CUBA

Abstract

Data-parallel co-processors have the potential to improve performance in highly parallel regions of code when coupled to a general-purpose CPU. However, applications often have to be modified in non-intuitive and complicated ways to mitigate the cost of data marshalling between the CPU and the co-processor. In some applications the overheads cannot be amortized and co-processors are unable to provide benefit. The additional effort and complexity of incorporating co-processors makes it difficult, if not impossible, to effectively utilize co-processors in large applications.