Evaluation of the parallel computational capabilities of embedded platforms for critical systems

Abstract

Modern critical systems need higher performance which cannot be delivered by the simple architectures used so far. Latest embedded architectures feature multi-cores and GPUs, which can be used to satisfy this need. In this thesis we parallelise relevant applications from multiple critical domains represented in the GPU4S benchmark suite, and perform a comparison of the parallel capabilities of candidate platforms for use in critical systems. In particular, we port the open source GPU4S Bench benchmarking suite in the OpenMP programming model, and we benchmark the candidate embedded heterogeneous multi-core platforms of the H2020 UP2DATE project, NVIDIA TX2, NVIDIA Xavier and Xilinx Zynq Ultrascale+, in order to drive the selection of the research platform which will be used in the next phases of the project. Our result indicate that in terms of CPU and GPU performance, the NVIDIA Xavier is the highest performing platform