Non-volatile memory technologies (NVMs) are promising candidates as the next-generation main memory due to high scalability and low energy consumption. However, the performance bottlenecks, such as high write latency and low cell endurance, still exist in NVMs. To address these problems, frequent pattern compression schemes have been widely used, which however suffer from the lack of flexibility and adaptability. In order to overcome these shortcomings, we propose a well-adaptive NVM write scheme, called Dynamic Frequent Pattern Compression (DFPC), to significantly reduce the amount of write units and extend the lifetime. Instead of only using static frequent patterns in existing FPC schemes, which are pre-defined and not always efficient for all applications, the idea behind DFPC is to exploit the characteristics of data distribution in execution to obtain dynamic patterns, which often appear in the real-world applications. To further improve the compression ratio, we exploit the value locality in a cache line to extend the granularity of dynamic patterns. Hence DFPC can encode the contents of cache lines with more kinds of frequent data patterns. We implement DFPC in GEM5 with NVMain and execute 8 applications from SPEC CPU2006 to evaluate our scheme. Experimental results demonstrate the efficacy and efficiency of DFPC.
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