In the age of high-performance computing, multi-core technology is seen to bridge the gap between good system throughput and increased power dissipation. Most multi-core architectures share hardware resources between cores, leading to cross-core interference which is non-trivial in many cases. Effective shared resource management is necessary to minimise the performance variability of threads due to cross-core interference as well as optimise resource usage. Many biological models have been proposed which model interactions between species. This paper uses a mathematical model, on the lines of the competitive Lotka-Volterra model for biological population growth, which models performance of the cores in a shared-memory multi-core system. It further formulates stability conditions for the multi-core system taking into account the workload characteristics and derives partition sizes to partition the shared cache to reduce the effect of cross-core interference for different workload types. Analysis of scalability of the model is also presented. Performance evaluations reveal that the LV-based mathematical model can be used to study the effects of resource sharing between cores, calculate partition sizes and is scalable.
['Sapna U. Prabhu', 'R. D. Daruwala']
Shared resource management in multi-core systems using LV competition model