Experiments for Predictable Execution of GPU Kernels

Abstract

Multi-Processor Systems-on-Chip (MPSoC) platforms will definitely power various future autonomous machines. Due to the high complexity of such platforms, it is difficult to achieve timing predictability, reliability and efficient resource utilization at the same time. We believe that time-triggered scheduling in combination with PRedictable Execution Model (PREM) can provide strong safety guarantees, and our longerterm goal is to schedule execution on the whole MPSoC (CPUs and GPU) in time triggered manner. To extend PREM to GPUs, we compare two synchronization mechanisms available on the NVIDIA Tegra X2 platform: one based on pinned memory and another that uses a GPU timer (socalled globaltimer). We found that running the NVIDIA profiler (nvprof) reconfigures the resolution of the globaltimer from 1 µs to 160 ns. By using time-triggered scheduling with such a resolution,itwaspossibletoreduceexecutiontimejitterofatiled 2D convolution kernel from 6.47% to 0.15% while maintaining the same average execution time.