A Joint Source/Channel Approach to Strengthen Embedded Programmable Devices against Flash Memory Errors

Abstract

Reconfigurable embedded systems can take advantage of programmable devices, such as microprocessors and field-programmable gate arrays (FPGAs), to achieve high performance and flexibility. Support to flexibility often comes at the expense of large amounts of nonvolatile memories. Unfortunately, nonvolatile memories, such as multilevel-cell (MLC) NAND flash, exhibit a high raw bit error rate that is mitigated by employing different techniques, including error correcting codes. Recent results show that low-density-parity-check (LDPC) codes are good candidates to improve the reliability of MLC NAND flash memories especially when page size increases. This letter proposes to use a joint source/channel approach, based on a modified arithmetic code and LDPC codes, to achieve both data compression and improved system reliability. The proposed technique is then applied to the configuration data of FPGAs and experimental results show the superior performance of the proposed system with respect to state of the art. Indeed, the proposed system can achieve bit-error-rates as low as about for cell-to-cell coupling strength factors well higher than 1.0.

Efficient VLSI architecture for the parallel dictionary LZW data compression algorithm

“…Universal data compression for flash memory systems has recently gained interest [1][2][3][4][5][6][7][8][9] because data compression can improve the storage capacity and the flash memory lifetime. Compression of redundant data reduces the amount of data transferred from the host to the flash system.…”

“…In particular, we propose a technique to adjust the partitioning to the data model. We focus on address spaces with 512, 1024, and 2048 entries, which are suitable for compression in current flash storage systems [1, 3, 9]. Numerical results demonstrate that the proposed partitioning improves the performance of the PDLZW compared with the original proposal.…”

Pipelined decoder for the limited context order Burrows–Wheeler transformation

“…Data compression is an important component of many storage and communication systems. For instance, in flash memory systems data compression can improve the storage capacity and the flash memory lifetime [1][2][3][4][5][6][7][8][9]. Data compression can reduce the amount of data transferred from the host system.…”