NCQ Vs. I/O Scheduler
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SAS Enters the Mainstream Although Adoption of Serial Attached SCSI
SAS enters the mainstream By the InfoStor staff http://www.infostor.com/articles/article_display.cfm?Section=ARTCL&C=Newst&ARTICLE_ID=295373&KEYWORDS=Adaptec&p=23 Although adoption of Serial Attached SCSI (SAS) is still in the infancy stages, the next 12 months bode well for proponents of the relatively new disk drive/array interface. For example, in a recent InfoStor QuickVote reader poll, 27% of the respondents said SAS will account for the majority of their disk drive purchases over the next year, although Serial ATA (SATA) topped the list with 37% of the respondents, followed by Fibre Channel with 32%. Only 4% of the poll respondents cited the aging parallel SCSI interface (see figure). However, surveys of InfoStor’s readers are skewed by the fact that almost half of our readers are in the channel (primarily VARs and systems/storage integrators), and the channel moves faster than end users in terms of adopting (or at least kicking the tires on) new technologies such as serial interfaces. Click here to enlarge image To get a more accurate view of the pace of adoption of serial interfaces such as SAS, consider market research predictions from firms such as Gartner and International Data Corp. (IDC). Yet even in those firms’ predictions, SAS is coming on surprisingly strong, mostly at the expense of its parallel SCSI predecessor. For example, Gartner predicts SAS disk drives will account for 16.4% of all multi-user drive shipments this year and will garner almost 45% of the overall market in 2009 (see figure on p. 18). -
Self-Learning Disk Scheduling
50 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 21, NO. 1, JANUARY 2009 Self-Learning Disk Scheduling Yu Zhang and Bharat Bhargava, Fellow, IEEE Abstract—The performance of disk I/O schedulers is affected by many factors such as workloads, file systems, and disk systems. Disk scheduling performance can be improved by tuning scheduler parameters such as the length of read timers. Scheduler performance tuning is mostly done manually. To automate this process, we propose four self-learning disk scheduling schemes: Change-sensing Round-Robin, Feedback Learning, Per-request Learning, and Two-layer Learning. Experiments show that the novel Two-layer Learning Scheme performs best. It integrates the workload-level and request-level learning algorithms. It employs feedback learning techniques to analyze workloads, change scheduling policy, and tune scheduling parameters automatically. We discuss schemes to choose features for workload learning, divide and recognize workloads, generate training data, and integrate machine learning algorithms into the Two-layer Learning Scheme. We conducted experiments to compare the accuracy, performance, and overhead of five machine learning algorithms: decision tree, logistic regression, naı¨ve Bayes, neural network, and support vector machine algorithms. Experiments with real-world and synthetic workloads show that self-learning disk scheduling can adapt to a wide variety of workloads, file systems, disk systems, and user preferences. It outperforms existing disk schedulers by as much as 15.8 percent while consuming less than 3 percent - 5 percent of CPU time. Index Terms—Machine learning, application-transparent adaptation, I/O, operating system. Ç 1INTRODUCTION UE to the physical limitations such as time-consuming selection, and parameter tuning. -
SUSE BU Presentation Template 2014
TUT7317 A Practical Deep Dive for Running High-End, Enterprise Applications on SUSE Linux Holger Zecha Senior Architect REALTECH AG [email protected] Table of Content • About REALTECH • About this session • Design principles • Different layers which need to be considered 2 Table of Content • About REALTECH • About this session • Design principles • Different layers which need to be considered 3 About REALTECH 1/2 REALTECH Software REALTECH Consulting . Business Service Management . SAP Mobile . Service Operations Management . Cloud Computing . Configuration Management and CMDB . SAP HANA . IT Infrastructure Management . SAP Solution Manager . Change Management for SAP . IT Technology . Virtualization . IT Infrastructure 4 About REALTECH 2/2 5 Our Customers Manufacturing IT services Healthcare Media Utilities Consumer Automotive Logistics products Finance Retail REALTECH Consulting GmbH 6 Table of Content • About REALTECH • About this session • Design principles • Different layers which need to be considered 7 The Inspiration for this Session • Several performance workshops at customers • Performance escalations at customer who migrated from UNIX (AIX, Solaris, HP-UX) to Linux • Presenting the experiences made at these customers in this session • Preventing the audience from performance degradation caused from: – Significant design mistakes – Wrong architecture assumptions – Having no architecture at all 8 Performance Optimization The False Estimation Upgrading server with CPUs that are 12.5% faster does not improve application -
Engineering Specifications
DOC NO : Rev. Issued Date : 2020/10/08 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : ENGINEERING SPECIFICATIONS Product Name: CVB-CDXXX (WT) Model CVB-CD128 CVB-CD256 CVB-CD512 CVB-CD1024 Author: Ken Liao DOC NO : Rev. Issued Date : 2020/10/08 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Version History Date 0.1 Draft 2020/07/20 1.0 First release 2020/10/08 DOC NO : Rev. Issued Date : 2020/10/08 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Copyright 2020 SOLID STATE STORAGE TECHNOLOGY CORPORATION Disclaimer The information in this document is subject to change without prior notice in order to improve reliability, design, and function and does not represent a commitment on the part of the manufacturer. In no event will the manufacturer be liable for direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the product or documentation, even if advised of the possibility of such damages. This document contains proprietary information protected by copyright. All rights are reserved. No part of this datasheet may be reproduced by any mechanical, electronic, or other means in any form without prior written permission of SOLID STATE STORAGE Technology Corporation. DOC NO : Rev. Issued Date : 2020/10/08 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Table of Contents 1 Introduction ....................................................................... 5 1.1 Overview ............................................................................................. -
On the Performance Variation in Modern Storage Stacks
On the Performance Variation in Modern Storage Stacks Zhen Cao1, Vasily Tarasov2, Hari Prasath Raman1, Dean Hildebrand2, and Erez Zadok1 1Stony Brook University and 2IBM Research—Almaden Appears in the proceedings of the 15th USENIX Conference on File and Storage Technologies (FAST’17) Abstract tions on different machines have to compete for heavily shared resources, such as network switches [9]. Ensuring stable performance for storage stacks is im- In this paper we focus on characterizing and analyz- portant, especially with the growth in popularity of ing performance variations arising from benchmarking hosted services where customers expect QoS guaran- a typical modern storage stack that consists of a file tees. The same requirement arises from benchmarking system, a block layer, and storage hardware. Storage settings as well. One would expect that repeated, care- stacks have been proven to be a critical contributor to fully controlled experiments might yield nearly identi- performance variation [18, 33, 40]. Furthermore, among cal performance results—but we found otherwise. We all system components, the storage stack is the corner- therefore undertook a study to characterize the amount stone of data-intensive applications, which become in- of variability in benchmarking modern storage stacks. In creasingly more important in the big data era [8, 21]. this paper we report on the techniques used and the re- Although our main focus here is reporting and analyz- sults of this study. We conducted many experiments us- ing the variations in benchmarking processes, we believe ing several popular workloads, file systems, and storage that our observations pave the way for understanding sta- devices—and varied many parameters across the entire bility issues in production systems. -
Vytvoření Softwareově Definovaného Úložiště Pro Potřeby Ukládání a Sdílení Dat V Rámci Instituce a Jeho Zálohování Do Datových Úložišť Cesnet
Slezská univerzita v Opavě Centrum informačních technologií Vysoká škola báňská – Technická univerzita Ostrava Fakulta elektrotechniky a informatiky Technická zpráva k projektu 529R1/2014 Vytvoření softwareově definovaného úložiště pro potřeby ukládání a sdílení dat v rámci instituce a jeho zálohování do datových úložišť Cesnet Řešitel: Ing. Jiří Sléžka Spoluřešitelé: Mgr. Jan Nosek, Ing. Pavel Nevlud, Ing. Marek Dvorský, Ph.D., Ing. Jiří Vychodil, Ing. Lukáš Kapičák Leden 2016 Obsah 1 Popis projektu...................................................................................................................................1 2 Cíle projektu.....................................................................................................................................1 3 Volba HW a SW komponent.............................................................................................................1 3.1 Hardware...................................................................................................................................1 3.2 GlusterFS..................................................................................................................................2 3.2.1 Replicated GlusterFS Volume...........................................................................................2 3.2.2 Distributed GlusterFS Volume..........................................................................................3 3.2.3 Striped Glusterfs Volume..................................................................................................3 -
Dell EMC Poweredge RAID Controller S140 User’S Guide Notes, Cautions, and Warnings
Dell EMC PowerEdge RAID Controller S140 User’s Guide Notes, cautions, and warnings NOTE: A NOTE indicates important information that helps you make better use of your product. CAUTION: A CAUTION indicates either potential damage to hardware or loss of data and tells you how to avoid the problem. WARNING: A WARNING indicates a potential for property damage, personal injury, or death. © 2018 - 2019 Dell Inc. or its subsidiaries. All rights reserved. Dell, EMC, and other trademarks are trademarks of Dell Inc. or its subsidiaries. Other trademarks may be trademarks of their respective owners. 2019 - 12 Rev. A09 Contents 1 Overview..................................................................................................................................... 6 PERC S140 specifications.....................................................................................................................................................6 Supported operating systems..............................................................................................................................................8 Supported PowerEdge systems.......................................................................................................................................... 9 Supported physical disks...................................................................................................................................................... 9 Management applications for the PERC S140................................................................................................................ -
Datasheet (PDF)
DOC NO : Rev. Issued Date : 2020/10/07 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : ENGINEERING SPECIFICATIONS Product Name: CVB-8DXXX-WT Model CVB-8D128- WT CVB-8D256 - WT CVB-8D512- WT CVB-8D1024 - WT Author: Ken Liao DOC NO : Rev. Issued Date : 2020/10/07 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Version History Date 0.1 Draft 2020/03/30 1.0 First release 2020/10/07 DOC NO : Rev. Issued Date : 2020/10/07 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Copyright 2020 SOLID STATE STORAGE TECHNOLOGY CORPORATION Disclaimer The information in this document is subject to change without prior notice in order to improve reliability, design, and function and does not represent a commitment on the part of the manufacturer. In no event will the manufacturer be liable for direct, indirect, special, incidental, or consequential damages arising out of the use or inability to use the product or documentation, even if advised of the possibility of such damages. This document contains proprietary information protected by copyright. All rights are reserved. No part of this datasheet may be reproduced by any mechanical, electronic, or other means in any form without prior written permission of SOLID STATE STORAGE Technology Corporation. DOC NO : Rev. Issued Date : 2020/10/07 V1.0 SOLID STATE STORAGE TECHNOLOGY CORPORATION 司 Revised Date : Table of Contents 1 Introduction ....................................................................... 5 1.1 Overview ............................................................................................. -
3.5-Inch, SAS 15K Enterprise Hard Disk Drives MAX3036RC • MAX3073RC • MAX3147RC
Storage High performance and high capacity for your mission critical storage applications. 3.5-Inch, SAS 15K Enterprise Hard Disk Drives MAX3036RC • MAX3073RC • MAX3147RC State-of-the-art hard disk drives for your most demanding enterprise applications 3.5-inch RoHS compliant enterprise hard disk drives offer 15K RPM spindle speed and feature storage capacities up to 147GB1 Ideal for applications requiring high performance and high bandwidth Native Command Queuing (NCQ), providing faster execution of operation commands Uses smaller connectors and cables than U320, a benefit acknowledged by the SCSI Trade Association (STA) Point-to-point connection allows for improved input-output per second (IOPS) in proportion to the number of drives connected 1 One gigabyte (GB) = one billion bytes; accessible capacity will be less and actual capacity depends on the operating environment and formatting. 3.5-Inch, SAS 15K Enterprise Hard Disk Drives MAX3036RC • MAX3073RC • MAX3147RC 3.5-Inch, SAS 15K RPM Series Hard Disk Drive Specifications With more than 35 years of experience in hard disk Description MAX3036RC MAX3073RC MAX3147RC drive technology, Fujitsu can offer state-of-the-art Functional Specifications hard disk drives for your most demanding enterprise Storage capacity (formatted)1 36.7 GB 73.5 GB 147.0 GB applications. Our latest SAS offering is another Disks 1 2 4 Heads (read/write) 2 4 8 example, building on our market leadership in the Bytes/sector 512 Seek time Track to track Read: 0.2 ms (typ.) / Write: 0.4 ms (typ.) exploding SAS market. Average Read: 3.3 ms (typ) / Write: 3.8 ms (typ) The availability of this latest SAS offering Full track Read: 8.0 ms (typ) / Write: 9.0 ms (typ) Average latency time 2.00 ms solidifies Fujitsu as the SAS leader for all form factors Rotational speed (RPM) 15,000 in the enterprise market, reflecting a determination Areal density 59 Gbits/sq. -
Buffered FUSE: Optimising the Android IO Stack for User-Level Filesystem
Int. J. Embedded Systems, Vol. 6, Nos. 2/3, 2014 95 Buffered FUSE: optimising the Android IO stack for user-level filesystem Sooman Jeong and Youjip Won* Hanyang University, #507-2, Annex of Engineering Center, 17 Haengdang-dong, Sungdong-gu, Seoul, 133-791, South Korea E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: In this work, we optimise the Android IO stack for user-level filesystem. Android imposes user-level filesystem over native filesystem partition to provide flexibility in managing the internal storage space and to maintain host compatibility. The overhead of user-level filesystem is prohibitively large and the native storage bandwidth is significantly under-utilised. We overhauled the FUSE layer in the Android platform and propose buffered FUSE (bFUSE) to address the overhead of user-level filesystem. The key technical ingredients of buffered FUSE are: 1) extended FUSE IO size; 2) internal user-level write buffer; 3) independent management thread which performs time-driven FUSE buffer synchronisation. With buffered FUSE, we examined the performances of five different filesystems and three disk scheduling algorithms in a combinatorial manner. With bFUSE on XFS filesystem using the deadline scheduling, we achieved the IO performance improvements of 470% and 419% in Android ICS and JB, respectively, over the existing smartphone device. Keywords: Android; storage; user-level filesystem; FUSE; write buffer; embedded systems. Reference to this paper should be made as follows: Jeong, S. and Won, Y. (2014) ‘Buffered FUSE: optimising the Android IO stack for user-level filesystem’, Int. J. Embedded Systems, Vol. 6, Nos. -
Run-Time Detection of Protocol Bugs in Storage I/O Device Drivers Domenico Cotroneo, Luigi De Simone, Roberto Natella
1 Run-Time Detection of Protocol Bugs in Storage I/O Device Drivers Domenico Cotroneo, Luigi De Simone, Roberto Natella Abstract—Protocol violation bugs in storage device drivers are necessarily lead to such symptoms. The lack of detection can a critical threat for data integrity, since these bugs can silently lead to silent corruptions of users’ data, thus exacerbating the corrupt the commands and data flowing between the OS and cost of software failures. storage devices. Due to their nature, these bugs are notoriously difficult to find by traditional testing. In this paper, we propose In this paper, we propose a novel approach for detecting I/O a run-time monitoring approach for storage device drivers, in protocol violations in storage device drivers, by monitoring at order to detect I/O protocol violations that would otherwise run-time the interactions between the driver and the hardware silently escalate in corruptions of users’ data. The monitoring device controller. The purpose of the run-time monitor is to de- approach detects violations of I/O protocols by automatically learning a reference model from failure-free execution traces. The tect device driver failures in a timely manner. This solution is approach focuses on selected portions of the storage controller meant both to users and engineers of high-availability storage interface, in order to achieve a good trade-off in terms of low systems, including: administrators and end-users of the system, performance overhead and high coverage and accuracy of failure which need to get alarms about the onset of data corruptions in detection. -
PCI Express X4 Card > 2 X Internal M.2 Key B + 1 X Internal Nvme M.2
PCI Express x4 Card > 2 x internal M.2 Key B + 1 x internal NVMe M.2 Key M - Low Profile Form Factor Description This PCI Express card by Delock expands the PC by three M.2 slots. On the card can be connected up to two M.2 SATA modules in format 22110, 2280, 2260, 2242, 2230 and one M.2 PCIe module in format 22110, 2280, 2260, 2242, 2230. The SATA modules will be connected via SATA cables to the motherboard. Specification Item no. 89394 • Connectors: EAN: 4043619893942 internal: 2 x 67 pin M.2 key B slot Country of origin: Taiwan, Republic of 1 x 67 pin M.2 key M slot China 1 x PCI Express x4, V3.0 2 x SATA 6 Gb/s 7 pin receptacle Package: Box 1 x SATA 15 pin power plug • Interface: SATA + PCIe • Supports two M.2 modules in format 22110, 2280, 2260, 2242 and 2230 with key B or key B+M based on SATA and one M.2 module in format 22110, 2280, 2260, 2242 and 2230 with key M or key B+M based on PCIe • Maximum height of the components on the module: 1.5 mm, application of double-sided assembled modules supported • Data transfer rate up to 6 Gb/s • Power supply via PCI Express interface or via SATA 15 pin power connector • Supports Native Command Queuing (NCQ) • Supports NVM Express (NVMe) System requirements • Windows Vista/Vista-64/7/7-64/8.1/8.1-64/10/10-64, Linux Kernel 3.2.0 • PC with one free PCI Express x4 / x8 / x16 / x32 slot • One free SATA 7 pin interface for each connected M.2 module based on SATA Package content • PCI Express card • Low profile bracket • 3 x fixing screw © 2021 by Delock.