Future flash-based solid-state drives (SSDs) must employ increasingly powerful error correction code (ECC) and digital signal processing (DSP) techniques to compensate the negative impact of technology scaling on NAND flash memory device reliability. Currently, all the ECC and DSP functions are implemented in a central SSD controller. However, the use of more powerful ECC and DSP makes such design practice subject to significant speed performance degradation and complicated controller implementation. An EZ-NAND (Error Zero NAND) flash memory design strategy is emerging in the industry, which moves all the ECC and DSP functions to each memory chip. Although EZ-NAND flash can simplify controller design and achieve high system speed performance, its high silicon cost may not be affordable for large-capacity SSDs in computing systems. We propose a quasi-EZ-NAND design strategy that hierarchically distributes ECC and DSP functions on both NAND flash memory chips and the central SSD controller. Compared with EZ-NAND design concept, it can maintain almost the same speed performance while reducing silicon cost overhead. Assuming the use of low-density parity-check (LDPC) code and postcompensation DSP technique, trace-based simulations show that SSDs using quasi-EZ-NAND flash can realize almost the same speed as SSDs using EZ-NAND flash, and both can reduce the average SSD response time by over 90 percent compared with conventional design practice. Silicon design at 65 nm node shows that quasi-EZ-NAND can reduce the silicon cost overhead by up to 44 percent compared with EZ-NAND.

This article presents a cross-layer codesign approach to reduce SSD read response latency. The key is to cohesively exploit the NAND flash memory device write speed vs. raw storage reliability trade-off at the physical layer and runtime data access workload dynamics at the system level. Leveraging runtime data access workload variation, we can opportunistically slow down NAND flash memory write speed and hence improve NAND flash memory raw storage reliability. This naturally enables an opportunistic use of weaker error correction schemes that can directly reduce SSD read access latency. We develop a disk-level scheduling scheme to effectively smooth the write workload in order to maximize the occurrence of runtime opportunistic NAND flash memory write slowdown. Using 2 bits/cell NAND flash memory with BCH-based error correction correction as a test vehicle, we carry out extensive simulations over various workloads and demonstrate that this developed cross-layer co-design solution can reduce the average SSD read latency by up to 59.4% without sacrificing the write throughput performance.

Today and future NAND flash memory will heavily rely on system-level fault-tolerance techniques such as error correction code (ECC) to ensure the overall system storage integrity. Since ECC demands the storage of coding redundancy and hence degrades effective cell storage efficiency, it is highly desirable to use more powerful coding solutions that can maintain the system storage reliability at less coding redundancy. This has motivated a growing interest in the industry to search for alternatives to BCH code being used in today. Regardless to specific ECCs, it is of great practical importance to know the theoretical limit on the achievable cell storage efficiency, which motivates this work. We first develop an approximate NAND flash memory channel model that explicitly incorporates program/erase (P/E) cycling effects and cell-to-cell interference, based on which we then develop strategies for estimating the information-theoretical bounds on cell storage efficiency. We show that it can readily reveal the tradeoffs among cell storage efficiency, P/E cycling endurance, and retention limit, which can provide important insights for system designers. Finally, motivated by the dynamics of P/E cycling effect revealed by the information-theoretical study, we propose two memory system design techniques that can improve the average NAND flash memory programming speed and increase the total amount of user data that can be stored in NAND flash cell over its entire lifetime.

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.

This paper presents a cross-layer co-design approach to reduce SSD read response latency. The key is to cohesively exploit the NAND flash memory device write speed vs. raw storage reliability trade-off at the physical layer and run-time data access workload variation at the system level. Leveraging run-time data access workload variation, we can opportunistically slow down NAND flash memory write speed and hence improve NAND flash memory raw storage reliability. This naturally enables an opportunistic use of weaker error correction schemes that can directly reduce SSD read access latency. We develop a disk-level scheduling scheme to effectively smooth the write workload in order to maximize the occurrence of run-time opportunistic NAND flash memory write slow down. Using 2 bits/cell NAND flash memory with BCH-based error correction correction as a test vehicle, we carry out extensive simulations over various workloads and demonstrate that this developed cross-layer co-design solution can reduce the average SSD read latency by up to 96%.

A novel hard-decision decoding algorithm for low-density parity-check (LDPC) codes is proposed in this paper. This algorithm employs the correlation information among the column vectors of the parity-check matrix and syndrome vector for decoding. It does not require soft information, and has low decoding complexity. Simulation results show that the proposed decoding algorithm could provide an effective tradeoff between error performance and decoding complexity.