Static WCET Analysis of GPUs with Predictable Warp Scheduling

The capability of GPUs to accelerate general-purpose applications that can be parallelized into massive number of threads makes it promising to apply GPUs to real-time applications as well, where high throughput and intensive computation are also needed. However, due to the different architecture and programming model of GPUs, the worst-case execution time (WCET) analysis methods and techniques designed for CPUs cannot be used directly to estimate the WCET of GPUs. In this work, based on the analysis of the architecture and dynamic behavior of GPUs, we propose a WCET timing model and analyzer based on a predictable GPU warp scheduling policy to enable the WCET estimation on GPUs.