We report on our experiences retargeting the seismic processing message-passing application Seis1.1 [11] to an SGI Challenge shared-memory multiprocessor. Our primary purpose in doing so is to provide a shared-address-space (SAS) version of the application for inclusion in the new high performance SPEChpc96 Benchmark Suite. As a result of this work wehave determined the language constructs necessary to express Seis1.1 in the SAS programming model. In addition, we havecharacterized the performance of the SAS versus message-passing programming models for this application on a shared-memory multiprocessor
