From Flash to 3D Xpoint: Performance Bottlenecks and Potentials in Rocksdb with Storage Evolution
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Relieving the Burden of Track Switch in Modern Hard Disk Drives
Multimedia Systems DOI 10.1007/s00530-010-0218-5 REGULAR PAPER Relieving the burden of track switch in modern hard disk drives Jongmin Gim • Youjip Won Received: 11 November 2009 / Accepted: 22 November 2010 Ó Springer-Verlag 2010 Abstract In this work, we propose a novel hard disk 128 KByte, 17% of the disk space becomes unusable. technique, ‘‘AV Disk’’, for modern multimedia applica- Despite the decreased storage area, track aligning tech- tions. Modern hard disk drives adopt complex sector layout nique increases the overall performance of the hard disk. mechanisms to reduce track and head switch overhead. According to our simulation-based experiment, overall disk While these complex sector layout mechanism can reduce performance increases about 5–25%. Given that capacity of average overhead involved in the track and head switch, hard disk increases 100% every year, we cautiously regard they bring larger variability in the overhead. From a it as reasonable tradeoff to increase the I/O latency of the multimedia application’s point of view, it is important to disk. minimize the worst case I/O latency rather than to improve the average IO latency. We focus our effort to minimize Keyword Hard disk drive Á Multimedia Á Track align Á track switch overhead as well as the variability in track Track switch Á Sector geometry Á Audio and video switch overhead involved in disk I/O. We propose that track of the hard disk drive is aligned with a certain IO size. In this work, we develop an elaborate performance model 1 Introduction with which we can compute the optimal IO unit size for multimedia applications. -
Ext4 File System and Crash Consistency
1 Ext4 file system and crash consistency Changwoo Min 2 Summary of last lectures • Tools: building, exploring, and debugging Linux kernel • Core kernel infrastructure • Process management & scheduling • Interrupt & interrupt handler • Kernel synchronization • Memory management • Virtual file system • Page cache and page fault 3 Today: ext4 file system and crash consistency • File system in Linux kernel • Design considerations of a file system • History of file system • On-disk structure of Ext4 • File operations • Crash consistency 4 File system in Linux kernel User space application (ex: cp) User-space Syscalls: open, read, write, etc. Kernel-space VFS: Virtual File System Filesystems ext4 FAT32 JFFS2 Block layer Hardware Embedded Hard disk USB drive flash 5 What is a file system fundamentally? int main(int argc, char *argv[]) { int fd; char buffer[4096]; struct stat_buf; DIR *dir; struct dirent *entry; /* 1. Path name -> inode mapping */ fd = open("/home/lkp/hello.c" , O_RDONLY); /* 2. File offset -> disk block address mapping */ pread(fd, buffer, sizeof(buffer), 0); /* 3. File meta data operation */ fstat(fd, &stat_buf); printf("file size = %d\n", stat_buf.st_size); /* 4. Directory operation */ dir = opendir("/home"); entry = readdir(dir); printf("dir = %s\n", entry->d_name); return 0; } 6 Why do we care EXT4 file system? • Most widely-deployed file system • Default file system of major Linux distributions • File system used in Google data center • Default file system of Android kernel • Follows the traditional file system design 7 History of file system design 8 UFS (Unix File System) • The original UNIX file system • Design by Dennis Ritche and Ken Thompson (1974) • The first Linux file system (ext) and Minix FS has a similar layout 9 UFS (Unix File System) • Performance problem of UFS (and the first Linux file system) • Especially, long seek time between an inode and data block 10 FFS (Fast File System) • The file system of BSD UNIX • Designed by Marshall Kirk McKusick, et al. -
OEM HARD DISK DRIVE SPECIFICATIONS for DPRS
IBML S39H-4500-02 OEM HARD DISK DRIVE SPECIFICATIONS for DPRS-20810/21215 (810/1215 MB) 2.5-Inch Hard Disk Drive with SCSI Interface Revision (1.2) IBML S39H-4500-02 OEM HARD DISK DRIVE SPECIFICATIONS for DPRS-20810/21215 (810/1215 MB) 2.5-Inch Hard Disk Drive with SCSI Interface Revision (1.2) 1st Edition (ver.1.0) S39H-4500-00 (June 16, 1995) 2nd Edition (ver.1.1) S39H-4500-01 (October 24, 1995) 3rd Edition (ver.1.2) S39H-4500-02 (November 1, 1995) The following paragraph does not apply to the United Kingdom or any country where such provisions are inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDES THIS PUBLICATION “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimer or express or implied warranties in certain transactions, therefore, this statement may not apply to You. This publication could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improve- ments and/or changes in the product(s) and/or the program(s) described in this publication at any time. It is possible that this publication may contain reference to, or information about, IBM products (machines and programs), programming, or services that are not announced in your country. Such references or information must not be construed to mean that IBM intends to announce such IBM products, programming, or services in your country. -
Learning Proxmox VE Learning Proxmox VE
Learning Proxmox VE Learning Proxmox VE Proxmox VE 4.1 provides an open source, enterprise virtualization platform on which to host virtual servers as What you will learn from this book either virtual machines or containers. Install and confi gure Proxmox VE 4.1 This book will support your practice of the requisite skills to successfully create, tailor, and deploy virtual machines Download container templates and virtual and containers with Proxmox VE 4.1. appliances Following a survey of PVE's features and characteristics, Create and host containers based on this book will contrast containers with virtual machines and templates establish cases for both. It walks through the installation Create and host virtual machines of Proxmox VE, explores the creation of containers and virtual machines, and suggests best practices for virtual Optimize virtual machine performance disk creation, network confi guration, and Proxmox VE for common use cases host and guest security. Apply the latest security patches to Throughout the book, you will navigate the Proxmox VE a Proxmox VE host Community Experience Distilled 4.1 web interface and explore options for command-line management. Contrast PVE virtual machines and containers in order to recognize their respective use cases Who this book is written for Secure Proxmox VE hosts as well as virtual This book is intended for server and system administrators machines and containers and engineers who are eager to take advantage of the Learning Proxmox VE potential of virtual machines and containers to manage Assess the benefi ts of virtualization with servers more effi ciently and make the best use of regard to budgets, server real estate, Rik Goldman resources, from energy consumption to hardware maintenance, and management time utilization and physical real estate. -
OEM HARD DISK DRIVE SPECIFICATIONS for DORS-31080 / DORS-32160 SCSI-3 FAST-20 68-Pin Single-Ended Models 3.5-Inch Hard Disk Driv
IBML S39H-2859-03 OEM HARD DISK DRIVE SPECIFICATIONS for DORS-31080 / DORS-32160 SCSI-3 FAST-20 68-pin Single-ended Models 3.5-Inch Hard Disk Drive ( 1080 / 2160 MB ) Revision (3.0) IBML S39H-2859-03 OEM HARD DISK DRIVE SPECIFICATIONS for DORS-31080 / DORS-32160 SCSI-3 FAST-20 68-pin Single-ended Models 3.5-Inch Hard Disk Drive ( 1080 / 2160 MB ) Revision (3.0) 1st Edition (Rev.1.0) S39H-2859-00 (Dec. 15, 1995) 2nd Edition (Rev.1.1) S39H-2859-01 (Jan. 22, 1996) 3rd Edition (Rev.2.0) S39H-2859-02 (Mar. 15, 1996) 4th Edition (Rev.3.0) S39H-2859-03 (Jun. 13, 1996) The following paragraph does not apply to the United Kingdom or any country where such provisions are inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDES THIS PUBLICATION “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimer or express or implied warranties in certain transactions, therefore, this statement may not apply to You. This publication could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improve- ments and/or changes in the product(s) and/or the program(s) described in this publication at any time. It is possible that this publication may contain reference to, or information about, IBM products (machines and programs), programming, or services that are not announced in your country. -
Analyzing the Performance of Intel Optane DC Persistent Memory in Storage Over App Direct Mode
Front cover Analyzing the Performance of Intel Optane DC Persistent Memory in Storage over App Direct Mode Introduces DCPMM Storage over Evaluates workload latency and App Direct Mode bandwidth performance Establishes performance Illustrates scaling performance for expectations for DCPMM DCPMM populations capacities Travis Liao Tristian "Truth" Brown Jamie Chou Abstract Intel Optane DC Persistent Memory is the latest memory technology for Lenovo® ThinkSystem™ servers. This technology deviates from contemporary flash storage offerings and utilizes the ground-breaking 3D XPoint non-volatile memory technology to deliver a new level of versatile performance in a compact memory module form factor. As server storage technology continues to advance from devices behind RAID controllers to offerings closer to the processor, it is important to understand the technological differences and suitable use cases. This paper provides a look into the performance of Intel Optane DC Persistent Memory Modules configured in Storage over App Direct Mode operation. At Lenovo Press, we bring together experts to produce technical publications around topics of importance to you, providing information and best practices for using Lenovo products and solutions to solve IT challenges. See a list of our most recent publications at the Lenovo Press web site: http://lenovopress.com Do you have the latest version? We update our papers from time to time, so check whether you have the latest version of this document by clicking the Check for Updates button on the front page of the PDF. Pressing this button will take you to a web page that will tell you if you are reading the latest version of the document and give you a link to the latest if needed. -
A Ffsck: the Fast File System Checker
A ffsck: The Fast File System Checker AO MA, University of Wisconsin, Madison; Backup Recovery Systems Division, EMC Corporation CHRIS DRAGGA, ANDREA C. ARPACI-DUSSEAU, and REMZI H. ARPACI-DUSSEAU, University of Wisconsin, Madison MARSHALL KIRK McKUSICK, McKusick.com Crash failures, hardware errors, and file system bugs can corrupt file systems and cause data loss, despite the presence of journals and similar preventive techniques. While consistency checkers such as fsck can detect this corruption and restore a damaged image to a usable state, they are generally created as an afterthought, to be run only at rare intervals. Thus, checkers operate slowly, causing significant downtime for large scale storage systems when they are needed. We address this dilemma by treating the checker as a key component of the overall file system (and not merely a peripheral add-on). To this end, we present a modified ext3 file system, rext3, to directly support the fast file system checker, ffsck. The rext3 file system colocates and self-identifies its metadata blocks, removing the need for costly seeks and tree traversals during checking. These modifications to the file system allow ffsck to scan and repair the file system at rates approaching the full sequential bandwidth of the underlying device. In addition, we demonstrate that rext3 performs competitively with ext3 in most cases and exceeds it in handling random reads and large writes. Finally, we apply our principles to FFS, the default FreeBSD file system, and its checker, doing so in a lightweight fashion that preserves the file-system layout while still providing some of the gains in performance from ffsck. -
Ext4 File System Performance Analysis in Linux Environment
Recent Advances in Applied & Biomedical Informatics and Computational Engineering in Systems Applications Ext4 file system Performance Analysis in Linux Environment BORISLAV DJORDJEVIC, VALENTINA TIMCENKO Mihailo Pupin Institute University of Belgrade Volgina 15, Belgrade SERBIA [email protected] , [email protected] Abstract: - This paper considers the characteristics and behavior of the modern 64-bit ext4 file system under the Linux operating system, kernel version 2.6. It also provides the performance comparison of ext4 file system with earlier ext3 and ext2 file systems. The testing procedures and further analysis are performed using the Postmark benchmark application. Key-Words: - Linux, FileSystems, ext4/ext3/ext2, journaling, inodes, file block allocation, disk performances 1 Introduction large number of file operations (creation, reading, Ext4 file system is the ext3 file system successor. It writing, appending and file deletion). It comprises is supported on today’s most popular Linux large number of files and data transactions. distributions (RedHat, Ubuntu, Fedora). In contrast Workload can be generated synthetically, as a result to the 32-bit ext3 file system [1] [2], that has only of applying benchmark software, or as a result of working with some real data applications. some features added to its predecessor ext2 and Workload characterization is a hard research maintains a data structure as in the ext2 file system, problem, as arbitrarily complex patterns can the ext4 file system has integrated more substantial frequently occur. In particular, some authors chose changes compared to ext3. Ext4 has improved data to emphasize support for spatial locality in the form structure and enhanced features, which brought of runs of requests to contiguous data, and temporal more reliability and efficiency. -
Initial Experience with 3D Xpoint Main Memory
Initial Experience with 3D XPoint Main Memory Jihang Liu Shimin Chen* State Key Laboratory of Computer Architecture State Key Laboratory of Computer Architecture Institute of Computing Technology, CAS Institute of Computing Technology, CAS University of Chinese Academy of Sciences University of Chinese Academy of Sciences [email protected] [email protected] Abstract—3D XPoint will likely be the first commercially available main memory NVM solution targeting mainstream computer systems. Previous database studies on NVM memory evaluate their proposed techniques mainly on simulated or emulated NVM hardware. In this paper, we report our initial experience experimenting with the real 3D XPoint main memory hardware. I. INTRODUCTION A new generation of Non-Volatile Memory (NVM) tech- nologies, including PCM [1], STT-RAM [2], and Memris- tor [3], are expected to address the DRAM scaling problem and become the next generation main memory technology Fig. 1. AEP machine. in future computer systems [4]–[7]. NVM has become a hot topic in database research in recent years. However, previous First, there are two CPUs in the machine. From the studies evaluate their proposed techniques mainly on simulated /proc/cpuinfo, the CPU model is listed as “Genuine In- or emulated hardware. In this paper, we report our initial tel(R) CPU 0000%@”. Our guess is that the CPU is a test experience with real NVM main memory hardware. model and/or not yet recognized by the Linux kernel. The 3D XPoint is an NVM technology jointly developed by CPU supports the new clwb instruction [9]. Given a memory Intel and Micron [8]. Intel first announced the technology address, clwb writes back to memory the associated cache in 2015. -
After the 3D Xpoint Take-Off, Emerging NVM Keeps Growing1
Press Release February 26, 2020 LYON, France After the 3D XPoint take-off, emerging NVM keeps growing1 OUTLINES: PCM2-based persistent memory hit the market in 2019. And embedded STT-MRAM3 has finally moved into mass production. The overall emerging NVM4 market is poised to reach over US$6 billion in 2025. The embedded business will account for 1/3 of it. Foundries and IDMs5 are accelerating the adoption of embedded emerging NVMs at advanced technology nodes. Rise of in-memory computing is triggering new players’ dynamics. “The stand-alone emerging NVM market will grow to over US$4 billion in 2025”, explains Simone Bertolazzi, PhD. Technology & Market Analyst at Yole Développement (Yole). “It will be driven by two key segments: low-latency storage (enterprise and client drives) and persistent memory (NVDIMMs).” 1 Extracted from Emerging Non-Volatile Memory, Yole Développement, 2020 2 PCM: Phase-Change Memory 3 STT- MRAM : Spin-Transfer Torque Magnetoresistive RAM 4 NVM: Non-Volatile Memory 5 IDM : Integrated Design Manufacturer Press Release The embedded emerging NVM entered the takeoff phase. The embedded market segment is showing a 118% CAGR6 between 2019 and 2025, reaching more than US$2 billion by 2025. In this dynamic context, the market research and strategy consulting company Yole, releases its annual memory report, Emerging Non-Volatile Memory. The 2020 edition presents an overview of the semiconductor memory market with stand-alone7 and embedded memories8. Yole’s memory team proposes today a deep understanding of emerging NVM applications with related market drivers, challenges, technology roadmap, players, and main trends. This report also offers detailed 2019-2025 market forecasts. -
Transforming Business with Data
WHITE PAPER Transforming Business with Data Enterprise infrastructure is pushing the boundaries of data in scope, size, and speed. The right infrastructure tools can help you make better business decisions by getting more value from data. Writing about the data explosion is the IT equivalent of “it was a dark and stormy night.” At this point, it’s an old narrative that misstates the challenge and actually understates the problem. Yes, there’s more data, but there are also more types of data, which further complicates how to store, activate, and monetize this modern-day resource that promises to transform companies and industries. Advanced analytics capabilities, like artificial intelligence (AI) and machine learning, make the machine-generated unstructured and semi-structured data coming from the Internet of Things (IoT) accessible and, thus, valuable. But many companies are still not realizing the full potential of even their conventional, structured data. Less than half of companies’ structured data is being actively used by decision-makers, and less than one percent of companies’ unstructured data is being analyzed or used at all.1 This data needs to be activated through better storage technologies so that companies can realize the full value of their data. One way in which Intel helps activate data is by innovatively disrupting data centers’ data tiers. Traditionally, IT organizations have faced a stark tradeoff with their storage: faster storage was much more expensive than slower storage. It only made economic sense to place the most-important, most-accessed data in fast storage. But if storage can be made faster—particularly less expensive storage— without a proportionate rise in price, more data can be analyzed and acted upon. -
Arxiv:1908.03583V1 [Cs.DC] 9 Aug 2019 1 Introduction
An Empirical Guide to the Behavior and Use of Scalable Persistent Memory Jian Yang Juno Kim Morteza Hoseinzadeh Joseph Izraelevitz Steven Swanson* Nonvolatile Systems Laboratory Computer Science & Engineering University of California, San Diego August 13, 2019 Abstract After nearly a decade of anticipation, scalable nonvolatile memory DIMMs are finally commercially available with the release of Intel’s 3D XPoint DIMM. This new nonvolatile DIMM supports byte-granularity accesses with access times on the order of DRAM, while also providing data storage that survives power outages. Researchers have not idly waited for real nonvolatile DIMMs (NVDIMMs) to arrive. Over the past decade, they have written a slew of papers proposing new programming models, file systems, libraries, and applications built to exploit the performance and flexibility that NVDIMMs promised to deliver. Those papers drew conclusions and made design decisions without detailed knowledge of how real NVDIMMs would behave or how industry would integrate them into computer architectures. Now that 3D XPoint NVDIMMs are actually here, we can provide detailed performance numbers, concrete guidance for programmers on these systems, reevaluate prior art for performance, and reoptimize persistent memory software for the real 3D XPoint DIMM. In this paper, we explore the performance properties and characteristics of Intel’s new 3D XPoint DIMM at the micro and macro level. First, we investigate the basic characteristics of the device, taking special note of the particular ways in which its performance is peculiar relative to traditional DRAM or other past methods used to emulate NVM. From these observations, we recommend a set of best practices to maximize the performance of the device.