Improving LDPC performance via asymmetric sensing level placement on flash memory

Flash memory development through technology scaling and bit density has significant impact on the reliability of flash cells. Hence strong error correction code (ECC) schemes are highly recommended. With a strong error correction capability, low-density-parity code (LDPC) is now applied for the state-of-the-art flash memory. However, LDPC has long decoding latency when the raw bit error rates (RBER) are high. This is because it needs finegrained soft sensing between states to iteratively decode the raw data. In this work, we propose a smart sensing level placement scheme to reduce the LDPC decoding latency. The basic idea for the placement scheme is motivated by two asymmetric error characteristics of flash memory: the asymmetric errors at different states, and the asymmetric errors caused by voltage left-shifts and right-shifts. With understanding of these two types of error characteristics, the sensing levels are smartly placed to achieve reduced sensing levels while maintaining the error correction capability of LDPC. Experiment analysis shows that the proposed scheme achieves significant performance improvement.

[1]  Nanning Zheng,et al.  LDPC-in-SSD: making advanced error correction codes work effectively in solid state drives , 2013, FAST.

[2]  Qiao Li,et al.  Access Characteristic Guided Read and Write Cost Regulation for Performance Improvement on Flash Memory , 2016, FAST.

[3]  Gregory R. Ganger,et al.  The DiskSim Simulation Environment Version 4.0 Reference Manual (CMU-PDL-08-101) , 1998 .

[4]  Tong Zhang,et al.  On the Use of Soft-Decision Error-Correction Codes in nand Flash Memory , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[5]  Hsie-Chia Chang,et al.  A 45nm 6b/cell charge-trapping flash memory using LDPC-based ECC and drift-immune soft-sensing engine , 2013, 2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers.

[6]  Wei Wu,et al.  Optimizing NAND flash-based SSDs via retention relaxation , 2012, FAST.

[7]  Onur Mutlu,et al.  Error patterns in MLC NAND flash memory: Measurement, characterization, and analysis , 2012, 2012 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[8]  Tong Zhang,et al.  Quasi-nonvolatile SSD: Trading flash memory nonvolatility to improve storage system performance for enterprise applications , 2012, IEEE International Symposium on High-Performance Comp Architecture.

[9]  Fei Wu,et al.  REAL: A retention error aware LDPC decoding scheme to improve NAND flash read performance , 2016, 2016 32nd Symposium on Mass Storage Systems and Technologies (MSST).

[10]  Edwin Hsing-Mean Sha,et al.  Exploit asymmetric error rates of cell states to improve the performance of flash memory storage systems , 2014, 2014 IEEE 32nd International Conference on Computer Design (ICCD).

[11]  Zili Shao,et al.  An Endurance-Aware Metadata Allocation Strategy for MLC NAND Flash Memory Storage Systems , 2016, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[12]  Tong Zhang,et al.  Using Lossless Data Compression in Data Storage Systems: Not for Saving Space , 2011, IEEE Transactions on Computers.

[13]  Onur Mutlu,et al.  Data retention in MLC NAND flash memory: Characterization, optimization, and recovery , 2015, 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA).

[14]  Yiran Chen,et al.  FlexLevel: A novel NAND flash storage system design for LDPC latency reduction , 2015, 2015 52nd ACM/EDAC/IEEE Design Automation Conference (DAC).

[15]  Tong Zhang,et al.  Enabling NAND Flash Memory Use Soft-Decision Error Correction Codes at Minimal Read Latency Overhead , 2013, IEEE Transactions on Circuits and Systems I: Regular Papers.

[16]  Antony I. T. Rowstron,et al.  Migrating server storage to SSDs: analysis of tradeoffs , 2009, EuroSys '09.