Safe and Efficient Deployment of Data-Parallelisable Applications on Many-Core Platforms: Theory and Practice

The safe and, at the same time, efficient deployment of parallelisable applications on many-core platforms is a challenging task. Theoretical Models of Computation (MoC) require the realistic estimation of task Worst-Case Execution Time (WCET) to provide safe latency guarantees. Due to interferences on shared resources, task WCET estimations are often exceedingly pessimistic. In reality, though, rarely do all the tasks execute with their WCET, thus introducing an efficiency gap, which is of consequence in realizing safety-critical and mixed-criticality systems. In this paper, we outline the additional research efforts required to i) derive a safe deployment from a MoC reducing that efficiency gap and ii) adapt at runtime to further improve performance and still preserve safety. We also outline the impact of the level of data-parallelisation onto this efficiency gap and present experimental evidence of the performance improvements from accurate WCET estimation, level of data-parallelisation and runtime adaptation.