Massively Parallel kNN using CUDA on Spam-Classification

摘要

Email Spam-classification is a fundamental, unseen element of everyday life. As email communication becomes more prolific, and email systems become more robust, it becomes increasingly necessary for Spam-classification systems to run accurately and efficiently while remaining all but invisible to the user. We propose a massively parallel implementation of Spam-classification using the k-Nearest Neighbors (kNN) algorithm on nVIDIA GPUs using CUDA. Being very simple and straightforward, the performance of the kNN search degrades dramatically for large data sets, since the task is computationally intensive. By utilizing the benefits of GPUs and CUDA, we seek to overcome that cost.