Performance Analysis of NAND Flash Memory Solid-State Disks

As their prices decline, their storage capacities increase, and their endurance improves, NAND Flash Solid-State Disks (SSD) provide an increasingly attractive alternative to Hard Disk Drives (HDD) for portable computing systems and PCs. HDDs have been an integral component of computing systems for several decades as long-term, non-volatile storage in memory hierarchy. Today's typical hard disk drive is a highly complex electro-mechanical system which is a result of decades of research, development, and fine-tuned engineering. Compared to HDD, flash memory provides a simpler interface, one without the complexities of mechanical parts. On the other hand, today's typical solid-state disk drive is still a complex storage system with its own peculiarities and system problems. Due to lack of publicly available SSD models, we have developed our NAND flash SSD models and integrated them into DiskSim, which is extensively used in academe in studying storage system architectures. With our flash memory simulator, we model various solid-state disk architectures for a typical portable computing environment, quantify their performance under real user PC workloads and explore potential for further improvements. We find the following: * The real limitation to NAND flash memory performance is not its low per-device bandwidth but its internal core interface. * NAND flash memory media transfer rates do not need to scale up to those of HDDs for good performance. * SSD organizations that exploit concurrency at both the system and device level improve performance significantly. * These system- and device-level concurrency mechanisms are, to a significant degree, orthogonal: that is, the performance increase due to one does not come at the expense of the other, as each exploits a different facet of concurrency exhibited within the PC workload. * SSD performance can be further improved by implementing flash-oriented queuing algorithms, access reordering, and bus ordering algorithms which exploit the flash memory interface and its timing differences between read and write requests

Energy Saving Techniques for Phase Change Memory (PCM)

In recent years, the energy consumption of computing systems has increased and a large fraction of this energy is consumed in main memory. Towards this, researchers have proposed use of non-volatile memory, such as phase change memory (PCM), which has low read latency and power; and nearly zero leakage power. However, the write latency and power of PCM are very high and this, along with limited write endurance of PCM present significant challenges in enabling wide-spread adoption of PCM. To address this, several architecture-level techniques have been proposed. In this report, we review several techniques to manage power consumption of PCM. We also classify these techniques based on their characteristics to provide insights into them. The aim of this work is encourage researchers to propose even better techniques for improving energy efficiency of PCM based main memory.Comment: Survey, phase change RAM (PCRAM

HEC: Collaborative Research: SAM^2 Toolkit: Scalable and Adaptive Metadata Management for High-End Computing

The increasing demand for Exa-byte-scale storage capacity by high end computing applications requires a higher level of scalability and dependability than that provided by current file and storage systems. The proposal deals with file systems research for metadata management of scalable cluster-based parallel and distributed file storage systems in the HEC environment. It aims to develop a scalable and adaptive metadata management (SAM2) toolkit to extend features of and fully leverage the peak performance promised by state-of-the-art cluster-based parallel and distributed file storage systems used by the high performance computing community. There is a large body of research on data movement and management scaling, however, the need to scale up the attributes of cluster-based file systems and I/O, that is, metadata, has been underestimated. An understanding of the characteristics of metadata traffic, and an application of proper load-balancing, caching, prefetching and grouping mechanisms to perform metadata management correspondingly, will lead to a high scalability. It is anticipated that by appropriately plugging the scalable and adaptive metadata management components into the state-of-the-art cluster-based parallel and distributed file storage systems one could potentially increase the performance of applications and file systems, and help translate the promise and potential of high peak performance of such systems to real application performance improvements. The project involves the following components: 1. Develop multi-variable forecasting models to analyze and predict file metadata access patterns. 2. Develop scalable and adaptive file name mapping schemes using the duplicative Bloom filter array technique to enforce load balance and increase scalability 3. Develop decentralized, locality-aware metadata grouping schemes to facilitate the bulk metadata operations such as prefetching. 4. Develop an adaptive cache coherence protocol using a distributed shared object model for client-side and server-side metadata caching. 5. Prototype the SAM2 components into the state-of-the-art parallel virtual file system PVFS2 and a distributed storage data caching system, set up an experimental framework for a DOE CMS Tier 2 site at University of Nebraska-Lincoln and conduct benchmark, evaluation and validation studies

Storage Systems for Non-volatile Memory Devices

This dissertation presents novel approaches to the use of non-volatile memory devices in building storage systems. There are many types of non-volatile memory devices, and they usually have better performance than regular magnetic hard disks in terms of throughput and latency. This dissertation focused on two of them, NAND flash memory and Phase Change Memory (PCM). This work consisted of two parts. The first part was to design a high-performance hybrid storage system employing Solid State Drives that are build out of NAND flash memory and Hard Disk Drives. In this hybrid system, we proposed two different policies to improve its performance. One is to exploit the fact that the performances of Solid State Drive and Hard Disk Drive are asymmetric and the other is to exploit concurrency on multiple devices. We implemented prototypes in Linux and evaluate both policies in multiple workloads and multiple configurations. The results showed that the proposed approaches improve the performance significantly, and adapt to different configurations of the system under different workloads. The second part was to implement a file system on a special class of memory devices, Storage Class Memory (SCM), which is both byte addressable and also nonvolatile, e.g. PCM. We claimed that both the existing regular file systems and the memory based file systems are not suitable for SCM, and proposed a new file system, called SCMFS, which is implemented on the virtual address space. In SCMFS, we utilized the existing memory management module in the operating system to do the block management. Our design keeps address space within a file contiguous to reduce the block management software. The simplicity of SCMFS not only makes it easy to implement, but also improves the performance. We implemented a prototype of SCMFS in Linux and evaluated its performance through multiple benchmarks

The Umbrella File System: Storage Management Across Heterogeneous Devices

With the advent of Flash based solid state devices (SSDs), the differences in physical devices used to store data in computers are becoming more and more pronounced. Effectively mapping the differences in storage devices to the files, and applications using the devices, is the problem addressed in this dissertation. This dissertation presents the Umbrella File System (UmbrellaFS), a layered file system designed to effectively map file and device level differences, while maintaining a single coherent directory structure for users. Particular files are directed to appropriate underlying file systems by intercepting system calls connecting the Virtual File System (VFS) to the underlying file systems. Files are evaluated by a policy module that can examine both filenames and file metadata to make decisions about final placement. Files are transparently directed to and moved between appropriate file systems based on their characteristics. A prototype of UmbrellaFS is implemented as a loadable kernel module in the 2.4 and 2.6 Linux kernels. In addition to providing the ability to direct files to file systems, UmbrellaFS enables different decisions at other layers of the storage stack. In particular, alternate page cache writeback methods are presented through the use of UmbrellaFS. A multiple queue strategy based on file sequentiality and a sorting strategy are presented as alternatives to standard Linux cache writeback protocols. These strategies are implemented in a 2.6 Linux kernel and show improvements in a variety of benchmarks and tests

Survey of Transportation of Adaptive Multimedia Streaming service in Internet

[DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; García-García, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

A New I/O Scheduler for Solid State Devices

Since the emergence of solid state devices onto the storage scene, improvements in capacity and price have brought them to the point where they are becoming a viable alternative to traditional magnetic storage for some applications. Current file system and device level I/O scheduler design is optimized for rotational magnetic hard disk drives. Since solid state devices have drastically different properties and structure, we may need to rethink the design of some aspects of the file system and scheduler levels of the I/O subsystem. In this thesis, we consider the current approach to I/O scheduling and show that the current scheduler design may not be ideally suited to solid state devices. We also present a framework for extracting some device parameters of solid state drives. Using the information from the parameter extraction, we present a new I/O scheduler design which utilizes the structure of solid state devices to efficiently schedule writes. The new scheduler, implemented on a 2.6 Linux kernel, shows up to 25% improvement for common workloads

IMPROVING THE PERFORMANCE OF HYBRID MAIN MEMORY THROUGH SYSTEM AWARE MANAGEMENT OF HETEROGENEOUS RESOURCES

Modern computer systems feature memory hierarchies which typically include DRAM as the main memory and HDD as the secondary storage. DRAM and HDD have been extensively used for the past several decades because of their high performance and low cost per bit at their level of hierarchy. Unfortunately, DRAM is facing serious scaling and power consumption problems, while HDD has suffered from stagnant performance improvement and poor energy efficiency. After all, computer system architects have an implicit consensus that there is no hope to improve future system’s performance and power consumption unless something fundamentally changes. To address the looming problems with DRAM and HDD, emerging Non-Volatile RAMs (NVRAMs) such as Phase Change Memory (PCM) or Spin-Transfer-Toque Magnetoresistive RAM (STT-MRAM) have been actively explored as new media of future memory hierarchy. However, since these NVRAMs have quite different characteristics from DRAM and HDD, integrating NVRAMs into conventional memory hierarchy requires significant architectural re-considerations and changes, imposing additional and complicated design trade-offs on the memory hierarchy design. This work assumes a future system in which both main memory and secondary storage include NVRAMs and are placed on the same memory bus. In this system organization, this dissertation work has addressed a problem facing the efficient exploitation of NVRAMs and DRAM integrated into a future platform’s memory hierarchy. Especially, this dissertation has investigated the system performance and lifetime improvement endowed by a novel system architecture called Memorage which co-manages all available physical NVRAM resources for main memory and storage at a system-level. Also, the work has studied the impact of a model-guided, hardware-driven page swap in a hybrid main memory on the application performance. Together, the two ideas enable a future system to ameliorate high system performance degradation under heavy memory pressure and to avoid an inefficient use of DRAM capacity due to injudicious page swap decisions. In summary, this research has not only demonstrated how emerging NVRAMs can be effectively employed and integrated in order to enhance the performance and endurance of a future system, but also helped system architects understand important design trade-offs for emerging NVRAMs based memory and storage systems