18,744 research outputs found

    A survey of data recovery on flash memory

    Get PDF
    In recent years, flash memory has become more widely used due to its advantages, such as fast data access, low power consumption, and high mobility. However, flash memory also has drawbacks that need to be overcome, such as erase-before-write, and the limitations of block deletion. In order to address this issue, the FTL (Flash Translation Layer) has been proposed with useful functionalities like address mapping, garbage collection, and wear-leveling. During the process of using, the data may be lost on power failure in the storage systems. In some systems, the data is very important. Thus recovery of data in the event of the system crash or a sudden power outage is of prime importance. This problem has attracted attention from researchers and many studies have been done. In this paper, we investigate previous studies on data recovery for flash memory from FTL processing solutions to PLR (Power Loss Recovery) solutions that have been proposed by authors in the conference proceeding, patents, or professional journals. This will provide a discussion of the proposed solutions to the data recovery in flash memory as well as an overview

    Improving the Performance and Endurance of Persistent Memory with Loose-Ordering Consistency

    Full text link
    Persistent memory provides high-performance data persistence at main memory. Memory writes need to be performed in strict order to satisfy storage consistency requirements and enable correct recovery from system crashes. Unfortunately, adhering to such a strict order significantly degrades system performance and persistent memory endurance. This paper introduces a new mechanism, Loose-Ordering Consistency (LOC), that satisfies the ordering requirements at significantly lower performance and endurance loss. LOC consists of two key techniques. First, Eager Commit eliminates the need to perform a persistent commit record write within a transaction. We do so by ensuring that we can determine the status of all committed transactions during recovery by storing necessary metadata information statically with blocks of data written to memory. Second, Speculative Persistence relaxes the write ordering between transactions by allowing writes to be speculatively written to persistent memory. A speculative write is made visible to software only after its associated transaction commits. To enable this, our mechanism supports the tracking of committed transaction ID and multi-versioning in the CPU cache. Our evaluations show that LOC reduces the average performance overhead of memory persistence from 66.9% to 34.9% and the memory write traffic overhead from 17.1% to 3.4% on a variety of workloads.Comment: This paper has been accepted by IEEE Transactions on Parallel and Distributed System
    • …
    corecore