Systems evaluation demonstrates execution strategies for application kernels across heterogeneous systems, highlighting solutions to bridge programmer productivity with computational speed.
Major simultaneous disruptions are currently under way in both hardware and software. In hardware, ``extreme heterogeneity'' has become critical to sustaining cost and performance improvements after Moore's Law, but poses productivity and portability challenges for developers. In software, the rise of large-scale data science is driven by developers who come from diverse backgrounds and, moreover, who demand the rapid prototyping and interactive-notebook capabilities of high-productivity languages like Python.
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Zhou et al. (2020) studied this question.
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