摘要

Molecular dynamics (MD) is a large-scale, communication-intensive problem that has been the subject of high-performance computing research and acceleration for years. Not surprisingly, the most success in accelerating MD comes from specialized systems such as the Anton machine. In this paper, we describe Novo-G# (novo-jee-sharp), a multi-node reconfigurable system designed for the acceleration of communication-intensive scientific problems in general, and MD in particular. This system provides a high-bandwidth, low-latency 3D torus network to allow direct communication between kernels running on multiple field-programmable gate arrays. We also present a performance model for Novo-G# running the 3D Fast Fourier Transform (FFT) kernel that forms the core of MD simulations. We validate the model against published Anton performance data and through initial hardware experiments on Novo-G#. Finally, through simulation studies, we show that this system at scale performs better than specialized systems like Anton and outperforms established CPU-based clusters like Blue Gene/Q by an order of magnitude for the 3D FFT kernel, with greater flexibility and lower costs.

  • 出版日期2016-6-10