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2017 IEEE International Conference on Computer Design (ICCD) (2017)
Boston, MA, USA
Nov. 5, 2017 to Nov. 8, 2017
ISSN: 1063-6404
ISBN: 978-1-5386-2254-4
pp: 573-580
Resistive Random Access Memory (RRAM) technology is proposed as a promising replacement candidate for DRAM-based main memory due to its good scalability, low standby power, and non-volatility. The structure of Triple-Level Cell (TLC) can offer higher data density over Single-Level Cell (SLC). However, TLC RRAM suffers from high write energy and latency. Data compression techniques can reduce the size of the data to store. In contrast, data encoding methods such as Incomplete Data Mapping (IDM) can 'expand' the size for latency and energy reduction. We observe that the compression ratio of each cacheline varies, and therefore the saved space of each compressed cacheline is different. On the other hand, we find that different IDMs have different tradeoffs in capacity and write latency/energy. To fully exploit the space saved by compression for reducing the write latency/energy, and improving the performance of TLC RRAM-based main memory system, Compression-Ratio-Aware Data Encoding (CRADE) is proposed. The key idea of CRADE is to dynamically select the best-performing IDM according to the compression ratio of each cacheline. The cacheline is compressed first, and then the compressed cacheline is encoded by IDM. For each compressed cacheline, the IDM which uses the fewest states to encode is applied on the condition that the encoded data size will not exceed the cacheline size. Experimental results show that CRADE can reduce the write energy by 15%, decrease the write latency by 19%, reduce the read latency by 4%, and improve the IPC performance by 2% compared with the state-of-the-art scheme.
cache storage, data compression, DRAM chips, encoding, flash memories, power aware computing

J. Xu et al., "Improving Performance of TLC RRAM with Compression-Ratio-Aware Data Encoding," 2017 IEEE 35th International Conference on Computer Design (ICCD), Boston, MA, USA, 2018, pp. 573-580.
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