GPU-accelerated molecular modeling coming of age

Graphics processing units (GPUs) have traditionally been used in molecular modeling solely for visualization of molecular structures and animation of trajectories resulting from molecular dynamics simulations. Modern GPUs have evolved into fully programmable, massively parallel co-processors that can now be exploited to accelerate many scientific computations, typically providing about one order of magnitude speedup over CPU code and in special cases providing speedups of two orders of magnitude. This paper surveys the development of molecular modeling algorithms that leverage GPU computing, the advances already made and remaining issues to be resolved, and the continuing evolution of GPU technology that promises to become even more useful to molecular modeling. Hardware acceleration with commodity GPUs is expected to benefit the overall computational biology community by bringing teraflops performance to desktop workstations and in some cases potentially changing what were formerly batch-mode computational jobs into interactive tasks.

Figure optionsDownload high-quality image (172 K)Download as PowerPoint slideResearch highlights▶ GPUs have become powerful accelerators for molecular modeling applications. ▶ GPUs provide better price-performance than traditional computing techniques. ▶ Recent GPUs support double-precision arithmetic and error correcting memory. ▶ GPU clusters consume less space, power, and cooling than traditional clusters. ▶ GPU accelerated implementations of simulation tools are still maturing.