Parallelizing multiple linear regression for speed and redundancy: an empirical study^∗

^∗This research was supported by the Army Research Office under contract number DAAL03-87-K-0087, by the Office of Naval Research under contract number N00014-J-89-1807 and by the Virginia Center for Innovative Technology.

Abstract

The purpose of this paper is to present a parallel implementation of multiple linear regression. We discuss the multiple linear regression model. Traditionally parallelism has been used for either speed up or redundancy (hence reliability). With stochastic data, by clever parsing and algorithm development, it is possible to achieve both speed and reliability enhancement. We demonstrate this with multiple linear regression.

^∗This research was supported by the Army Research Office under contract number DAAL03-87-K-0087, by the Office of Naval Research under contract number N00014-J-89-1807 and by the Virginia Center for Innovative Technology.

^∗This research was supported by the Army Research Office under contract number DAAL03-87-K-0087, by the Office of Naval Research under contract number N00014-J-89-1807 and by the Virginia Center for Innovative Technology.

Notes

^∗This research was supported by the Army Research Office under contract number DAAL03-87-K-0087, by the Office of Naval Research under contract number N00014-J-89-1807 and by the Virginia Center for Innovative Technology.