Details

Autor(en) / Beteiligte

• Chen, Feng
• Hou, Binbing
• Lee, Rubao

Titel

Internal Parallelism of Flash Memory-Based Solid-State Drives

Ist Teil von

• ACM transactions on storage, 2016-06, Vol.12 (3), p.1-39

Erscheinungsjahr

2016

Quelle

ACM Digital Library

Beschreibungen/Notizen

• A unique merit of a solid-state drive (SSD) is its internal parallelism . In this article, we present a set of comprehensive studies on understanding and exploiting internal parallelism of SSDs. Through extensive experiments and thorough analysis, we show that exploiting internal parallelism of SSDs can not only substantially improve input/output (I/O) performance but also may lead to some surprising side effects and dynamics. For example, we find that with parallel I/Os, SSD performance is no longer highly sensitive to access patterns (random or sequential), but rather to other factors, such as data access interferences and physical data layout. Many of our prior understandings about SSDs also need to be reconsidered. For example, we find that with parallel I/Os, write performance could outperform reads and is largely independent of access patterns, which is opposite to our long-existing common understanding about slow random writes on SSDs. We have also observed a strong interference between concurrent reads and writes as well as the impact of physical data layout to parallel I/O performance. Based on these findings, we present a set of case studies in database management systems, a typical data-intensive application. Our case studies show that exploiting internal parallelism is not only the key to enhancing application performance, and more importantly, it also fundamentally changes the equation for optimizing applications. This calls for a careful reconsideration of various aspects in application and system designs. Furthermore, we give a set of experimental studies on new-generation SSDs and the interaction between internal and external parallelism in an SSD-based Redundant Array of Independent Disks (RAID) storage. With these critical findings, we finally make a set of recommendations to system architects and application designers for effectively exploiting internal parallelism.