  To mitigate the ever worsening "Power wall" and "Memory wall" problems,
multi-core architectures with multilevel cache hierarchies have been widely
accepted in modern processors. However, the complexity of the architectures
makes modeling of shared caches extremely complex. In this paper, we propose a
data-sharing aware analytical model for estimating the miss rates of the
downstream shared cache under multi-core scenarios. Moreover, the proposed
model can also be integrated with upstream cache analytical models with the
consideration of multi-core private cache coherent effects. This integration
avoids time consuming full simulations of the cache architecture that required
by conventional approaches. We validate our analytical model against gem5
simulation results under 13 applications from PARSEC 2.1 benchmark suites.
Compared to the results from gem5 simulations under 8 hardware configurations
including dual-core and quad-core architectures, the average absolute error of
the predicted shared L2 cache miss rates is less than 2% for all
configurations. After integrated with the refined upstream model with coherence
misses, the overall average absolute error in 4 hardware configurations is
degraded to 8.03% due to the error accumulations. The proposed coherence model
can achieve similar accuracies of state of the art approach with only one tenth
time overhead. As an application case of the integrated model, we also evaluate
the miss rates of 57 different multi-core and multi-level cache configurations.
