A Programming Framework for Scientific Applications on CPU-GPU Systems [report]

John Owens
2013 unpublished
I was awarded the DOE's Early Career Principal Investigator Award in 2004. This was the single most important event in my early career; it validated the research program I had begun and it launched me into a productive research career. It also opened up relationships with DOE scientists across the country. Your confidence in me is very, very, very much appreciated. At a high level, my research interests center around designing, programming, and evaluating computer systems that use new
more » ... to solve interesting problems. The rapid change of technology allows a variety of different architectural approaches to computationally difficult problems, and a constantly shifting set of constraints and trends makes the solutions to these problems both challenging and interesting. One of the most important recent trends in computing has been a move to commodity parallel architectures. This sea change is motivated by the industry's inability to continue to profitably increase performance on a single processor and instead to move to multiple parallel processors. In the period of review, my most significant work has been leading a research group looking at the use of the graphics processing unit (GPU) as a general-purpose processor. GPUs can potentially deliver superior performance on a broad range of problems than their CPU counterparts, but effectively mapping complex applications to a parallel programming model with an emerging programming environment is a significant and important research problem. As the computing industry moves toward ubiquitous parallel hardware and software, the lessons learned from the GPU, the first commodity parallel processor, are even more important. Our field of "GPU computing" (also called "general-purpose computation on the GPU" [GPGPU]) continues to have a substantial and growing impact on mainstream computing. As one of the early researchers in the field, I was privileged to lead two highly-cited articles 1 , supported by this
doi:10.2172/1069280 fatcat:57sldzyzebdcbkrkromt5sb3fe