GroupUCP: An On-Demand Fine-Grained Cache Dynamic Partition Strategy

With the advancement of modern computer technology, the memory wall problem is getting more and more severe. Under this background, the last-level cache in multi-level memory hierarchy becomes a key resource affecting system performance. In recent years various researches have optimized the last-level cache by means of size expansion, and dynamic resource management. Way-partitioning technique is the main method of cache resource management, which optimizes system performance by partitioning the cache into ways and allocating them to each application. However, it is coarse-grained and requires all sets of caches to follow the same way partitioning strategy. In fact, applications may have different space demand on different sets, and the way-partitioning technique restricts the space utilization of the cache, resulting in a waste of cache resources. In this paper, we propose an on-demand fine-grained cache resource management technique, GroupUCP, whose design idea is to aggregate individual cache sets into groups based on the different space demand of each application on each set, using dynamic grouping and real-time evaluation. Each group can be allocated space on demand independently, thus improving cache utilization and overall system performance. Experiments demonstrate that GroupUCP achieves finer-grained on-demand resource allocation using less hardware resources than the traditional UCP approach and achieves higher system performance improvement in cache-sensitive application combinations which shows imbalance space demand of cache.