DyLDPC: A Dynamic LDPC Code with Variable Correction Capability to Improve Decoding Performance for 3D NAND Flash Memory

3D NAND flash memory is currently the mainstream storage medium due to high density and large capacity. However, the high raw bit error rate (RBER) poses challenges to data reliability. Low-density parity-check (LDPC) codes, known for strong error correction capabilities, are widely used to ensure data reliability. Traditional error correction schemes employ a single, fixed LDPC code, resulting in suboptimal performance—excess decoding overhead at low RBER and insufficient correction capability at high RBER. To address these limitations, we propose DyLDPC: a dynamic LDPC code with variable correction capability to improve decoding performance for 3D NAND flash memory. DyLDPC dynamically adjusts the error correction capability of LDPC codes based on the temporal and spatial variations of RBER in 3D NAND flash memory. Temporally, RBER increases with retention time and program/erase (P/E) cycles. Spatially, RBER varies across layers and pages. DyLDPC predicts RBER under varying conditions and allocates appropriate LDPC codes accordingly, effectively reducing ECC storage overhead, extending flash memory lifespan, and improving decoding efficiency. While ensuring data reliability, it optimizes error correction performance. Evaluations indicate that DyLDPC reduces decoding iterations by 8.1% and latency by 74% on average compared to static schemes. Additionally, using differentiated LDPC codes for most significant bit (MSB) and least significant bit (LSB) pages in multi-level cell (MLC) NAND further reduces LSB decoding latency by 27.8%.

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Publication Details

Journal
ACM Transactions on Design Automation of Electronic Systems
Published
2026-02-09
DOI
https://doi.org/10.1145/3796534
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
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article

DyLDPC: A Dynamic LDPC Code with Variable Correction Capability to Improve Decoding Performance for 3D NAND Flash Memory

Ryan Tu, Shaoqi Gao, Yangyi Li, Xianwei Meng et al.
ACM Transactions on Design Automation of Electronic Systems
Advanced Data Storage Technologies
article

DyLDPC: A Dynamic LDPC Code with Variable Correction Capability to Improve Decoding Performance for 3D NAND Flash Memory

Ryan Tu, Shaoqi Gao, Yangyi Li, Xianwei Meng, Lingyan Fan, Fei Wu, Changsheng Xie, Geyang Ren, Qiang Li, Meng Zhang
article en

Abstract

3D NAND flash memory is currently the mainstream storage medium due to high density and large capacity. However, the high raw bit error rate (RBER) poses challenges to data reliability. Low-density parity-check (LDPC) codes, known for strong error correction capabilities, are widely used to ensure data reliability. Traditional error correction schemes employ a single, fixed LDPC code, resulting in suboptimal performance—excess decoding overhead at low RBER and insufficient correction capability at high RBER. To address these limitations, we propose DyLDPC: a dynamic LDPC code with variable correction capability to improve decoding performance for 3D NAND flash memory. DyLDPC dynamically adjusts the error correction capability of LDPC codes based on the temporal and spatial variations of RBER in 3D NAND flash memory. Temporally, RBER increases with retention time and program/erase (P/E) cycles. Spatially, RBER varies across layers and pages. DyLDPC predicts RBER under varying conditions and allocates appropriate LDPC codes accordingly, effectively reducing ECC storage overhead, extending flash memory lifespan, and improving decoding efficiency. While ensuring data reliability, it optimizes error correction performance. Evaluations indicate that DyLDPC reduces decoding iterations by 8.1% and latency by 74% on average compared to static schemes. Additionally, using differentiated LDPC codes for most significant bit (MSB) and least significant bit (LSB) pages in multi-level cell (MLC) NAND further reduces LSB decoding latency by 27.8%.

ACM Transactions on Design Automation of Electronic Systems
Wuhan National Laboratory for Optoelectronics (CN), Inspur (China) (CN), Huazhong University of Science and Technology (CN), Hangzhou Dianzi University (CN)
Openalex Percentile: Top 67%
Advanced Data Storage Technologies
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