Acceleration methodology for the implementation of scientific application on reconfigurable hardware
Phillip Murray Martin · 2009
The role of heterogeneous multi-core architectures in the industrial and scientific computing community is expanding. For researchers to increase the performance of complex applications, a multifaceted approach is needed to utilize emerging reconfigurable computing (RC) architectures. First, the method for accelerating applications must provide flexible solutions for fully utilizing key architecture traits across platforms. Secondly, the approach needs to be readily accessible to application scientists. A recent trend toward emerging disruptive architectures is an important signal that fundamental limitations in traditional high performance computing (HPC) are limiting break through research. To respond to these challenges, scientists are under pressure to identify new programming methodologies and elements in platform architectures that will translate into enhanced program efficacy. Reconfigurable computing (RC) allows the implementation of almost any computer architecture trait, but identifying which traits work best for numerous scientific problem domains is difficult. However, by leveraging the existing underlying framework available in field programmable gate arrays (FPGAs), it is possible to build a method for utilizing RC traits for accelerating scientific applications. By contrasting both hardware and software changes, RC platforms afford developers the ability to examine various architecture characteristics to find those best suited for production-level scientific applications. The flexibility afforded by FPGAs allow these characteristics to then be extrapolated to heterogeneous, multi-core and general-purpose computing on graphics processing units (GP-GPU) HPC platforms. Additionally by coupling high-level