An Analytical Performance Model for Partitioning Off-Chip Memory Bandwidth

With the emergence of multi-programmed workloads for Chip Multiprocessors (CMP), Quality of Service (QoS) of each co-scheduled application on the CMP is increasingly gaining importance. As more and more applications are consolidated into a single chip to compete for the limited off-chip memory bandwidth, off-chip memory bandwidth partitioning makes an increasing impact on system performance. Although various existing heuristic-based memory scheduling schemes have achieved significant system performance improvement by better partitioning the bandwidth, it is still not clear what are the best ways to partition off-chip bandwidth for improving different system performance objectives. The goal of this paper is to understand how off-chip memory bandwidth partitioning affects various system performance objectives. To achieve this goal, we propose an analytical model that is simple yet powerful enough to reveal the relationship between various memory bandwidth partitioning schemes and different system performance objectives. From our model, optimal memory bandwidth partitioning schemes for different system-level objectives are derived. Experimental results from a cycle-accurate full-system simulator show that, for heterogeneous workloads, performance improvements over No_partitioning/Equal_partitioning in terms of harmonic weighted speedup, minimum fairness, weighted speedup and sum of IPCs are 20.3%/2.1%, 49.8%/38.7%, 32.8%/7.6% and 64.2%/24%, on average, with our corresponding optimal partitioning schemes (i.e., Square_root, Proportional, Priority_APC, Priority_API), respectively.