Accelerating High Performance Computing Applications: Using CPUs, GPUs, Hybrid CPU/GPU, and FPGAs

Most modern scientific research requires significant advanced modeling, simulation, and visualization. Due to the growing complexity of physical models, these research activities increasingly are requiring more and more High Performance Computing (HPC) resources and this trend is predicted to grow even stronger. Considering this growth in HPC applications, the traditional parallel computing model based solely on Central Processing Units (CPUs) is unable to meet the scientific needs of the researchers. HPC requirements are expected to reach exascale in this decade. There are several approaches to enhance and speed up HPC, some of the most promising involve hybrid solutions. In this paper, we describe existing state of hardware and accelerators for HPC. Such components include CPUs, Graphics Processing Units (GPU), and Field-Programmable Gate Arrays (FPGAs). Various hybrid implementations of these accelerators are presented and compared. Examples of the top supercomputers are included as well, together with their hardware configurations. Concluding this paper, we discuss our prediction of further HPC hardware trends in support of advanced modeling, simulation, and visualization.