Scientific Computing Applications on a Stream Processor

Stream processors, developed for the stream programming model, perform well on media applications. In this paper we examine the applicability of a stream processor to scientific computing applications. Eight scientific applications, each having different performance characteristics, are mapped to a stream processor. Due to the novelty of the stream programming model, we show how to map programs in a traditional language, such as FORTRAN. In a stream processor system, the management of system resources is the programmers´ responsibility. We present several optimizations, which enable mapped programs to exploit various aspects of the stream processor architecture. Finally, we analyze the performance of the stream processor and the presented optimizations on a set of scientific computing applications. The stream programs are from 1.67 to 32.5 times faster than the corresponding FORTRAN programs on an Itanium 2 processor, with the optimizations playing an important role in realizing the performance improvement.