Exploring graphics processor performance for general purpose applications

Abstract

Graphics processors are designed to perform many floating-point operations per second. Consequently, they are an attractive architecture for high-performance computing at a low cost. Nevertheless, it is still not very clear how to exploit all their potential for general-purpose applications. In this work we present a comprehensive study of the performance of an application executing on the GPU. In addition, we analyze the possibility of using the graphics card to extend the life-time of a computer system. In our experiments we compare the execution on a mid-class GPU (NVIDIA GeForce FX 5700LE) with a high-end CPU (Pentium 4 3.2 GHz). The results show that to achieve high speedup with the GPU you need to: (1) format the vectors into two-dimensional arrays; (2) process large data arrays; and (3) perform a considerable amount of operations per data element. Finally, we study the performance when upgrading a low-end system by simply adding a GPU. This solution is cheaper, results in smaller power consumption and achieves higher speedup (8.1x versus 1.3x) than a full upgrade to a new high-end system.