Achieving portability and efficiency over chip heterogeneous multiprocessor systems

Emerging programming models for chip heterogeneous multiprocessor (CHMP) systems elevate architecture details up into the source code. This eliminates portability and requires designers to navigate a multidimensional search space when trying to optimize designs. In this paper, we present an approach that reinstates portability through a combination of polymorphic functions and an adaptive runtime system. Together they enable runtime profiling and dynamic scheduling of unaltered source code across systems with different combinations of heterogeneous resources. Our results verify the ability of our programming model and runtime system to re-enable the notion of writing code once and run anywhere. Runtime results show how runtime tuning can increase resource utilization and provide performance increases as the number and heterogeneity of computing resources increases.