Parallel Shared-Memory Workloads Performance on Asymmetric Multi-core Architectures

Putting performance asymmetric cores inside the same processor can be a good alternative to obtain high performance per area, throughput and single-threaded performance. However, the impact of running parallel applications on this type of machine is not clear, since most of previous work focused on multi-programmed and server workloads where there is low or no dependence between threads. In this work, we analyze the impact of running parallel shared-memory programs on heterogeneous multi-core setups using six parallel applications with diverse parallelization schemes. Moreover, we show that, in some cases, with a high number of cores, it is better to put one complex core than several simple ones. The impact of sharing the address space between asymmetric cores with private caches was also investigated and the number of invalidations per write access was not greater than a comparable homogeneous configuration.