Parallel I/O, in the context of a computer, means the performance of multiple input/output operations at the same time, for instance simultaneously outputs to storage devices and display devices.[1] It is a fundamental feature of operating systems.[2]

One particular instance is parallel writing of data to disk; when file data is spread across multiple disks, for example in a RAID array, one can store multiple parts of the data at the same time, thereby achieving higher write speeds than with a single device.[3][4]

Other ways of parallel access to data include: Parallel Virtual File System, Lustre, GFS etc.

Contents

FeaturesEdit

Scientific computingEdit

It is used for scientific computing and not for databases. It breaks up support into multiple layers including High level I/O library, Middleware layer and Parallel file system.[5] Parallel File System manages the single view, maintains logical space and provides access to data files.[6]

StorageEdit

A single file may be stripped across one or more object storage target, which increases the bandwidth while accessing the file and available disk space.[7] The caches are larger in Parallel I/O and shared through distributed memory systems.[8][9][10][11]

BreakthroughsEdit

Companies have been running Parallel I/O on their servers to achieve results with regard to price and performance. Parallel processing is especially critical for scientific calculations where applications are not only CPU but also are I/O bound.[12]

See alsoEdit

ReferencesEdit

  1. ^ "Parallel I/O" (PDF). Johns Hopkins University.
  2. ^ "Introduction to Parallel I/O" (PDF). Oak Ridge National Laboratory.
  3. ^ "Introduction: The Parallel I/O Stack" (PDF). Cornell University.
  4. ^ "Introduction to Parallel I/O". The University of Texas at Austin.
  5. ^ "Parallel I/O". Scientific Computing Department.
  6. ^ "A Comprehensive Look at High Performance Parallel I/O". Berkeley Lab.
  7. ^ http://calcul.math.cnrs.fr/Documents/Manifestations/CIRA2011/2011-01_haefele_parallel_IO-workshop_Lyon.pdf
  8. ^ https://www.olcf.ornl.gov/wp-content/uploads/2013/05/OLCF-Data-Intro-IO-Gerber-FINAL.pdf
  9. ^ "A Comprehensive Look at High Performance Parallel I/O".
  10. ^ "Parallel I/O – Why, How, and Where to?". 2015-04-09.
  11. ^ Teng Wang; Kevin Vasko; Zhuo Liu; Hui Chen; Weikuan Yu (2016). "Enhance parallel input/output with cross-bundle aggregation". The International Journal of High Performance Computing Applications. 30 (2): 241–256.
  12. ^ Laghave, Nikhil; Sosonkina, Masha; Maris, Pieter; Vary, James P. (2009-05-25). Benefits of Parallel I/O in Ab Initio Nuclear Physics Calculations. Lecture Notes in Computer Science. 5544. pp. 84–93. doi:10.1007/978-3-642-01970-8_9. ISBN 9783642019692.