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Control divergence poses many problems in parallelizing loops. While predicated execution is commonly used to convert control dependence into data dependence, it often incurs high overhead because it allocates resources equally for both branches of a ...

Current GPUs maintain high programmability by abstracting the SIMD nature of the hardware as independent concurrent threads of control with hardware responsible for generating predicate masks to utilize the SIMD hardware for different flows of control. ...

Control and memory divergence between threads in the same execution bundle, or warp, can significantly throttle the performance of GPU applications. We exploit the observation that many GPU applications exhibit error tolerance to propose branch and data ...