Towards Practical Page Coloring-based Multi-core Cache Management Xiao Zhang, Sandhya Dwarkadas, and Kai Shen Department of Computer Science, University of Rochester Modern multi-core processors present new resource management challenges due to the subtle interactions of simultaneously executing processes sharing on-chip resources (particularly the L2 cache). Recent research demonstrates that the operating system may use the page coloring mechanism to control cache partitioning, and consequently to achieve fair and efficient cache utilization. However, page coloring places additional constraints on memory space allocation, which may conflict with application memory needs. Further, adaptive adjustments of cache partitioning policies in a multi-programmed execution environment may incur substantial overhead for page recoloring (or copying). This paper proposes a hot-page coloring approach---enforcing coloring on only a small set of frequently accessed (or hot) pages for each process. The cost of identifying hot pages online is reduced by leveraging the knowledge of spatial locality during a page table scan of access bits. Our results demonstrate that hot page identification and selective coloring can significantly alleviate the coloring-induced adverse effects in practice. However, we also reach the somewhat negative conclusion that without additional hardware support, adaptive page coloring is only beneficial when recoloring is performed infrequently (meaning long scheduling time quanta in multi-programmed executions).