Abstract:
Logistic regression (LR) is a widely used machine
learning algorithm. It is regarded unsuitably slow for high
dimensional problems compared to other machine learning
algorithms such as SVM, decision trees and Bayes classifier.
In this paper we utilize the data parallel nature of the
algorithm to implement it on NVidia GPUs. We have
implemented this GPU-based LR on the newest generation
GPU with Compute Unified Device Architecture (CUDA).
Our GPU implementation is based on BFGS optimization
method. This implementation was extended to multiple GPU
and cluster environment. This paper describes the
performance gain while using GPU environment.
