Performance Predictions for General-Purpose Computation on GPUs
Centre for Adv. Media Technol., Nanyang Technological University, Singapore
In ICPP ’07: Proceedings of the 2007 International Conference on Parallel Processing (2007), 50.
@conference{liu2007performance,
title={Performance Predictions for General-Purpose Computation on GPUs},
author={Liu, W. and Schmidt, B.},
booktitle={Parallel Processing, 2007. ICPP 2007. International Conference on},
pages={50},
issn={0190-3918},
year={2007},
organization={IEEE}
}
Using modern graphics processing units for no-graphics high performance computing is motivated by their enhanced programmability, attractive price/performance ratio and incredible growth in speed. Although the pipeline of a modern graphics processing unit (GPU) permits high throughput and more concurrency, they bring more complexities in analyzing the performance of GPU-based applications. In this paper, we identify factors that determine performance of GPU-based applications. We then classify them into three categories: data-linear, data-constant and computation-dependent. According to the characteristics of these factors, we propose a performance model for each factor. These models are then used to predict the performance of bio-sequence database scanning application on GPUs. Theoretical analyses and measurements show that our models can achieve precise performance predictions.
November 2, 2010 by hgpu
