Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Accelerated volume rendering and tomographic reconstruction using texture mapping hardware
VVS '94 Proceedings of the 1994 symposium on Volume visualization
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Ray tracing on programmable graphics hardware
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Brook for GPUs: stream computing on graphics hardware
ACM SIGGRAPH 2004 Papers
Direct approaches to exploit many-core architecture in bioinformatics
Future Generation Computer Systems
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Work involving the use of application acceleration devices is showing great promise, however, there are still major obstacles preventing their widespread adoption. Currently the process of porting applications to an accelerator requires expertise in both the computer science and application domains, due to the lack of abstraction available. We present our work associated with the development of a novel solution to this abstraction problem; an intelligent semi-automatic application porting system, that will allow a higher level of abstraction, to be presented to the end user, while maintaining reasonable performance levels. A prototype system has been constructed that can successfully port applications to Graphics Processing Units (GPUs) and shows promising results in terms of performance comparisons between CPU and GPU. We are presently extending our prototype to other application acceleration devices and to allow the automatic selection of the most appropriate device for an application using Machine Learning techniques. We expect our work and results will be of widespread interest to the increasing community involved in porting code to application accelerators.