Details

Autor(en) / Beteiligte

• Thomasian, Alexander,

Titel

Storage systems : organization, performance, coding, reliability, and their data processing

Auflage

First edition

Ort / Verlag

Waltham, Massachusetts : Elsevier,

Erscheinungsjahr

[2022]

Link zum Volltext

• Elsevier Books AutoHoldings

Beschreibungen/Notizen

• Front Cover -- Storage Systems -- Copyright -- Contents -- About the author -- Preface -- Acknowledgments -- Abbreviations and acronyms -- 1 Introduction -- 1.1 Computer systems after WW II -- 1.2 High level programming languages - Fortran -- 1.2.1 A Programming Language - APL -- 1.2.2 COmmon Business Oriented Language - COBOL -- 1.2.3 IBM's PL/I programming language -- 1.2.4 Some early computer companies -- 1.3 Effect of data representation on storage space requirements -- 1.4 Basic computer arithmetic -- 1.5 Author's experience with IBM computers in 1970s -- 1.5.1 IBM computers at Univ. of Tehran and IBM World Trade Corp. in Tehran, Iran -- 1.5.2 My experiences with IBM computers at Tehran Regional Electric Company -- 1.5.3 Customer billing at TREC utility -- 1.5.4 My experience with IBM computers at UCLA -- 1.6 IBM's System 360 and its successors -- 1.6.1 US lawsuits against IBM and AT&amp -- T -- 1.6.2 Amdahl Corp. and plug compatible computers -- 1.6.3 Radio Corporation of America - RCA -- 1.6.4 Electronic Data Systems - EDS and Perot Systems -- 1.7 The IBM S/360 computer family -- 1.8 Operating systems associated with IBM mainframes -- 1.9 Early computer companies possibly competing with IBM -- 1.9.1 Burroughs + UNIVAC = UNISYS -- 1.10 My experience at Burroughs Corp. -- 1.10.1 NCR - National Cash Register Corp. -- 1.10.2 Control Data Corporation -- 1.10.3 Honeywell Corp. -- 1.10.4 Hewlett-Packard - HP Corp. -- 1.10.5 Digital Equipment Corp - DEC -- 1.11 Computer company revenue rankings -- 1.12 Computer structures book -- 1.13 Computer family architectures - CFA -- 1.14 Virtual memory and page replacement algorithms -- 1.15 Memory space fragmentation and dynamic storage allocation -- 1.15.1 Page replacement algorithms -- 1.15.2 Simplified analysis of a paging system -- 1.16 Analysis of thrashing in 2-phase locking - 2PL systems.
• 1.17 CPU caches -- 1.18 Multiprogrammed computer systems -- 1.19 Timesharing systems -- 1.20 Mean response with FCFS and processor-sharing scheduling -- 1.21 Analysis of open and closed queueing network models -- 1.22 Bottleneck analysis and balanced job bounds -- 1.23 Performance analyses of I/O subsystems -- 1.24 Vector supercomputers -- 1.25 Parallel computers -- 1.25.1 The ILLIAC IV computer -- 1.25.2 Thinking Machines Connection Machine -- 1.25.3 Kendall Square Research's KSR-1 -- 1.25.4 Goodyear Massively Parallel Processor - MPP -- 1.25.5 MasPar -- 1.25.6 NCUBE -- 1.25.7 Meiko -- 1.25.8 SUPRENUM -- 1.25.9 Parsytec -- 1.25.10 Intel Personal SuperComputer - iPSC -- 1.25.11 IBM's BlueGene supercomputer -- 1.25.12 Tesla Dojo supercomputer for AI training -- 1.26 The future of supercomputing -- 1.27 Microprocessor CPUs, GPUs, FPGAs, and ASICs -- 1.28 RISCV and other microprocessors -- 1.29 The IBM PC and its compatibles -- 1.29.1 Experience with IBM workstations -- 1.30 Storage studies by Alan Jay Smith at Berkeley -- 1.31 Prefetching -- 1.32 Database buffers -- 1.33 Checkpointing in processing large jobs -- 1.34 Computer related rule of thumb -- 1.34.1 Amdahl rules in developing S/360 computers -- 1.34.2 Amdahl's law in the era of multicore -- 1.34.3 Amazon optimal configurations for x86-based EC2 instances -- 1.34.4 Kung's law -- 1.34.5 Brooks' law -- 1.34.6 Patterson et al.'s roofline bound -- 1.34.7 Gray's rules of thumb -- 1.34.8 Jim Gray's five minute rule -- 1.34.9 Moore's law -- 1.34.10 Wright's law -- 1.34.11 Dennard's law -- 1.34.12 Huang's law for Graphics Processing Units - GPUs -- 1.34.13 Grosch's law -- 1.34.14 Kryder's law -- 1.34.15 Subsecond response times -- 1.35 Conclusions and summary -- 2 Storage technologies and their data -- 2.1 Evolution of recording material -- 2.2 Advertising and e-commerce.
• 2.3 Computer storage technologies -- 2.3.1 Punched cards - Hollerith and IBM -- 2.3.2 Punched paper tapes -- 2.3.3 Handwriting recognition -- 2.3.4 Delay line memories -- 2.3.5 Core memories -- 2.3.6 Semiconductor memories -- 2.3.7 Redundant array of Independent Memories - RAIM -- 2.3.8 Magnetic Random Access Memory - MRAM -- 2.3.9 Magnetic tapes and tape libraries -- 2.3.10 An analytical model for a tape library -- 2.3.11 Summary of a recent article on magnetic tapes -- 2.3.12 Origins of Hard Disk Drives - HDDs -- 2.3.13 HDD manufacturers -- 2.3.14 Storage technologies expected to replace disk drives -- 2.3.15 Magnetic bubble memories -- 2.3.16 Charged Couple Devices - CCDs -- 2.3.17 Micro-Electro-Mechanical Systems - MEMS -- 2.3.18 IBM Zurich millipede -- 2.3.19 Phase Change Memory - PCM -- 2.3.20 Flash memories -- 2.3.21 Companies producing flash memories -- 2.3.22 Elevating commodity storage with the SALSA host translation layer -- 2.3.23 Flash SSD versus magnetic HDD pricing -- 2.3.24 Pure Storage design of Purity -- 2.3.25 Intel/Micron 3D_XPoint Optane Memory -- 2.3.26 Processing In Memory - PIM -- 2.3.27 Universal memory technology - UltraRAM -- 2.3.28 Racetrack memory -- 2.3.29 Optical storage -- 2.3.30 Holographic memory -- 2.3.31 M-DISC and storage longevity -- 2.3.32 Persistent and NonVolatile Memory - NVM -- 2.3.33 Glass as a new storage medium -- 2.3.34 DNA based archival storage system -- 2.4 Reliability studies of DRAM, HDDs, &amp -- flash SSDs -- 2.4.1 Flash SSD reliability at Facebook, Google &amp -- NetApp -- 2.5 Storage Networking Industry Association - SNIA -- 2.5.1 Solid state storage performance -- 2.5.2 Persistent Memory Forum -- 2.5.3 Computational storage -- 2.6 Big data and its sources -- 2.7 Sources of storage content -- 2.8 Ranking and description of media companies -- 2.9 Sources of news: newspapers, radio and TV stations.
• 2.9.1 Newspapers in US and worldwide -- 2.9.2 TV networks in US -- 2.10 Text editing and formatting languages -- 2.11 Online books sources -- 2.12 Free book download web sites -- 2.13 Data, image, audio and video compression -- 2.13.1 Data compression -- 2.13.2 Huffman coding/encoding -- 2.13.3 Lempel-Ziv - LZ encoding -- 2.13.4 Arithmetic coding -- 2.13.5 Miscellaneous topics on data compression -- 2.13.6 Universal Resource Locator - URL shortener -- 2.13.7 Image compression -- 2.13.8 Video/audio compression -- 2.14 Main memory data compression -- 2.15 Data deduplication in storage systems -- 2.15.1 Data deduplication at Microsoft -- 2.15.2 The Venti prototype at Bell Labs/Lucent -- 2.15.3 Data Domain deduplication -- 2.15.4 Datrium -- 2.15.5 Summary of a major survey on data deduplication -- 2.16 Up and coming data deduplication companies -- 2.17 Storage research at IBM's Almaden Research Center in 1990s -- 2.18 Cleversafe and its information dispersal technology -- 2.19 Recent developments at IBM Research at ARC -- 2.20 Storage research at Hewlett-Packard - HP -- 2.21 Primary storage vendors and enterprise companies in 2020 -- 2.22 All-flash upstart storage companies -- 2.23 Hyperconverged infrastructure for storage systems -- 2.24 Top enterprise storage backup players -- 2.25 Data storage companies: up and coming storage vendors -- 2.26 Parallel file systems -- 2.27 Cloud storage -- 2.27.1 Cloud computing price models -- 2.27.2 Storage as a service in cloud computing -- 2.27.3 Cloud storage elasticity and its benchmarking -- 2.28 Jai Menon's predictions on the future of clouds -- 2.29 Cloud storage companies -- 2.30 Distributed systems research related to clouds -- 2.30.1 OceanStore -- 2.30.2 Inktomi and CAP theorem -- 2.30.3 Replicated data -- 2.30.4 Sky Computing -- 2.31 Data encryption -- 2.31.1 Data encryption for cloud storage.
• 2.32 Conclusions - predictions about storage systems -- 2.32.1 Resurgence in shared storage, but Fibre-Channel fades -- 3 Disk drive data placement and scheduling -- 3.1 The organization of Hard Disk Drives - HDDs -- 3.2 Internal organization of files in UNIX -- 3.3 Review of disk arm scheduling -- 3.3.1 Implementation of SATF -- 3.3.2 Disk performance studies by Windsor Hsu and Alan Jay Smith at IBM ARC -- 3.3.3 Linux support for disk scheduling -- 3.4 Disk scheduling for mixed workloads -- 3.5 Real time disk scheduling for multimedia -- 3.6 Storage virtualization -- 3.7 File placement on disk -- 3.7.1 Anticipatory disk arm placement -- 3.8 Disks with Shingled Magnetic Recording - SMR -- 3.9 Review of analyses of disk scheduling methods -- 3.10 Analytic studies of disk storage -- 3.11 Analysis of a zoned disk with the FCFS scheduling -- 3.11.1 Disk service time in zoned disks with FCFS scheduling -- 3.12 Performance analysis of the SCAN policy -- 3.13 Analysis of the SATF policy -- 3.13.1 Preliminary investigation of SATF -- 3.13.2 First method for the analysis of SATF -- 3.13.3 Second method for the analysis of SATF -- 3.14 Conclusions -- 4 Mirrored &amp -- hybrid arrays -- 4.1 Introduction to mirrored and hybrid disk arrays -- 4.2 Mirrored and hybrid disk array organizations -- 4.2.1 Basic Mirroring - BM -- 4.2.2 Group Rotate Declustering - GRD -- 4.2.3 Interleaved Declustering - ID -- 4.2.4 Chained Declustering - CD -- 4.2.5 Dual striping -- 4.2.6 Logical volume and automatic storage management and GPFS -- 4.2.7 LSI Logic RAID -- 4.2.8 Adaptive disk arrays -- 4.2.9 SSPiRAL (Survivable Storage using Parity in Redundant Array Layout) -- 4.2.10 B-code -- 4.2.11 Weaver codes -- 4.2.12 Robust, Efficient, Scalable, Autonomous, Reliable - RESAR -- 4.2.13 Multiway placement -- 4.2.14 Classification of mirrored and hybrid disk arrays.
• 4.3 Routing read requests in mirrored disks.
• Storage Systems: Organization, Performance, Coding, Reliability and Their Data Processing was motivated by the 1988 Redundant Array of Inexpensive/Independent Disks proposal to replace large form factor mainframe disks with an array of commodity disks. Disk loads are balanced by striping data into strips--with one strip per disk-- and storage reliability is enhanced via replication or erasure coding, which at best dedicates k strips per stripe to tolerate k disk failures. Flash memories have resulted in a paradigm shift with Solid State Drives (SSDs) replacing Hard Disk Drives (HDDs) for high performance applications. RAID and Flash have resulted in the emergence of new storage companies, namely EMC, NetApp, SanDisk, and Purestorage, and a multibillion-dollar storage market. Key new conferences and publications are reviewed in this book. The goal of the book is to expose students, researchers, and IT professionals to the more important developments in storage systems, while covering the evolution of storage technologies, traditional and novel databases, and novel sources of data. We describe several prototypes: FAWN at CMU, RAMCloud at Stanford, and Lightstore at MIT; Oracle's Exadata, AWS' Aurora, Alibaba's PolarDB, Fungible Data Center; and author's paper designs for cloud storage, namely heterogeneous disk arrays and hierarchical RAID. Surveys storage technologies and lists sources of data: measurements, text, audio, images, and video Familiarizes with paradigms to improve performance: caching, prefetching, log-structured file systems, and merge-trees (LSMs) Describes RAID organizations and analyzes their performance and reliability Conserves storage via data compression, deduplication, compaction, and secures data via encryption Specifies implications of storage technologies on performance and power consumption Exemplifies database parallelism for big data, analytics, deep learning via multicore CPUs, GPUs, FPGAs, and ASICs, e.g., Google's Tensor Processing Units.
• Description based on print version record.