Finite difference (FD) methods are the most prevalent numerical modeling algorithms for simulating linear wave propagation phenomena in geophysics, electromagnetics, and aero- or marine-acoustics applications. Unfortunately, evaluating time evolution for waves in large-scale 2D or 3D domains is computationally demanding and data-intensive. As such, its programs are often exclusively executed on high performance supercomputers. In this paper, we propose a solution to accelerate the execution of realistic wave field modeling problems on a baseline reconfigurable computing (RC) platform. By adopting appropriate high-order temporal and spatial FD schemes along with efficient on-chip data buffering structure, we alleviate external memory bandwidth bottleneck at the cost of increased floating-point computations, which fortunately can be absorbed by the pipelined computing engine with negligible speed penalty. In this way, a balance point can always be reached where the utilization of onboard reconfigurable hardware resources and external memory bandwidth are all optimized. The desirable simplicity and scalability properties of our method make it compatible with most commercial RC platforms. Moreover, our implementation is consistent with the prevalent PC-Cluster systems and can achieve better price-performance ratio along with much lower power consumption. 2006 Elsevier B.V. All rights reserved.
