Reconfigurable supercomputing (RSC) combines programmable logic chips with high performance microprocessors, all communicating over a high bandwidth, low latency interconnection network. Reconfigurable hardware has demonstrated an order of magnitude speedup on compute-intensive kernels in science and engineering. However, translating high level algorithms to programmable hardware is a formidable barrier to the use of these resources by scientific programmers . A library-based approach has been suggested, so that the software application can call standard library functions that have been optimized for hardware. The potential benefits of this approach are evaluated on several large scientific supercomputing applications. It is found that hardware linear algebra libraries would be of little benefit to the applications analyzed. To maximize performance of supercomputing applications on RSC, it is necessary to identify kernels of high computational density that can be mapped to hardware, c...
Maya Gokhale, Christopher Rickett, Justin L. Tripp