Dynamic Virtual Page-based Flash Translation Layer with Novel Hot Data Identification and Adaptive Parallelism Management

Solid-state disks (SSDs) tend to replace traditional motor-driven hard disks in high-end storage devices in past few decades. However, various inherent features, such as out-of-place update [resorting to garbage collection (GC)] and limited endurance (resorting to wear leveling), need to be reduced to a large extent before that day comes. Both the GC and wear leveling fundamentally depend on hot data identification (HDI). In this paper, we propose a hot data-aware flash translation layer architecture based on a dynamic virtual page (DVPFTL) so as to improve the performance and lifetime of NAND flash devices. First, we develop a generalized dual layer HDI (DL-HDI) framework, which is composed of a cold data pre-classifier and a hot data post-identifier. Those can efficiently follow the frequency and recency of information access. Then, we design an adaptive parallelism manager (APM) to assign the clustered data chunks to distinct resident blocks in the SSD so as to prolong its endurance. Finally, the experimental results from our realized SSD prototype indicate that the DVPFTL scheme has reliably improved the parallelizability and endurance of NAND flash devices with improved GC-costs, compared with related works.Peer reviewe

Self-Learning Hot Data Prediction: Where Echo State Network Meets NAND Flash Memories

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Well understanding the access behavior of hot data is significant for NAND flash memory due to its crucial impact on the efficiency of garbage collection (GC) and wear leveling (WL), which respectively dominate the performance and life span of SSD. Generally, both GC and WL rely greatly on the recognition accuracy of hot data identification (HDI). However, in this paper, the first time we propose a novel concept of hot data prediction (HDP), where the conventional HDI becomes unnecessary. First, we develop a hybrid optimized echo state network (HOESN), where sufficiently unbiased and continuously shrunk output weights are learnt by a sparse regression based on L2 and L1/2 regularization. Second, quantum-behaved particle swarm optimization (QPSO) is employed to compute reservoir parameters (i.e., global scaling factor, reservoir size, scaling coefficient and sparsity degree) for further improving prediction accuracy and reliability. Third, in the test on a chaotic benchmark (Rossler), the HOESN performs better than those of six recent state-of-the-art methods. Finally, simulation results about six typical metrics tested on five real disk workloads and on-chip experiment outcomes verified from an actual SSD prototype indicate that our HOESN-based HDP can reliably promote the access performance and endurance of NAND flash memories.Peer reviewe

A Survey on the Integration of NAND Flash Storage in the Design of File Systems and the Host Storage Software Stack

With the ever-increasing amount of data generate in the world, estimated to reach over 200 Zettabytes by 2025, pressure on efficient data storage systems is intensifying. The shift from HDD to flash-based SSD provides one of the most fundamental shifts in storage technology, increasing performance capabilities significantly. However, flash storage comes with different characteristics than prior HDD storage technology. Therefore, storage software was unsuitable for leveraging the capabilities of flash storage. As a result, a plethora of storage applications have been design to better integrate with flash storage and align with flash characteristics. In this literature study we evaluate the effect the introduction of flash storage has had on the design of file systems, which providing one of the most essential mechanisms for managing persistent storage. We analyze the mechanisms for effectively managing flash storage, managing overheads of introduced design requirements, and leverage the capabilities of flash storage. Numerous methods have been adopted in file systems, however prominently revolve around similar design decisions, adhering to the flash hardware constrains, and limiting software intervention. Future design of storage software remains prominent with the constant growth in flash-based storage devices and interfaces, providing an increasing possibility to enhance flash integration in the host storage software stack

고성능 컴퓨팅 시스템에서 버스트 버퍼를 위한 I/O 분리 기법의 실증적 구현

학위논문(석사)--서울대학교 대학원 :공과대학 컴퓨터공학부,2019. 8. 엄현상.To meet the exascale I/O requirements in the High-Performance Computing (HPC), a new I/O subsystem, named Burst Buffer, based on non-volatile memory, has been developed. However, the diverse HPC workloads and the bursty I/O pattern cause severe data fragmentation to SSDs, which creates the need for expensive garbage collection (GC) and also increase the number of bytes actually written to SSD. The new multi-stream feature in SSDs offers an option to reduce the cost of garbage collection. In this paper, we leverage this multi-stream feature to group the I/O streams based on the user IDs and implement this strategy in a burst buffer we call BIOS, short for Burst Buffer with an I/O Separation scheme. Furthermore, to optimize the I/O separation scheme in burst buffer environments, we propose a stream-aware scheduling policy based on burst buffer pools in workload manager and implement the real burst buffer system, BIOS framework, by integrating the BIOS with workload manager. We evaluate the BIOS and framework with a burst buffer I/O traces from Cori Supercomputer including a diverse set of applications. We also disclose and analyze the benefits and limitations of using I/O separation scheme in HPC systems. Experimental results show that the BIOS could improve the performance by 1.44× on average and reduce the Write Amplification Factor (WAF) by up to 1.20×, and prove that the framework can keep on the benefits of the I/O separation scheme in the HPC environment.Abstract Introduction 1 Background and Challenges 5 Burst Buffer 5 Write Amplification in SSDs 6 Multi-streamed SSD 7 Challenges of Multi-stream Feature in Burst Buffers 7 I/O Separation Scheme in Burst Buffer 10 Stream Allocation Criteria 10 Implementation 12 Limitations of User ID-based Stream Allocation 14 BIOS Framework 15 Support in Workload Manager 15 Burst Buffer Pools 16 Stream-Aware Scheduling Policy 18 Workflow of BIOS Framework 20 Evaluation 21 Experiment Setup 21 Evaluation with Synthetic Workload 21 Evaluation with HPC Applications 25 Evaluation with Emulated Workload 27 Evaluation with Different Striping Configuration 29 Evaluation on BIOS Framework 30 Summary and Lessons Learned 33 An I/O Separation Scheme in Burst Buffer 33 Evaluation with Synthetic Workload 33 Evaluation with HPC Applications 33 Evaluation with Emulated Workload 34 Evaluation with Striping Configurations 34 A BIOS Framework 34 Evaluation with Real Burst Buffer Environments 34 Discussion 36 Limited Number of Nodes 36 Advanced BIOS Framework 37 Related work 38 Conclusions 40 Bibliography 42 초록 48Maste

A Survey on the Integration of NAND Flash Storage in the Design of File Systems and the Host Storage Software Stack

With the ever-increasing amount of data generate in the world, estimated to reach over 200 Zettabytes by 2025, pressure on efficient data storage systems is intensifying. The shift from HDD to flash-based SSD provides one of the most fundamental shifts in storage technology, increasing performance capabilities significantly. However, flash storage comes with different characteristics than prior HDD storage technology. Therefore, storage software was unsuitable for leveraging the capabilities of flash storage. As a result, a plethora of storage applications have been design to better integrate with flash storage and align with flash characteristics. In this literature study we evaluate the effect the introduction of flash storage has had on the design of file systems, which providing one of the most essential mechanisms for managing persistent storage. We analyze the mechanisms for effectively managing flash storage, managing overheads of introduced design requirements, and leverage the capabilities of flash storage. Numerous methods have been adopted in file systems, however prominently revolve around similar design decisions, adhering to the flash hardware constrains, and limiting software intervention. Future design of storage software remains prominent with the constant growth in flash-based storage devices and interfaces, providing an increasing possibility to enhance flash integration in the host storage software stack

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

Towards Effective and Efficient Data Management in Embedded Systems and Internet of Things

The majority of today low-end and low-cost embedded devices work in dynamic environments under several constraints such as low power, reduced memory, limited processing and communication, etc. Therefore, their data management is critical. We introduce here a general method for data representation, storage, and transmission in embedded systems based on a compact representation scheme and some heuristics. This method has been implemented, tested, and evaluated within a vehicle tracking system that uses an in-house very low cost microcontroller-based telemetry device, which provides for near-real-time remote vehicle monitoring, energy consumption, ubiquitous health, etc. However, our method is general and can be used for any type of low-cost and resource-constrained embedded device, where data communication from the device to the Internet (or cloud) is involved. Its efficiency and effectiveness are proven by significant reductions of mobile data transmitted, as our case study shows. Further benefits are reducing power consumption and transmission costs

On the use of NAND flash memory in high-performance relational databases

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 47-49).High-density NAND flash storage has become relatively inexpensive due to the popularity of various consumer electronics. Recently, several manufacturers have released IDE-compatible NAND flash-based drives in sizes up to 64 GB at reasonable (sub-$1000) prices. Because flash is significantly more durable than mechanical hard drives and requires considerably less energy, there is some speculation that large data centers will adopt these devices. As database workloads make up a substantial fraction of the processing done by data centers, it is interesting to ask how switching to flash-based storage will affect the performance of database systems. We evaluate this question using IDE-based flash drives from two major manufacturers. We measure their read and write performance and find that flash has excellent random read performance, acceptable sequential read performance, and quite poor write performance compared to conventional IDE disks. We then consider how standard database algorithms are affected by these performance characteristics and find that the fast random read capability dramatically improves the performance of secondary indexes and index-based join algorithms. We next investigate using logstructured filesystems to mitigate the poor write performance of flash and find an 8.2x improvement in random write performance, but at the cost of a 3.7x decrease in random read performance. Finally, we study techniques for exploiting the inherent parallelism of multiple-chip flash devices, and we find that adaptive coding strategies can yield a 2x performance improvement over static ones. We conclude that in many cases flash disk performance is still worse than on traditional drives and that current flash technology may not yet be mature enough for widespread database adoption if performance is a dominant factor. Finally, we briefly speculate how this landscape may change based on expected performance of next-generation flash memories.by Daniel Myers.S.M

Signal Processing for Caching Networks and Non-volatile Memories

The recent information explosion has created a pressing need for faster and more reliable data storage and transmission schemes. This thesis focuses on two systems: caching networks and non-volatile storage systems. It proposes network protocols to improve the efficiency of information delivery and signal processing schemes to reduce errors at the physical layer as well. This thesis first investigates caching and delivery strategies for content delivery networks. Caching has been investigated as a useful technique to reduce the network burden by prefetching some contents during o˙-peak hours. Coded caching [1] proposed by Maddah-Ali and Niesen is the foundation of our algorithms and it has been shown to be a useful technique which can reduce peak traffic rates by encoding transmissions so that different users can extract different information from the same packet. Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. On one hand, distributed storage limits the capability of combining content from different servers into a single message, causing performance losses in coded caching schemes. But, on the other hand, the inherent redundancy existing in distributed storage systems can be used to improve the performance of those schemes through parallelism. This thesis proposes a scheme combining distributed storage of the content in multiple servers and an efficient coded caching algorithm for delivery to the users. This scheme is shown to reduce the peak transmission rate below that of state-of-the-art algorithms