Philipp Lucas

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In the last few years, GPUs have become new, promising targets for general purpose programming. Their inherent parallel architecture makes them particularly suited for scientific numerical computations with high arithmetical density. There have been several proposals to exploit the computational power of GPUs for data-parallel algorithms. These approaches(More)
In the last few years, PC technology underwent a paradigm shift. The current trend leads aways from raising sequential performance to enhancing the available parallelism. The rapid performance increase of Graphics Processing Units (GPUs) is a part of this trend. However, it is difficult to harness the computational potential because for the longest time(More)
Retargeting a compiler's back end to a new architecture is a time-consuming process. This becomes an evident problem in the area of programmable graphics hardware (graphics processing units, GPUs) or embedded processors, where architectural changes are faster than elsewhere. We propose the object-oriented rewrite system OORS to overcome this problem. Using(More)