Data buffering optimization methods toward a uniform programming interface for gpu-based applications

Abstract

The massive computational power available in off-the shelf Graphics Processing Units (GPUs) can pave the way for its usage in general purpose applications. Current interfaces to program GPU operation are still oriented towards graphics processing. This paper is focused in disparities on those programming interfaces and proposes an extension to of the recently developed Caravela library that supports streambased computation. This extension implements effective methods to counterbalance the disparities and differences in graphics runtime environments. Experimental results show that these methods improve performance of GPU-based applications by more than 50% and demonstrate that the proposed extended interface can be an effective solution for generalpurpose programming on GPUs.