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Simultaneous multithreading processors improve throughput oversingle-threaded processors thanks to sharing internal core resources amonginstructions from distinct threads. However, resource sharing introducesinter-thread interference within the core, which has a negative impact onindividual application performance and can significantly increase theturnaround time of multi-program workloads. The severity of the interferenceeffects depends on the competing co-runners sharing the core. Thus, it can bemitigated by applying a thread-to-core allocation policy that smartly selectsapplications to be run in the same core to minimize their interference.  This paper presents SYNPA, a simple approach that dynamically allocatesthreads to cores in an SMT processor based on their run-time dynamic behavior.The approach uses a regression model to select synergistic pairs to mitigateintra-core interference. The main novelty of SYNPA is that it uses just threevariables collected from the performance counters available in current ARMprocessors at the dispatch stage. Experimental results show that SYNPAoutperforms the default Linux scheduler by around 36%, on average, in terms ofturnaround time in 8-application workloads combining frontend bound and backendbound benchmarks.

SYNPA: SMT Performance Analysis and Allocation of Threads to Cores in ARM Processors