𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Load-sharing algorithms for parallel database processing on shared-everything multiprocessors

✍ Scribed by Yasuhiro Hirano; Tetsuji Satoh; Ushio Inoue; Katsumi Teranaka


Publisher
John Wiley and Sons
Year
1993
Tongue
English
Weight
665 KB
Volume
24
Category
Article
ISSN
0882-1666

No coin nor oath required. For personal study only.

✦ Synopsis


Abstract

This paper describes new load‐sharing algorithms for parallel database processing. There is a trade‐off between overhead and load unbalance in ordinary algorithms. The proposed algorithms solve the tradeoff by varying the number of tasks allocated at one time, which is fixed in ordinary algorithms. Performance evaluations show that the proposed algorithms achieve fair load sharing with low overhead, independent of database size, the number of processors and data distribution.


πŸ“œ SIMILAR VOLUMES


Parallel algorithms for QR decomposition
✍ K. Wright πŸ“‚ Article πŸ“… 1991 πŸ› Elsevier Science 🌐 English βš– 733 KB

Wright K., Parallel algorithms for QR decomposition on a shared memory multiprocessor, Parallel Computing 17 (1991) 779-790. Various parallel implementations of algorithms for the QR decomposition of a matrix are compared using shared memory multiprocessors. Algorithms based on both Givens and Hous

A load balancing algorithm on multiproce
✍ Nariyoshi Yamai Member; Shinji Shimojo; Hideo Miyahara Members πŸ“‚ Article πŸ“… 1990 πŸ› John Wiley and Sons 🌐 English βš– 621 KB

## Abstract To use multiprocessor systems efficiently, several load balancing algorithms have been adopted widely. However, most of the algorithms proposed so far can be applied to FCFS systems, and only a few can be applied to time‐sharing systems in wide use today. This paper proposes a load bala

Usefulness of adaptive load sharing for
✍ Clarke, Sheldon; Dandamudi, Sivarama P. πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 128 KB

Networks of workstations (NOWs) can be used for parallel processing by using public domain software like PVM. However, NOW-based parallel processing suffers from node heterogeneity, background load variations, and high-latency, low-bandwidth communication network. Previous studies on load sharing in