DATE: Thursday, August 21, 2003
TIME: Noon - 1 pm
PLACE: Wean Hall 8220

Jiri Schindler
Carnegie Mellon University

Matching Application Access Patterns to Storage Device Characteristics

Conventional computer systems have insufficient information about storage device performance characteristics. As a consequence, they utilize the available device resources inefficiently, which, in turn, results in poor application performance. In contrast, a few high-level, device-independent hints encapsulating unique storage device characteristics can achieve significant I/O performance gains without breaking the established abstraction of a storage device as a linear address space of fixed-size blocks. A piece of system software (here referred to as storage manager), which translates application requests into individual I/Os, can automatically match application access patterns to the provided characteristics. This results in more efficient utilization of storage devices and thus improved application performance.

This dissertation (i) identifies specific features of disk drives, disk arrays, and MEMS-based storage devices not exploited by conventional systems, (ii) quantifies the potential performance gains these features offer, and (iii) demonstrates on three different implementations (FFS file system, database storage manager, and disk array logical volume manager) the benefits to the applications using these storage managers. It describes two specific attributes: the Access Delay Boundaries attribute delineates efficient accesses to storage devices and the Parallelism attribute exploits the parallelism inherent to a storage device. In addition to improving application performance, The two described performance attributes mesh well with existing storage manager data structures, requiring minimal changes to their code. Most importantly, they simplify the error-prone task of performance tuning and have the biggest impact on systems with regular access patterns.

Jiri Schindler is a fifth-year graduate student at Carnegie Mellon's Parallel Data Laboratory working under Prof. Greg Ganger. Jiri is interested in file and storage systems. In particular, he is investigating ways of regaining the performance that is available inside a storage device but lost on the outside due to high-level interfaces.

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