CompEx: Compression-expansion coding for energy, latency, and lifetime improvements in MLC/TLC NVM

Multi-level/triple-level cell non-volatile memories (MLC/TLC NVMs) such as PCM and RRAM are the subject of active research and development as replacement candidates for DRAM, which is limited by its high refresh power and poor scaling potential. Besides the benefits of non-volatility (low refresh power) and improved scalability, MLC/TLC NVMs offer high data density and memory capacity over DRAM. However, the viability of MLC/TLC NVMs is limited primarily due to the high programming energy and latency as well as the low endurance of NVM cells; these are primarily attributable to the iterative program-and-verify procedure necessary for programming the NVM cells. In this paper, we propose compression-expansion (CompEx) coding, a low overhead scheme that synergistically integrates statistical compression with expansion coding to realize simultaneous energy, latency, and lifetime improvements in MLC/TLC NVMs. CompEx coding is agnostic to the choice of compression technique; in this paper, we evaluate CompEx coding using both frequent pattern compression (FPC) and base-delta-immediate (BΔI) compression. CompEx coding integrates FPC/BΔI with (k, m)q `expansion' coding; expansion codes are a class of q-ary linear block codes that encode data using only the low energy states of a q-ary NVM cell. CompEx coding simultaneously reduces energy and latency and improves lifetime for no memory overhead and negligible logic overhead (≈ 10k gates, which is <; 0.1% per NVM module). Our full-system simulations of a system that integrates TLC RRAM show that CompEx coding reduces total memory energy by 53% and write latency by 24%; these improvements translate to a 5.7% improvement in IPC, a 11.8% improvement in main memory bandwidth, and 1.8× improvement in lifetime over classical binary coding using data-comparison write. CompEx coding thus addresses the programming energy/latency and lifetime challenges of MLC/-TLC NVMs that pose a serious technological roadblock to their adoption in high performance computing systems.