Optimizing NAND flash-based SSDs via retention relaxation
FAST'12 Proceedings of the 10th USENIX conference on File and Storage Technologies
The optimized wavelet filters for speech compression
International Journal of Speech Technology
| Hi-index | 14.98 |
Lossless data compression for data storage has become less popular as mass data storage systems are becoming increasingly cheap. This leaves many files stored on mass data storage media uncompressed although they are losslessly compressible. This paper proposes to exploit the lossless compressibility of those files to improve the underlying storage system performance metrics such as energy efficiency and access speed, other than saving storage space as in conventional practice. The key idea is to apply runtime lossless data compression to enable an opportunistic use of a stronger error correction code (ECC) with more coding redundancy in data storage systems, and trade such opportunistic extra error correction capability to improve other system performance metrics in the runtime. Since data storage is typically realized in the unit of equal-sized sectors (e.g., 512 B or 4 KB user data per sector), we only apply this strategy to each individual sector independently in order to be completely transparent to the firmware, operating systems, and users. Using low-density parity check (LDPC) code as ECC in storage systems, this paper quantitatively studies the effectiveness of this design strategy in both hard disk drives and NAND flash memories. For hard disk drives, we use this design strategy to reduce average hard disk drive read channel signal processing energy consumption, and results show that up to 38 percent read channel energy saving can be achieved. For NAND flash memories, we use this design strategy to improve average NAND flash memory write speed, and results show that up to 36 percent write speed improvement can be achieved for 2 bits/cell NAND flash memories.