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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)
The CGiS programming language is designed to open up the parallel performance possibilities of graphics processing units (GPUs) to general purpose programmers. This tool demonstration paper sums up the ideas behind CGiS and the compiler framework and shows its usage.
In this paper, we present the recent developments on the design and implementation of the data-parallel programming language CGiS. CGiS is devised to facilitate use of the data-parallel resources of current graphics processing units (GPUs) for scientific programming.
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)
Many embedded control systems work in different operating modes, for example start-up, stand-by, shutdown and failure mode. These different operating modes usually have different timing requirements, and the different functional behaviour also leads to differences in timing behaviour. A Worst-Case Execution Time (WCET) analysis of such a system needs to… (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)