Towards Design and Analysis For High-Performance and Reliable SSDs

NAND Flash-based Solid State Disks have many attractive technical merits, such as low power consumption, light weight, shock resistance, sustainability of hotter operation regimes, and extraordinarily high performance for random read access, which makes SSDs immensely popular and be widely employed in different types of environments including portable devices, personal computers, large data centers, and distributed data systems. However, current SSDs still suffer from several critical inherent limitations, such as the inability of in-place-update, asymmetric read and write performance, slow garbage collection processes, limited endurance, and degraded write performance with the adoption of MLC and TLC techniques. To alleviate these limitations, we propose optimizations from both specific outside applications layer and SSDs\u27 internal layer. Since SSDs are good compromise between the performance and price, so SSDs are widely deployed as second layer caches sitting between DRAMs and hard disks to boost the system performance. Due to the special properties of SSDs such as the internal garbage collection processes and limited lifetime, traditional cache devices like DRAM and SRAM based optimizations might not work consistently for SSD-based cache. Therefore, for the outside applications layer, our work focus on integrating the special properties of SSDs into the optimizations of SSD caches. Moreover, our work also involves the alleviation of the increased Flash write latency and ECC complexity due to the adoption of MLC and TLC technologies by analyzing the real work workloads

Flashing up the storage hierarchy

The focus of this thesis is on systems that employ both flash and magnetic disks as storage media. Considering the widely disparate I/O costs of flash disks currently on the market, our approach is a cost-aware one: we explore techniques that exploit the I/O costs of the underlying storage devices to improve I/O performance. We also study the asymmetric I/O properties of magnetic and flash disks and propose algorithms that take advantage of this asymmetry. Our work is geared towards database systems; however, most of the ideas presented in this thesis can be generalised to any data-intensive application. For the case of low-end, inexpensive flash devices with large capacities, we propose using them at the same level of the memory hierarchy as magnetic disks. In such setups, we study the problem of data placement, that is, on which type of storage medium each data page should be stored. We present a family of online algorithms that can be used to dynamically decide the optimal placement of each page. Our algorithms adapt to changing workloads for maximum I/O efficiency. We found that substantial performance benefits can be gained with such a design, especially for queries touching large sets of pages with read-intensive workloads. Moving one level higher in the storage hierarchy, we study the problem of buffer allocation in databases that store data across multiple storage devices. We present our novel approach to per-device memory allocation, under which both the I/O costs of the storage devices and the cache behaviour of the data stored on each medium determine the size of the main memory buffers that will be allocated to each device. Towards informed decisions, we found that the ability to predict the cache behaviour of devices under various cache sizes is of paramount importance. In light of this, we study the problem of efficiently tracking the hit ratio curve for each device and introduce a lowoverhead technique that provides high accuracy. The price and performance characteristics of high-end flash disks make them perfectly suitable for use as caches between the main memory and the magnetic disk(s) of a storage system. In this context, we primarily focus on the problem of deciding which data should be placed in the flash cache of a system: how the data flows from one level of the memory hierarchy to the others is crucial for the performance of such a system. Considering such decisions, we found that the I/O costs of the flash cache play a major role. We also study several implementation issues such as the optimal size of flash pages and the properties of the page directory of a flash cache. Finally, we explore sorting in external memory using external merge-sort, as the latter employs access patterns that can take full advantage of the I/O characteristics of flash memory. We study the problem of sorting hierarchical data, as such is necessary for a wide variety of applications including archiving scientific data and dealing with large XML datasets. The proposed algorithm efficiently exploits the hierarchical structure in order to minimize the number of disk accesses and optimise the utilization of available memory. Our proposals are not specific to sorting over flash memory: the presented techniques are highly efficient over magnetic disks as well

Letter from the Special Issue Editor

Editorial work for DEBULL on a special issue on data management on Storage Class Memory (SCM) technologies

Redesigning Transaction Processing Systems for Non-Volatile Memory

Department of Computer Science and EngineeringTransaction Processing Systems are widely used because they make the user be able to manage their data more efficiently. However, they suffer performance bottleneck due to the redundant I/O for guaranteeing data consistency. In addition to the redundant I/O, slow storage device makes the performance more degraded. Leveraging non-volatile memory is one of the promising solutions the performance bottleneck in Transaction Processing Systems. However, since the I/O granularity of legacy storage devices and non-volatile memory is not equal, traditional Transaction Processing System cannot fully exploit the performance of persistent memory. The goal of this dissertation is to fully exploit non-volatile memory for improving the performance of Transaction Processing Systems. Write amplification between Transaction Processing System is pointed out as a performance bottleneck. As first approach, we redesigned Transaction Processing Systems to minimize the redundant I/O between the Transaction Processing Systems. We present LS-MVBT that integrates recovery information into the main database file to remove temporary files for recovery. The LS-MVBT also employs five optimizations to reduce the write traffics in single fsync() calls. We also exploit the persistent memory to reduce the performance bottleneck from slow storage devices. However, since the traditional recovery method is for slow storage devices, we develop byte-addressable differential logging, user-level heap manager, and transaction-aware persistence to fully exploit the persistent memory. To minimize the redundant I/O for guarantee data consistency, we present the failure-atomic slotted paging with persistent buffer cache. Redesigning indexing structure is the second approach to exploit the non-volatile memory fully. Since the B+-tree is originally designed for block granularity, It generates excessive I/O traffics in persistent memory. To mitigate this traffic, we develop cache line friendly B+-tree which aligns its node size to cache line size. It can minimize the write traffic. Moreover, with hardware transactional memory, it can update its single node atomically without any additional redundant I/O for guaranteeing data consistency. It can also adapt Failure-Atomic Shift and Failure-Atomic In-place Rebalancing to eliminate unnecessary I/O. Furthermore, We improved the persistent memory manager that exploit traditional memory heap structure with free-list instead of segregated lists for small memory allocations to minimize the memory allocation overhead. Our performance evaluation shows that our improved version that consider I/O granularity of non-volatile memory can efficiently reduce the redundant I/O traffic and improve the performance by large of a margin.ope