SC Conference - Activity Details

Andy Keane  (NVIDIA)

GPU Software Tools

Wednesday,  11:30AM - 12:00PM

Room 19A/19B

The inherently parallel architecture of today's GPUs can offer HPC professionals a boost in speed anywhere from 8X to over 400X, depending on the application. However, if developing software for the parallel processor is complicated, developers will not use it no matter the potential performance. New programming models, such as the CUDA programming environment have also entered the industry seeking to address this challenge - allowing developers to use the familiar, industry standard language of C. CUDA allows developers to distribute work across the "many-cores" architecture of GPUs without the need to learn a new and complex programming language. As a new, alternative way of approaching the challenges associated with data-intensive computation on a processor technology already present in consumer PCs, workstations and servers, the potential of GPU Computing is huge. This presentation will discuss these exciting new technologies in direct relation to real challenges facing organizations and will examine deployments of this technology in fields such as oil and gas, finance and medical imaging.