How to address certification for multi-core based IMA platforms: Current status and potential solutions

In modern aircrafts, more and more functions traditionally implemented as Line Replaceable Units (LRUs) will be hosted by Integrated Modular Avionics (IMA) modules. At the same time new aircraft programs will require new safety functions, information services and comfort features which will also increase the demand for processing performance of IMA modules. The traditional approach to provide more processing bandwidth was to increase the CPU clock frequency, increase pseudo-parallel processing on instruction level through instruction pipelines and speculative program executions and to increase the cache size and number of cache levels. With today\´s technology, this approach has reached its limit. Increasing CPU frequency causes disproportionate power consumption and thermal dissipation loss and raises more and more problems due to chip internal and external crosstalk, signal delays and reflection. Existing parallelism and dependencies on code level prevent further performance improvement through parallel execution on instruction level. To further increase processor performance, the chip industry has switched to a multi-core design for the high performance processors. The development of multi-core based high performance IMA platforms will be a necessary step to reach a larger scale integration on function level. The question is, "Can a multi-core based platform reach the same level of determinism as a single core platform and can this be demonstrated?" This paper addresses certification aspects of multi-core based IMA platforms with the focus on today\´s technologies and processes. The paper provides an analysis of potential hardware and software related interference channels between partitions running on a multi-core based platform. Different core software concepts found in existing implementations like asymmetric multi processing (AMP) and symmetric multi processing (SMP) concepts are evaluated with respect to partitioning aspects.