Prediction of Optimal Readahead Parameter in Linux by Using Monitoring Tool

Total Page:16

File Type:pdf, Size:1020Kb

Prediction of Optimal Readahead Parameter in Linux by Using Monitoring Tool Prediction of Optimal Readahead Parameter in Linux by Using Monitoring Tool Ekaterina Gorelkina Sergey Grekhov SRC Moscow, Samsung Electronics SRC Moscow, Samsung Electronics [email protected] [email protected] Jaehoon Jeong Mikhail Levin SAIT, Samsung Electronics SRC Moscow, Samsung Electronics [email protected] [email protected] Abstract this paper has a very good facilities to be widely and simply used for embedded applications optimization to Frequently, application developers face to the hidden increase their quality and effectiveness. performance problems that are provided by operating system internal behavior. For overriding such problems, 1 Introduction Linux operation system has a lot of parameters that can be tuned by user-defined values for accelerating the sys- In modern computing systems high performance disk tem performance. However, in common case evaluating drive systems very often have a serious problem related of the best system parameters requires a very time con- with its performance, effectiveness and speed. Usu- suming investigation in Linux operating system area that ally the disk input-output (I/O) performance is related usually is impossible because of strong time limitations with time which needs to mechanical parts of the disk to for development process. move to a location of the data storing. This time usually This paper describes a method that allows any applica- defines the time delays in the data extraction. Operating tion developer to find the optimal value for the Linux systems incorporate disk read-ahead cache to minimize OS parameter: the optimal maximal read-ahead win- the time delays. Typically, the data from the disk are dow size. This parameter can be tuned by optimal buffered in a memory with a relatively fast access time. value in easy way that allows improving application per- If requested data is already reside in the cache mem- formance in short time without getting any knowledge ory, the data can be transferred directly from the cache about Linux kernel internals and spending a lot of time memory to the requester. In result the performance is in- for experimental search for the best system parameters. creased because the access to data from the cache mem- ory is substantially faster than the access from the disk Our method provides the prediction of optimal maximal drive [1]. read-ahead window size for Linux OS by using the mon- itoring tool for Linux kernel. Scenario of our method Very often such cache can be sufficiently effective. But using is very simple that allows obtaining the optimal sometimes it can produce the low system performance. value for maximal read-ahead window size for the sin- This relates with the sensitivity of the read-ahead cache gle application run. Our experiments for Linux 2.6 show to cache hit statistics [2]. A read-ahead cache having that our method detects an optimal read-ahead window a low hit rate may perform more poorly than an un- size for various real embedded applications with ade- cached disk due to caching overhead and queuing de- quate accuracy and optimization effect can be about a lays, among others. This problem is especially impor- few and even a few dozen percents in comparison to de- tant to be solved for embedded systems, because they fault case. The maximal observed optimization effect usually have less memory and slow CPUs than servers for accelerating the embedded application start-up time and workstations. was 59% in comparison to default case. Performance of read-ahead subsystem can be controlled Taking into account these facts the method proposed in by its main parameter - maximal read-ahead window • 83 • 84 • Prediction of Optimal Readahead Parameter in Linux by Using Monitoring Tool size: the maximum amount of data which can be read- tions in Linux kernel that contains general information ahead from block device. The performance of each ap- of system characterization. The current SWAP revision plication that is running under management OS depends can monitor both kernel and application levels of the on the performance of read-ahead cache. Thus, using Linux system. It provides evaluation of a set of impor- optimal maximal read-ahead window size value for the tant system characteristics for main Linux subsystems current application can improve performance of this ap- (such as Memory Management, Process Management, plication significantly. Typically, the finding the opti- File System and Network). Additional, current revision mal maximal read ahead window size for target applica- of SWAP has some automatic performance analysis fea- tion consists of the following steps: (1) tune operating tures such as trace comparison, automatic bottleneck re- system by current maximal read-ahead window; (2) re- gion localization, etc. boot the system; (3) run the target application; (4) mea- We have integrated our method into SWAP framework sure the time of execution of target application. These because SWAP satisfies to all necessary requirements of steps should be repeated several times for various maxi- our method. mal read-ahead window sizes until the optimal value of read-ahead window size will be found. The main dis- 2.1 General Idea advantage of such method is too much time that should be spent for finding the optimal value of maximal read- We suggest that optimal solution can be obtained by ahead window size. Thus, finding the optimal value of minimization of the following two characteristics: the maximal read-ahead window size during single applica- number of requests to the block device and the amount tion run could significantly improve the performance of of pages that were forced to read by target application, target application and save a lot of machine and human but were not used. resources. The big value of maximal read-ahead window size pro- 2 Method Overview vides minimization of the first characteristic – number of requests to the block device. However, in common The suggested technique consists of the following steps: situation the big value of maximal read-ahead window (1) user should collect data from the application and size provides reading a lot of pages from block device OS during application execution by monitoring tool for that are not used by application. In the other words the Linux kernel one time; (2) monitoring tool analyzes col- big value of maximal read-ahead window size makes OS lected data and evaluates optimal maximal read-ahead performs a lot of unnecessary job that is very time con- window size automatically; (3) user can access evalu- suming. It is obvious that application performance de- ated optimal read-ahead window size value via moni- grades because of such OS behavior. toring tool user interface. Thus, in comparison to man- The small value of maximal read-ahead window size ual method of finding optimal read-ahead window size provides minimization of the second characteristic – the and other existing methods (see [11], [12], [13] for de- amount of pages that were forced to read by target ap- tails), the suggested method has the following advan- plication, but were not used. However, in this case op- tages: (1) determines optimal maximal read-ahead win- timization effect of read-ahead cache is decreased be- dow size value during single run of application that is cause of a lot of application requests for memory pages to be optimized; (2) uses existing read-ahead subsystem invoke the requests to the block device instead of re- without any changes. quests to the read-ahead cache. This method is designed to be used as a module of a Thus, to reach the optimal OS behavior for current ap- monitoring tool such as SWAP - System-Wide Analyzer plication we need to obtain such maximal read-ahead of Performance developed by Samsung Research Cen- window size value that provides minimization of both ter (SRC) in Moscow. The initial version of SWAP characteristics simultaneously. was developed in 2006 and uses functional interfaces of Kprobe for providing dynamic instrumentation of Linux 2.2 Collected Data kernel for ARM and MIPS architecture. Next revision of SWAP tool was developed in SRC in 2007. This re- The first step of our method requires collecting the im- vision allowed collecting traces from predefined func- portant information about application behavior during 2010 Linux Symposium • 85 execution for future analyzing and evaluating the result. Application For these purposes, it is necessary to monitor the ac- cesses to the memory that has been performed by appli- Memory cation. SWAP has ability for tracking memory accesses 1 2 3 4 3 1 2 3 4 4 1 1 and organizing them in trace that allows estimating the Read−ahead window Read−ahead window following aspects: 1) the total number of accessed mem- ory pages, loaded from block device; 2) the addresses of 1 Pages which were not used by application accessed memory pages and their source (loaded from 2 Pages which were accessed by application and were block device or not); 3) the order of accesses. read directly from block device, without read−ahead 3 Pages which were accessed by application and were Notice, that our method requires the single application read from block device via read−ahead cache run only for gathering the monitoring information for 4 Pages which were read from block device into read−ahead evaluation of the optimal values of maximal read-ahead cache and were not used by application window size. Figure 1: Read-ahead emulation procedure 2.3 Analysis of Collected Data F = Rrn(Ma;Rws) (1) According to the basic idea, two following values should be minimized simultaneously: where Rrn is the number of requests to the block device, Ma is number of memory accesses that requires map- ping pages from block device and Rws is the maximal • F - number of requests to the block device; read-ahead window size.
Recommended publications
  • Oracle® Linux Administrator's Solutions Guide for Release 6
    Oracle® Linux Administrator's Solutions Guide for Release 6 E37355-64 August 2017 Oracle Legal Notices Copyright © 2012, 2017, Oracle and/or its affiliates. All rights reserved. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. No other rights are granted to the U.S.
    [Show full text]
  • Oracle® Linux 7 Working with LXC
    Oracle® Linux 7 Working With LXC F32445-02 October 2020 Oracle Legal Notices Copyright © 2020, Oracle and/or its affiliates. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, then the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs) and Oracle computer documentation or other Oracle data delivered to or accessed by U.S. Government end users are "commercial computer software" or "commercial computer software documentation" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, the use, reproduction, duplication, release, display, disclosure, modification, preparation of derivative works, and/or adaptation of i) Oracle programs (including any operating system, integrated software, any programs embedded, installed or activated on delivered hardware, and modifications of such programs), ii) Oracle computer documentation and/or iii) other Oracle data, is subject to the rights and limitations specified in the license contained in the applicable contract.
    [Show full text]
  • Readahead: Time-Travel Techniques for Desktop and Embedded Systems
    Readahead: time-travel techniques for desktop and embedded systems Michael Opdenacker Free Electrons [email protected] Abstract 1.2 Reading ahead Readahead techniques have successfully been used to The idea of reading ahead is to speed up the access to reduce boot time in recent GNU/Linux distributions like a file by preloading at least parts of its contents in page Fedora Core or Ubuntu. However, in embedded sys- cache ahead of time. This can be done when spare I/O tems with scarce RAM, starting a parallel thread read- resources are available, typically when tasks keep the ing ahead all the files used in system startup is no longer processor busy. Of course, this requires the ability to appropriate. The cached pages could be reclaimed even predict the future! before accessing the corresponding files. Fortunately, the systems we are dealing with are pre- This paper will first guide you through the heuristics dictable or even totally predictable in some situations! implemented in kernelspace, as well as through the userspace interface for preloading files or just announc- ing file access patterns. Desktop implementations will • Predictions by watching file read patterns. If pages be explained and benchmarked. We will then detail Free are read from a file in a sequential manner, it makes Electrons’ attempts to implement an easy to integrate sense to go on reading the next blocks in the file, helper program reading ahead files at the most appropri- even before these blocks are actually requested. ate time in the execution flow. • System startup. The system init sequence doesn’t This paper and the corresponding presentation target change.
    [Show full text]
  • Beyond Init: Systemd Linux Plumbers Conference 2010
    Beyond Init: systemd Linux Plumbers Conference 2010 Kay Sievers Lennart Poettering November 2010 Kay Sievers, Lennart Poettering Beyond Init: systemd Triggers: Boot, Socket, Bus, Device, Path, Timers, More Kay Sievers, Lennart Poettering Beyond Init: systemd Kay Sievers, Lennart Poettering Beyond Init: systemd Substantial coverage of basic OS boot-up tasks, including fsck, mount, quota, hwclock, readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots. Status: almost made Fedora 14. Kay Sievers, Lennart Poettering Beyond Init: systemd including fsck, mount, quota, hwclock, readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots. Status: almost made Fedora 14. Substantial coverage of basic OS boot-up tasks, Kay Sievers, Lennart Poettering Beyond Init: systemd mount, quota, hwclock, readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots. Status: almost made Fedora 14. Substantial coverage of basic OS boot-up tasks, including fsck, Kay Sievers, Lennart Poettering Beyond Init: systemd quota, hwclock, readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots. Status: almost made Fedora 14. Substantial coverage of basic OS boot-up tasks, including fsck, mount, Kay Sievers, Lennart Poettering Beyond Init: systemd hwclock, readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots. Status: almost made Fedora 14. Substantial coverage of basic OS boot-up tasks, including fsck, mount, quota, Kay Sievers, Lennart Poettering Beyond Init: systemd readahead, tmpfiles, random-seed, console, static module loading, early syslog, plymouth, shutdown, kexec, SELinux, initrd+initrd-less boots.
    [Show full text]
  • Using the Linux NFS Client with IBM System Storage N Series
    Front cover Using the Linux NFS Client with IBM System Storage N series Kernel releases and mount options Tuning the Linux client for performance and reliability Utilities to support advanced NFS features Alex Osuna Eva Ho Chuck Lever ibm.com/redbooks International Technical Support Organization Using the Linux NFS Client with IBM System Storage N series May 2007 SG24-7462-00 Note: Before using this information and the product it supports, read the information in “Notices” on page v. First Edition (May 2007) This edition applies to Version 7.1 of Data ONTAP and later. © Copyright International Business Machines Corporation 2007. All rights reserved. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents Notices . .v Trademarks . vi Preface . vii The team that wrote this book . vii Become a published author . vii Comments welcome. viii Chapter 1. Linux NSF client overview and solution design considerations . 1 1.1 Introduction . 2 1.2 Deciding which Linux NFS client is right for you . 2 1.2.1 Identifying kernel releases . 3 1.2.2 Current Linux distributions . 4 1.2.3 The NFS client in the 2.4 kernel . 5 1.2.4 The NFS client in the 2.6 kernel . 6 1.3 Mount options for Linux NFS clients . 7 1.4 Choosing a network transport protocol . 12 1.5 Capping the size of read and write operations . 16 Chapter 2. Mount options. 19 2.1 Special mount options. 20 2.2 Tuning NFS client cache behavior . 21 2.3 Mounting with NFS version 4 .
    [Show full text]
  • Troubleshooting Made Easy in Linux
    Expert Reference Series of White Papers Troubleshooting Made Easy In Linux 1-800-COURSES www.globalknowledge.com Troubleshooting Made Easy In Linux David Egan, RHCX Introduction Part 1: Troubleshooting Overview Part 2: Getting Started Part 3: Getting Services Started Part 1: Troubleshooting Overview Every operating system portrays itself as powerful, able to leap tall buildings and applications in single strides, able to weather the storms of prolonged heavy usage, resilient to weathering, and so much more! One of the necessary evils, albeit less often spoken of, in case we jinx something, is the topic of troubleshooting. What could possibly go wrong? Doesn’t everyone believe in fair play, honorable intentions, and being openly honest and straightforward in all things virtual? Where does one start when the operating system does not start, the application does not load or run correctly, the network hangs or a network service does not listen or perform? A common practice is to reload the machine, either from the installation media and then patch it, or from some standardized image. Either way, the problem has only been gotten around, not solved. What if you want to solve the problem itself? What if you need to solve the problem to move ahead? Linux is noted for being rock solid, stable, and easy to manage but not as user friendly ... ‘Where do I click?’ is usually not the answer. There is an ancient, and maybe black, dark, or mysterious ‘art’ form known as troubleshooting. The idea of troubleshooting problems when they occur, whether with the system bootup or setup, networking or network services, or applications in memory, is a daunting task for anyone.
    [Show full text]
  • Evolving Ext4 for Shingled Disks Abutalib Aghayev Theodore Ts’O Garth Gibson Peter Desnoyers Carnegie Mellon University Google, Inc
    Evolving Ext4 for Shingled Disks Abutalib Aghayev Theodore Ts’o Garth Gibson Peter Desnoyers Carnegie Mellon University Google, Inc. Carnegie Mellon University Northeastern University Abstract ST5000AS0011 Drive-Managed SMR (Shingled Magnetic Recording) disks 30 ST8000AS0002 10 ST4000LM016 offer a plug-compatible higher-capacity replacement for WD40NMZW conventional disks. For non-sequential workloads, these 3 WD5000YS disks show bimodal behavior: After a short period of high 1 throughput they enter a continuous period of low throughput. 0.3 We introduce ext4-lazy1, a small change to the Linux 0.1 Throughput (MiB/s) ext4 file system that significantly improves the throughput 0.03 in both modes. We present benchmarks on four different 0.01 drive-managed SMR disks from two vendors, showing that 0 100 200 300 400 500 ext4-lazy achieves 1.7-5.4× improvement over ext4 on a Time (s) metadata-light file server benchmark. On metadata-heavy Figure 1: Throughput of CMR and DM-SMR disks from Table 1 under benchmarks it achieves 2-13× improvement over ext4 on 4 KiB random write traffic. CMR disk has a stable but low throughput under drive-managed SMR disks as well as on conventional disks. random writes. DM-SMR disks, on the other hand, have a short period of high throughput followed by a continuous period of ultra-low throughput. 1 Introduction Type Vendor Model Capacity Form Factor Over 90% of all data in the world has been generated over the DM-SMR Seagate ST8000AS0002 8 TB 3.5 inch last two years [14]. To cope with the exponential growth of DM-SMR Seagate ST5000AS0011 5 TB 3.5 inch data, as well as to stay competitive with NAND flash-based DM-SMR Seagate ST4000LM016 4 TB 2.5 inch solid state drives (SSDs), hard disk vendors are researching DM-SMR Western Digital WD40NMZW 4 TB 2.5 inch capacity-increasing technologies like Shingled Magnetic CMR Western Digital WD5000YS 500 GB 3.5 inch Recording (SMR) [20,60], Heat Assisted Magnetic Record- ing (HAMR) [29], and Bit-Patterned Magnetic Recording Table 1: CMR and DM-SMR disks from two vendors used for evaluation.
    [Show full text]
  • SUSE Linux Enterprise Server 12 SP4 System Analysis and Tuning Guide System Analysis and Tuning Guide SUSE Linux Enterprise Server 12 SP4
    SUSE Linux Enterprise Server 12 SP4 System Analysis and Tuning Guide System Analysis and Tuning Guide SUSE Linux Enterprise Server 12 SP4 An administrator's guide for problem detection, resolution and optimization. Find how to inspect and optimize your system by means of monitoring tools and how to eciently manage resources. Also contains an overview of common problems and solutions and of additional help and documentation resources. Publication Date: September 24, 2021 SUSE LLC 1800 South Novell Place Provo, UT 84606 USA https://documentation.suse.com Copyright © 2006– 2021 SUSE LLC and contributors. All rights reserved. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or (at your option) version 1.3; with the Invariant Section being this copyright notice and license. A copy of the license version 1.2 is included in the section entitled “GNU Free Documentation License”. For SUSE trademarks, see https://www.suse.com/company/legal/ . All other third-party trademarks are the property of their respective owners. Trademark symbols (®, ™ etc.) denote trademarks of SUSE and its aliates. Asterisks (*) denote third-party trademarks. All information found in this book has been compiled with utmost attention to detail. However, this does not guarantee complete accuracy. Neither SUSE LLC, its aliates, the authors nor the translators shall be held liable for possible errors or the consequences thereof. Contents About This Guide xii 1 Available Documentation xiii
    [Show full text]
  • Containers Are Linux, Run/Optimized and Tuned Just Like Linux
    Performance Analysis and Tuning – Part I Containers are Linux, run/optimized and tuned just like Linux. D. John Shakshober (Shak) – Tech Director Performance Engineering Larry Woodman - Senior Consulting Engineer Bill Gray – Senior Principal Performance Engineer Joe Mario - Senior Principal Performance Engineer Agenda: Performance Analysis Tuning Part I • Part I - Containers are Linux, run/optimized and tuned just like Linux. • RHEL Evolution 5->6->7 – Hybrid Clouds Atomic / OSE / RHOP • System Performance/Tools Tuned profiles • NonUniform Memory Access (NUMA) • What is NUMA, RHEL Architecture, Auto-NUMA-Balance • Network Performance – noHZ, Throughput vs Latency-performance • Tuna – IRQ pinning, alter priorities, monitor • NFV w/ DPDK fastdata path • Perf advanced features, BW monitoring, Cache-line tears C-2-C •“Performance + Scale Experts” - 205C - 5:30-7 PM • Free - Soda/Beer/Wine Red Hat Enterprise Linux Performance Evolution • RHEL5 • 1000 Hz, CFQ IO elevator, ktune to change to deadline • Numactl, taskset affinity, static hugepages, IRQ balance, oprofile • RHEL 6 • Tickless scheduler CFS, islocpus, userspace NUMAD tool • Transparent hugepages (THP), numa-IRQ balance, cGroups • Tuna, Perf, PCP ship w/ OS • RHEL 7 • NoHZ_full for CFQ, islocpu, realtime ship same RHEL7 kernel • AutoNuma balance, THP, systemd – Atomic containers RHEL Performance Workload Coverage (bare metal, KVM virt w/ RHEV and/or OSP, LXC Kube/OSEand Industry Standard Benchmarks) Benchmarks – code path coverage Application Performance ● CPU – linpack, lmbench ● Linpack
    [Show full text]
  • Beyond Init: Systemd Linux.Conf.Au 2011
    Beyond Init: systemd linux.conf.au 2011 Lennart Poettering January 2011 Lennart Poettering Beyond Init: systemd compatible with SysV and LSB init scripts. systemd provides aggressive parallelization capabilities, uses socket and D-Bus activation for starting services, offers on-demand starting of daemons, keeps track of processes using Linux cgroups, supports snapshotting and restoring of the system state, maintains mount and automount points and implements an elaborate transactional dependency-based service control logic. It can work as a drop-in replacement for sysvinit." \systemd is a system and session manager for Linux, Lennart Poettering Beyond Init: systemd systemd provides aggressive parallelization capabilities, uses socket and D-Bus activation for starting services, offers on-demand starting of daemons, keeps track of processes using Linux cgroups, supports snapshotting and restoring of the system state, maintains mount and automount points and implements an elaborate transactional dependency-based service control logic. It can work as a drop-in replacement for sysvinit." \systemd is a system and session manager for Linux, compatible with SysV and LSB init scripts. Lennart Poettering Beyond Init: systemd uses socket and D-Bus activation for starting services, offers on-demand starting of daemons, keeps track of processes using Linux cgroups, supports snapshotting and restoring of the system state, maintains mount and automount points and implements an elaborate transactional dependency-based service control logic. It can work as a drop-in replacement for sysvinit." \systemd is a system and session manager for Linux, compatible with SysV and LSB init scripts. systemd provides aggressive parallelization capabilities, Lennart Poettering Beyond Init: systemd offers on-demand starting of daemons, keeps track of processes using Linux cgroups, supports snapshotting and restoring of the system state, maintains mount and automount points and implements an elaborate transactional dependency-based service control logic.
    [Show full text]
  • Device Mapper (Kernel Part of LVM2 Volume Management) Milan Brož [email protected] Device Mapper
    Device mapper (kernel part of LVM2 volume management) Milan Brož [email protected] Device mapper ... modular Linux 2.6 kernel driver . framework for constructing new block devices and mapping them to existing block devices . managed through API (IOCTL interface) . libdevmapper, dmsetup command utility DM knows nothing about ● LVM (logical volumes, volume groups) ► managed by userspace tools (LVM2, EVMS, ...) ● partitions, filesystems ► managed by userspace tools (fdisk, mkfs, mount, ...) 2 Device mapper – mapped device access application write() USERSPACE VFS filesystem ... /dev/mapper/<dev> DEVICE Map IO BLOCK MAPPER LAYER [ MAPPING TABLE ] LOW LEVEL DRIVERS PHYSICAL DEVICES /dev/sda ... EXAMPLE KERNEL 3 Device mapper – control interface application LVM2 application DM library (libdevmapper) USERSPACE IOCTL INTERFACE MAPPING DEVICE MAPPER TABLES DM TARGETS KERNEL 4 Device mapper - TARGETS . linear – maps continuous range of another block device . striped (~RAID0) – striping across devices . mirror (~RAID1) – mirroring devices . crypt – encrypt data using CryptoAPI . snapshot – online snapshots of block device . multipath – access to multipath devices (misc. hw handlers) . zero,error,delay – test and special targets . truecrypt ... raid45 (~RAID4,5) – raid (with dedicated) parity . loop – stack device over another or over file . throttle, rwsplit, flakey – test targets 5 Device mapper – applications lvm2*[.rpm] dmraid*[.rpm] cryptsetup*[.rpm] ... device-mapper*[.rpm] LVM2 EVMS DMRAID cryptsetup ... dmsetup libdevmapper USERSPACE /dev/mapper/control KERNEL DEVICE MAPPER DM & LVM2 / DevConf 2007 6 Simulate disk fail – 100MB disk with bad 9th sector Create new disk and map 9th sector to error target dmsetup create bad_disk 0 8 linear /dev/sdb1 0 8 1 error 9 204791 linear /dev/sdb1 9 Set readahead to 0, check block device size blockdev --setra 0 /dev/mapper/bad_disk blockdev --getsz /dev/mapper/bad_disk DD should fail on 9th sector..
    [Show full text]
  • Arxiv:1901.01161V1 [Cs.CR] 4 Jan 2019
    Page Cache Attacks Daniel Gruss1, Erik Kraft1, Trishita Tiwari2, Michael Schwarz1, Ari Trachtenberg2, Jason Hennessey3, Alex Ionescu4, Anders Fogh5 1 Graz University of Technology, 2 Boston University, 3 NetApp, 4 CrowdStrike, 5 Intel Corporation Abstract last twenty years [3, 40, 53]. Osvik et al. [51] showed that an attacker can observe the cache state at the granularity of We present a new hardware-agnostic side-channel attack that a cache set using Prime+Probe, and later Yarom et al. [77] targets one of the most fundamental software caches in mod- showed this with cache line granularity using Flush+Reload. ern computer systems: the operating system page cache. The While different cache attacks have different use cases, the page cache is a pure software cache that contains all disk- accuracy of Flush+Reload remains unrivaled. backed pages, including program binaries, shared libraries, Indeed, virtually all Flush+Reload attacks target pages in and other files, and our attacks thus work across cores and the so-called page cache [30, 33, 34, 35, 42, 77]. The page CPUs. Our side-channel permits unprivileged monitoring of cache is a pure software cache implemented in all major op- some memory accesses of other processes, with a spatial res- erating systems today, and it contains virtually all pages in olution of 4 kB and a temporal resolution of 2 µs on Linux use. Pages that contain data accessible to multiple programs, (restricted to 6:7 measurements per second) and 466 ns on such as disk-backed pages (e.g., program binaries, shared li- Windows (restricted to 223 measurements per second); this braries, other files, etc.), are shared among all processes re- is roughly the same order of magnitude as the current state- gardless of privilege and permission boundaries [24].
    [Show full text]