Panda: Fast access to persistent arrays using high-level interfaces and server directed input/output

Multidimensional arrays are a fundamental data type in scientific computing and are used extensively across a broad range of applications. Often these arrays are persistent, i.e., they outlive the invocation of the program that created them. Portability and performance with respect to input and output (i/o) pose significant challenges to applications accessing large persistent arrays, especially in distributed-memory environments. A significant number of scientific applications perform conceptually simple array i/o operations, such as reading or writing a subarray, an entire array, or a list of arrays. However, the algorithms to perform these operations efficiently on a given platform may be complex and non-portable, and may require costly customizations to operating system software.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Seamons, Kent Eldon

Contributors dc:contributor

• Winslett, Marianne

• Engineering, System Science
• Computer Science

Statement dc:rights

• Copyright 1996 Seamons, Kent Eldon

Language dc:language

eng

Identifier

9780591088489
AAI9702660
(UMI)AAI9702660

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/22649