SPaC: a segment-based parallel compression for backup acceleration in nonvolatile processors

Xiao Sheng, Yiqun Wang, Yongpan Liu, Huazhong Yang

Abstract: Nonvolatile processor (NVP) has become an emerging topic in recent years. The conventional NV processor equips each flip-flop with a nonvolatile storage for data backup, which results in much faster backup speed with significant area overheads. A compression based architecture (PRLC) solved the area problem but with a nontrivial increasing on backup time. This paper provides a segment-based parallel compression (SPaC) architecture to achieve tradeoffs between area and backup speed. Furthermore, we use an off-line and online hybrid method to balance the workloads of different compression modules in SPaC. Experimental results show that SPaC can achieve 76% speed up against PRLC and meanwhile reduces the area by 16% against conventional NV processors.