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While high-efficiency machines are increasingly embracing heterogeneous architectures and massive multithreading, contemporary mainstream programming languages reflect a mental model in which processing elements are homogeneous, concurrency is limited, and memory is a flat undifferentiated pool of storage. Moreover, the current state of the art in programming heterogeneous machines tends towards using separate programming models, such as OpenMP and CUDA, for different portions of the machine.doi:10.1109/sc.2012.48 dblp:conf/sc/GarlandKZ12 fatcat:ua2yayf6svf5nbk7nlmlks267i