, based on the sizes and update frequencies of groups of pages. Our
evaluation shows that Wolf is robust to workloads change, with an improvement
factor of 2 with respect to the state-of-the-art. We also show that Wolf
performs comparably and even slightly better than the state of the art with
stable workloads (over 20% improvement with a TPC-C workload)