Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications
School of Computing Sciences and Engineering, VIT University, India
International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 2, No. 5, 2011
@article{gupta2011performance,
title={Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications},
author={Gupta, S. and Babu, M.R.},
year={2011}
}
In Natural Language Processing (NLP) applications, the main time-consuming process is string matching due to the large size of lexicon. In string matching processes, data dependence is minimal and hence it is ideal for parallelization. A dedicated system with memory interleaving and parallel processing techniques for string matching can reduce this burden of host CPU, thereby making the system more suitable for real-time applications. Now it is possible to apply parallelism using multi-cores on CPU, though they need to be used explicitly to achieve high performance. Recent GPUs hold a large number of cores, and have a potential for high performance in many general purpose applications. Programming tools for multi-cores on CPU and a large number of cores on GPU have been formulated, but it is still difficult to achieve high performance on these platforms. In this paper, we compare the performance of single-core, multi-core CPU and GPU using such a Natural Language Processing application.
December 6, 2011 by hgpu
