File Vs. Block Vs. Object Storage
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File Systems and Disk Layout I/O: the Big Picture
File Systems and Disk Layout I/O: The Big Picture Processor interrupts Cache Memory Bus I/O Bridge Main I/O Bus Memory Disk Graphics Network Controller Controller Interface Disk Disk Graphics Network 1 Rotational Media Track Sector Arm Cylinder Platter Head Access time = seek time + rotational delay + transfer time seek time = 5-15 milliseconds to move the disk arm and settle on a cylinder rotational delay = 8 milliseconds for full rotation at 7200 RPM: average delay = 4 ms transfer time = 1 millisecond for an 8KB block at 8 MB/s Bandwidth utilization is less than 50% for any noncontiguous access at a block grain. Disks and Drivers Disk hardware and driver software provide basic facilities for nonvolatile secondary storage (block devices). 1. OS views the block devices as a collection of volumes. A logical volume may be a partition ofasinglediskora concatenation of multiple physical disks (e.g., RAID). 2. OS accesses each volume as an array of fixed-size sectors. Identify sector (or block) by unique (volumeID, sector ID). Read/write operations DMA data to/from physical memory. 3. Device interrupts OS on I/O completion. ISR wakes up process, updates internal records, etc. 2 Using Disk Storage Typical operating systems use disks in three different ways: 1. System calls allow user programs to access a “raw” disk. Unix: special device file identifies volume directly. Any process that can open thedevicefilecanreadorwriteany specific sector in the disk volume. 2. OS uses disk as backing storage for virtual memory. OS manages volume transparently as an “overflow area” for VM contents that do not “fit” in physical memory. -
Altavault 4.4 Administration Guide
Beta Draft NetApp® AltaVault™ Cloud Integrated Storage 4.4 Administration Guide NetApp, Inc. Telephone: +1 (408) 822-6000 Part number: 215-12478_A0 495 East Java Drive Fax: + 1 (408) 822-4501 November 2017 Sunnyvale, CA 94089 Support telephone: +1(888) 463-8277 U.S. Web: www.netapp.com Feedback: [email protected] Beta Draft Contents Beta Draft Contents Chapter 1 - Introduction of NetApp AltaVault Cloud Integrated Storage ............................................ 11 Overview of AltaVault....................................................................................................................................11 Supported backup applications and cloud destinations...........................................................................11 AutoSupport ............................................................................................................................................11 System requirements and specifications.........................................................................................................11 Documentation and release notes ...................................................................................................................12 Chapter 2 - Deploying the AltaVault appliance ......................................................................................13 Deployment guidelines ...................................................................................................................................13 Basic configuration.........................................................................................................................................15 -
The Parallel File System Lustre
The parallel file system Lustre Roland Laifer STEINBUCH CENTRE FOR COMPUTING - SCC KIT – University of the State Rolandof Baden Laifer-Württemberg – Internal and SCC Storage Workshop National Laboratory of the Helmholtz Association www.kit.edu Overview Basic Lustre concepts Lustre status Vendors New features Pros and cons INSTITUTSLustre-, FAKULTÄTS systems-, ABTEILUNGSNAME at (inKIT der Masteransicht ändern) Complexity of underlying hardware Remarks on Lustre performance 2 16.4.2014 Roland Laifer – Internal SCC Storage Workshop Steinbuch Centre for Computing Basic Lustre concepts Client ClientClient Directory operations, file open/close File I/O & file locking metadata & concurrency INSTITUTS-, FAKULTÄTS-, ABTEILUNGSNAME (in der Recovery,Masteransicht ändern)file status, Metadata Server file creation Object Storage Server Lustre componets: Clients offer standard file system API (POSIX) Metadata servers (MDS) hold metadata, e.g. directory data, and store them on Metadata Targets (MDTs) Object Storage Servers (OSS) hold file contents and store them on Object Storage Targets (OSTs) All communicate efficiently over interconnects, e.g. with RDMA 3 16.4.2014 Roland Laifer – Internal SCC Storage Workshop Steinbuch Centre for Computing Lustre status (1) Huge user base about 70% of Top100 use Lustre Lustre HW + SW solutions available from many vendors: DDN (via resellers, e.g. HP, Dell), Xyratex – now Seagate (via resellers, e.g. Cray, HP), Bull, NEC, NetApp, EMC, SGI Lustre is Open Source INSTITUTS-, LotsFAKULTÄTS of organizational-, ABTEILUNGSNAME -
What Is Object Storage?
What is Object Storage? What is object storage? How does object storage vs file system compare? When should object storage be used? This short paper looks at the technical side of why object storage is often a better building block for storage platforms than file systems are. www.object-matrix.com Object Matrix Ltd [email protected] Experts in Digital Content Governance & Object Storage +44(0)2920 382 308 The Rise of Object Storage Centera the trail blazer… What exactly Object Storage is made of will be discussed later; its benefits and its limitations included. But first of all a brief history of the rise of Object Storage: Concepts around object storage can be dated back to the 1980’s1 , but it wasn’t until around 2002 when EMC launched Centera to the world – a Content Addressable Storage product2 - that there was an object storage product for the world in general3. However, whilst Centera sold well – some sources say over 600PB were sold – there were fundamental issues with the product. In, 2005 I had a meeting with a “next Companies railed against having to use a “proprietary API” for data generation guru” of a top 3 storage access and a simple search on a search engine shows that company, and he boldly told me: “There is Centera had plenty of complaints about its performance. It wasn’t no place for Object Storage. Everything long until the industry was calling time on Centera and its “content you can do on object storage can be addressable storage” (CAS) version of object storage: not only done in the filesystem. -
IBM Cloud Object Storage System On-Premises Features and Benefits Object Storage to Help Solve Terabytes-And-Beyond Storage Challenges
IBM Cloud Cloud Object Storage Data Sheet IBM Cloud Object Storage System on-premises features and benefits Object storage to help solve terabytes-and-beyond storage challenges The IBM® Cloud Object Storage System™ is a breakthrough platform Highlights that helps solve unstructured data challenges for companies worldwide. It is designed to provide scalability, availability, security, • On-line scalability that offers a single manageability, flexibility, and lower total cost of ownership (TCO). storage system and namespace • Security features include a wide The Cloud Object Storage System is deployed in multiple range of capabilities designed to meet configurations as shown in Figure 1. Each node consists of Cloud security requirements Object Storage software running on an industry-standard server. • Reliability and availability characteristics Cloud Object Storage software is compatible with a wide range of of the system are configurable servers from many sources, including a physical or virtual appliance. • Single copy protected data with In addition, IBM conducts certification of specific servers that geo-dispersal creating both efficiency customers want to use in their environment to help insure quick and manageability initial installation, long-term reliability and predictable performance. • Compliance enabled vaults for when compliance requirements or locking down data is required Data source Multiple concurrent paths ACCESSER® LAYER ......... Multiple concurrent paths SLICESTOR® LAYER ......... Figure 1: Multiple configurations of -
Semiconductor Memories
Semiconductor Memories Prof. MacDonald Types of Memories! l" Volatile Memories –" require power supply to retain information –" dynamic memories l" use charge to store information and require refreshing –" static memories l" use feedback (latch) to store information – no refresh required l" Non-Volatile Memories –" ROM (Mask) –" EEPROM –" FLASH – NAND or NOR –" MRAM Memory Hierarchy! 100pS RF 100’s of bytes L1 1nS SRAM 10’s of Kbytes 10nS L2 100’s of Kbytes SRAM L3 100’s of 100nS DRAM Mbytes 1us Disks / Flash Gbytes Memory Hierarchy! l" Large memories are slow l" Fast memories are small l" Memory hierarchy gives us illusion of large memory space with speed of small memory. –" temporal locality –" spatial locality Register Files ! l" Fastest and most robust memory array l" Largest bit cell size l" Basically an array of large latches l" No sense amps – bits provide full rail data out l" Often multi-ported (i.e. 8 read ports, 2 write ports) l" Often used with ALUs in the CPU as source/destination l" Typically less than 10,000 bits –" 32 32-bit fixed point registers –" 32 60-bit floating point registers SRAM! l" Same process as logic so often combined on one die l" Smaller bit cell than register file – more dense but slower l" Uses sense amp to detect small bit cell output l" Fastest for reads and writes after register file l" Large per bit area costs –" six transistors (single port), eight transistors (dual port) l" L1 and L2 Cache on CPU is always SRAM l" On-chip Buffers – (Ethernet buffer, LCD buffer) l" Typical sizes 16k by 32 Static Memory -
File Systems and Storage
FILE SYSTEMS AND STORAGE On Making GPFS Truly General DEAN HILDEBRAND AND FRANK SCHMUCK Dean Hildebrand manages the PFS (also called IBM Spectrum Scale) began as a research project Cloud Storage Software team that quickly found its groove supporting high performance comput- at the IBM Almaden Research ing (HPC) applications [1, 2]. Over the last 15 years, GPFS branched Center and is a recognized G expert in the field of distributed out to embrace general file-serving workloads while maintaining its original and parallel file systems. He pioneered pNFS, distributed design. This article gives a brief overview of the origins of numer- demonstrating the feasibility of providing ous features that we and many others at IBM have implemented to make standard and scalable access to any file GPFS a truly general file system. system. He received a BSc degree in computer science from the University of British Columbia Early Days in 1998 and a PhD in computer science from Following its origins as a project focused on high-performance lossless streaming of multi- the University of Michigan in 2007. media video files, GPFS was soon enhanced to support high performance computing (HPC) [email protected] applications, to become the “General Parallel File System.” One of its first large deployments was on ASCI White in 2002—at the time, the fastest supercomputer in the world. This HPC- Frank Schmuck joined IBM focused architecture is described in more detail in a 2002 FAST paper [3], but from the outset Research in 1988 after receiving an important design goal was to support general workloads through a standard POSIX inter- a PhD in computer science face—and live up to the “General” term in the name. -
EEPROM Emulation
...the world's most energy friendly microcontrollers EEPROM Emulation AN0019 - Application Note Introduction This application note demonstrates a way to use the flash memory of the EFM32 to emulate single variable rewritable EEPROM memory through software. The example API provided enables reading and writing of single variables to non-volatile flash memory. The erase-rewrite algorithm distributes page erases and thereby doing wear leveling. This application note includes: • This PDF document • Source files (zip) • Example C-code • Multiple IDE projects 2013-09-16 - an0019_Rev1.09 1 www.silabs.com ...the world's most energy friendly microcontrollers 1 General Theory 1.1 EEPROM and Flash Based Memory EEPROM stands for Electrically Erasable Programmable Read-Only Memory and is a type of non- volatile memory that is byte erasable and therefore often used to store small amounts of data that must be saved when power is removed. The EFM32 microcontrollers do not include an embedded EEPROM module for byte erasable non-volatile storage, but all EFM32s do provide flash memory for non-volatile data storage. The main difference between flash memory and EEPROM is the erasable unit size. Flash memory is block-erasable which means that bytes cannot be erased individually, instead a block consisting of several bytes need to be erased at the same time. Through software however, it is possible to emulate individually erasable rewritable byte memory using block-erasable flash memory. To provide EEPROM functionality for the EFM32s in an application, there are at least two options available. The first one is to include an external EEPROM module when designing the hardware layout of the application. -
A Hybrid Swapping Scheme Based on Per-Process Reclaim for Performance Improvement of Android Smartphones (August 2018)
Received August 19, 2018, accepted September 14, 2018, date of publication October 1, 2018, date of current version October 25, 2018. Digital Object Identifier 10.1109/ACCESS.2018.2872794 A Hybrid Swapping Scheme Based On Per-Process Reclaim for Performance Improvement of Android Smartphones (August 2018) JUNYEONG HAN 1, SUNGEUN KIM1, SUNGYOUNG LEE1, JAEHWAN LEE2, AND SUNG JO KIM2 1LG Electronics, Seoul 07336, South Korea 2School of Software, Chung-Ang University, Seoul 06974, South Korea Corresponding author: Sung Jo Kim ([email protected]) This work was supported in part by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education under Grant 2016R1D1A1B03931004 and in part by the Chung-Ang University Research Scholarship Grants in 2015. ABSTRACT As a way to increase the actual main memory capacity of Android smartphones, most of them make use of zRAM swapping, but it has limitation in increasing its capacity since it utilizes main memory. Unfortunately, they cannot use secondary storage as a swap space due to the long response time and wear-out problem. In this paper, we propose a hybrid swapping scheme based on per-process reclaim that supports both secondary-storage swapping and zRAM swapping. It attempts to swap out all the pages in the working set of a process to a zRAM swap space rather than killing the process selected by a low-memory killer, and to swap out the least recently used pages into a secondary storage swap space. The main reason being is that frequently swap- in/out pages use the zRAM swap space while less frequently swap-in/out pages use the secondary storage swap space, in order to reduce the page operation cost. -
DAOS: Revolutionizing High-Performance Storage with Intel® Optane™ Technology
SOLUTION BRIEF Distributed Asynchronous Object Storage (DAOS) Intel® Optane™ Technology DAOS: Revolutionizing High-Performance Storage with Intel® Optane™ Technology With the exponential growth of data, distributed storage systems have become not only the heart, but also the bottleneck of data centers. High-latency data access, poor scalability, difficulty managing large datasets, and lack of query capabilities are just a few examples of common hurdles. Traditional storage systems have been designed for rotating media and for POSIX* input/output (I/O). These storage systems represent a key performance bottleneck, and they cannot evolve to support new data models and next-generation workflows. The Convergence of HPC, Big Data, and AI Storage requirements have continued to evolve, with the need to manipulate ever-growing datasets driving a further need to remove barriers between data and compute. Storage is no longer driven by traditional workloads with large streaming writes like checkpoint/restart, but is increasingly driven by complex I/O patterns from new storage pillars. High-performance data-analytics workloads are generating vast quantities of random reads and writes. Artificial-intelligence (AI) workloads are reading far more than traditional high-performance computing (HPC) workloads. Data streaming from instruments into an HPC cluster require better quality of service (QoS) to avoid data loss. Data-access time is now becoming as critical as write bandwidth. New storage semantics are required to query, analyze, filter, and transform datasets. A single storage platform in which next-generation workflows combine HPC, big data, and AI to exchange data and communicate is essential. DAOS Software Stack Intel has been building an entirely open source software ecosystem for data-centric computing, fully optimized for Intel® architecture and non-volatile memory (NVM) technologies, including Intel® Optane™ DC persistent memory and Intel Optane DC SSDs. -
AN-1471 Application Note
AN-1471 APPLICATION NOTE One Technology Way • P. O. Box 9106 • Norwood, MA 02062-9106, U.S.A. • Tel: 781.329.4700 • Fax: 781.461.3113 • www.analog.com ADuCM4050 Flash EEPROM Emulation by Pranit Jadhav and Rafael Lajara INTRODUCTION provides assurance that the flash initialization function works as Nonvolatile data storage is a necessity in many embedded expected. An ECC check is enabled for the entire user space in systems. Data, such as boot up configuration, calibration constants, the flash memory of the ADuCM4050. If ECC errors are reported and network related information, is normally stored on an during any read operation, the ECC engine automatically corrects electronically erasable programmable read only memory 1-bit errors and only reports on detection of 2-bit errors. When a (EEPROM) device. The advantage of using the EEPROM to store read occurs on the flash, appropriate flags are set in the status this data is that a single byte on an EEPROM device can be register of the ADuCM4050. If interrupts are generated, the source rewritten or updated without affecting the contents in the other address of the ECC error causing an interrupt is available in the locations. FLCC0_ECC_ADDR register for the interrupt service routine (ISR) to read. The ADuCM4050 is an ultra low power microcontroller unit (MCU) with integrated flash memory. The ADuCM4050 includes Emulation of the EEPROM on the integrated flash memory 512 kB of embedded flash memory with a 72-bit wide data bus reduces the bill of material (BOM) cost by omitting the EEPROM that provides two 32-bits words of data and one corresponding in the design. -
File System Layout
File Systems Main Points • File layout • Directory layout • Reliability/durability Named Data in a File System index !le name directory !le number structure storage o"set o"set block Last Time: File System Design Constraints • For small files: – Small blocks for storage efficiency – Files used together should be stored together • For large files: – ConCguous allocaon for sequenCal access – Efficient lookup for random access • May not know at file creaon – Whether file will become small or large File System Design Opons FAT FFS NTFS Index Linked list Tree Tree structure (fixed, asym) (dynamic) granularity block block extent free space FAT array Bitmap Bitmap allocaon (fixed (file) locaon) Locality defragmentaon Block groups Extents + reserve Best fit space defrag MicrosoS File Allocaon Table (FAT) • Linked list index structure – Simple, easy to implement – SCll widely used (e.g., thumb drives) • File table: – Linear map of all blocks on disk – Each file a linked list of blocks FAT MFT Data Blocks 0 1 2 3 !le 9 block 3 4 5 6 7 8 9 !le 9 block 0 10 !le 9 block 1 11 !le 9 block 2 12 !le 12 block 0 13 14 15 16 !le 12 block 1 17 18 !le 9 block 4 19 20 FAT • Pros: – Easy to find free block – Easy to append to a file – Easy to delete a file • Cons: – Small file access is slow – Random access is very slow – Fragmentaon • File blocks for a given file may be scaered • Files in the same directory may be scaered • Problem becomes worse as disk fills Berkeley UNIX FFS (Fast File System) • inode table – Analogous to FAT table • inode – Metadata • File owner, access permissions,