FPGA-based accelerator development for non-engineers

In todays world of big-data computing, access to massive, complex data sets has reached an unprecedented level, and the task of intelligently processing such data into useful information has become a growing concern to the high-performance computing community. However, domain experts, who are the brains behind this processing, typically lack the skills required to build FPGA-based hardware accelerators ideal for their applications, as traditional development flows targeting such hardware require digital design expertise. This work proposes a usable, end-to-end accelerator development methodology that attempts to bridge this gap between domain-experts and the vast computational capacity of FPGA-based heterogeneous platforms. To accomplish this, a development flow was assembled, targeting the Convey Hybrid-Core HC-1 heterogeneous platform and utilizing an existing graphical design environment for design entry. The efficacy of the flow in extending FPGA-based acceleration to non-engineers in the life sciences was informally tested at an NSF-funded summer workshop, organized and hosted by a bioinformatics organization at a particular university. A group of five life-science-focused, non-engineer participants made significant modifications to a bare-bones Smith-Waterman accelerator, extending its functionality and improving performance.