NOVELLA: Nonvolatile Last-Level Cache Bypass for Optimizing Off-Chip Memory Energy

Abstract

Contemporary multiprocessor systems-on-chips (MPSoCs) continue to confront energy-related challenges, primarily originating from off-chip data movements. Nonvolatile memories (NVMs) emerge as a promising solution with their high-storage density and low leakage, yet they suffer from slow and expensive write operations. Writebacks from higher-level caches and responses from off-chip memory create significant contention at the shared nonvolatile last-level cache (LLC), affecting system performance with increased queuing for critical reads. Previous research primarily addresses the performance issues by trying to mitigate contention through the bypassing of NVM writes. Nevertheless, off-chip memory energy, one of the most critical components of system energy, remains unaddressed by state-of-the-art bypass policies. While certain energy components, such as leakage and refresh, depend on system performance, performance-optimizing bypass policies may not ensure energy efficiency. Aggressive bypass decisions aimed only at performance enhancement could degrade cache reuse, potentially outweighing reductions in leakage and refresh energies with the increase in off-chip dynamic energy. While both performance and off-chip memory energy are influenced by both cache contention and reuse, the tradeoffs for achieving optimal performance versus optimal energy are different. We introduce nonvolatile last-level cache bypass for optimizing off-chip memory energy (NOVELLA), a novel bypass policy for the nonvolatile LLC, to optimize off-chip memory energy by exploiting tradeoffs between cache contention and reuse, achieving a balance across different components of the energy. Compared to a naïve no-bypass baseline, while state-of-the-art reuse-aware bypass solutions reduce off-chip memory energy consumption by up to 8%, and a contention- and reuse-aware bypass baseline by 12%, NOVELLA achieves significant energy savings of 21% across diverse SPEC workloads.