Comparing Filesystem Performance: Red Hat Enterprise Linux 6 Vs
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Bull SAS: Novascale B260 (Intel Xeon Processor 5110,1.60Ghz)
SPEC CINT2006 Result spec Copyright 2006-2014 Standard Performance Evaluation Corporation Bull SAS SPECint2006 = 10.2 NovaScale B260 (Intel Xeon processor 5110,1.60GHz) SPECint_base2006 = 9.84 CPU2006 license: 20 Test date: Dec-2006 Test sponsor: Bull SAS Hardware Availability: Dec-2006 Tested by: Bull SAS Software Availability: Dec-2006 0 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 12.7 400.perlbench 11.6 8.64 401.bzip2 8.41 6.59 403.gcc 6.38 11.9 429.mcf 12.7 12.0 445.gobmk 10.6 6.90 456.hmmer 6.72 10.8 458.sjeng 9.90 11.0 462.libquantum 10.8 17.1 464.h264ref 16.8 9.22 471.omnetpp 8.38 7.84 473.astar 7.83 12.5 483.xalancbmk 12.4 SPECint_base2006 = 9.84 SPECint2006 = 10.2 Hardware Software CPU Name: Intel Xeon 5110 Operating System: Windows Server 2003 Enterprise Edition (32 bits) CPU Characteristics: 1.60 GHz, 4MB L2, 1066MHz bus Service Pack1 CPU MHz: 1600 Compiler: Intel C++ Compiler for IA32 version 9.1 Package ID W_CC_C_9.1.033 Build no 20061103Z FPU: Integrated Microsoft Visual Studio .NET 2003 (lib & linker) CPU(s) enabled: 1 core, 1 chip, 2 cores/chip MicroQuill SmartHeap Library 8.0 (shlW32M.lib) CPU(s) orderable: 1 to 2 chips Auto Parallel: No Primary Cache: 32 KB I + 32 KB D on chip per core File System: NTFS Secondary Cache: 4 MB I+D on chip per chip System State: Default L3 Cache: None Base Pointers: 32-bit Other Cache: None Peak Pointers: 32-bit Memory: 8 GB (2GB DIMMx4, FB-DIMM PC2-5300F ECC CL5) Other Software: None Disk Subsystem: 73 GB SAS, 10000RPM Other Hardware: None -
Serverless Network File Systems
Serverless Network File Systems Thomas E. Anderson, Michael D. Dahlin, Jeanna M. Neefe, David A. Patterson, Drew S. Roselli, and Randolph Y. Wang Computer Science Division University of California at Berkeley Abstract In this paper, we propose a new paradigm for network file system design, serverless network file systems. While traditional network file systems rely on a central server machine, a serverless system utilizes workstations cooperating as peers to provide all file system services. Any machine in the system can store, cache, or control any block of data. Our approach uses this location independence, in combination with fast local area networks, to provide better performance and scalability than traditional file systems. Further, because any machine in the system can assume the responsibilities of a failed component, our serverless design also provides high availability via redundant data storage. To demonstrate our approach, we have implemented a prototype serverless network file system called xFS. Preliminary performance measurements suggest that our architecture achieves its goal of scalability. For instance, in a 32-node xFS system with 32 active clients, each client receives nearly as much read or write throughput as it would see if it were the only active client. 1. Introduction A serverless network file system distributes storage, cache, and control over cooperating workstations. This approach contrasts with traditional file systems such as Netware [Majo94], NFS [Sand85], Andrew [Howa88], and Sprite [Nels88] where a central server machine stores all data and satisfies all client cache misses. Such a central server is both a performance and reliability bottleneck. A serverless system, on the other hand, distributes control processing and data storage to achieve scalable high performance, migrates the responsibilities of failed components to the remaining machines to provide high availability, and scales gracefully to simplify system management. -
CS 5600 Computer Systems
CS 5600 Computer Systems Lecture 10: File Systems What are We Doing Today? • Last week we talked extensively about hard drives and SSDs – How they work – Performance characterisEcs • This week is all about managing storage – Disks/SSDs offer a blank slate of empty blocks – How do we store files on these devices, and keep track of them? – How do we maintain high performance? – How do we maintain consistency in the face of random crashes? 2 • ParEEons and MounEng • Basics (FAT) • inodes and Blocks (ext) • Block Groups (ext2) • Journaling (ext3) • Extents and B-Trees (ext4) • Log-based File Systems 3 Building the Root File System • One of the first tasks of an OS during bootup is to build the root file system 1. Locate all bootable media – Internal and external hard disks – SSDs – Floppy disks, CDs, DVDs, USB scks 2. Locate all the parEEons on each media – Read MBR(s), extended parEEon tables, etc. 3. Mount one or more parEEons – Makes the file system(s) available for access 4 The Master Boot Record Address Size Descripon Hex Dec. (Bytes) Includes the starEng 0x000 0 Bootstrap code area 446 LBA and length of 0x1BE 446 ParEEon Entry #1 16 the parEEon 0x1CE 462 ParEEon Entry #2 16 0x1DE 478 ParEEon Entry #3 16 0x1EE 494 ParEEon Entry #4 16 0x1FE 510 Magic Number 2 Total: 512 ParEEon 1 ParEEon 2 ParEEon 3 ParEEon 4 MBR (ext3) (swap) (NTFS) (FAT32) Disk 1 ParEEon 1 MBR (NTFS) 5 Disk 2 Extended ParEEons • In some cases, you may want >4 parEEons • Modern OSes support extended parEEons Logical Logical ParEEon 1 ParEEon 2 Ext. -
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. -
XFS: There and Back ...And There Again? Slide 1 of 38
XFS: There and Back.... .... and There Again? Dave Chinner <[email protected]> <[email protected]> XFS: There and Back .... and There Again? Slide 1 of 38 Overview • Story Time • Serious Things • These Days • Shiny Things • Interesting Times XFS: There and Back .... and There Again? Slide 2 of 38 Story Time • Way back in the early '90s • Storage exceeding 32 bit capacities • 64 bit CPUs, large scale MP • Hundreds of disks in a single machine • XFS: There..... Slide 3 of 38 "x" is for Undefined xFS had to support: • Fast Crash Recovery • Large File Systems • Large, Sparse Files • Large, Contiguous Files • Large Directories • Large Numbers of Files • - Scalability in the XFS File System, 1995 http://oss.sgi.com/projects/xfs/papers/xfs_usenix/index.html XFS: There..... Slide 4 of 38 The Early Years XFS: There..... Slide 5 of 38 The Early Years • Late 1994: First Release, Irix 5.3 • Mid 1996: Default FS, Irix 6.2 • Already at Version 4 • Attributes • Journalled Quotas • link counts > 64k • feature masks • • XFS: There..... Slide 6 of 38 The Early Years • • Allocation alignment to storage geometry (1997) • Unwritten extents (1998) • Version 2 directories (1999) • mkfs time configurable block size • Scalability to tens of millions of directory entries • • XFS: There..... Slide 7 of 38 What's that Linux Thing? • Feature development mostly stalled • Irix development focussed on CXFS • New team formed for Linux XFS port! • Encumberance review! • Linux was missing lots of bits XFS needed • Lot of work needed • • XFS: There and..... Slide 8 of 38 That Linux Thing? XFS: There and..... Slide 9 of 38 Light that fire! • 2000: SGI releases XFS under GPL • • 2001: First stable XFS release • • 2002: XFS merged into 2.5.36 • • JFS follows similar timeline • XFS: There and.... -
Hypervisors Vs. Lightweight Virtualization: a Performance Comparison
2015 IEEE International Conference on Cloud Engineering Hypervisors vs. Lightweight Virtualization: a Performance Comparison Roberto Morabito, Jimmy Kjällman, and Miika Komu Ericsson Research, NomadicLab Jorvas, Finland [email protected], [email protected], [email protected] Abstract — Virtualization of operating systems provides a container and alternative solutions. The idea is to quantify the common way to run different services in the cloud. Recently, the level of overhead introduced by these platforms and the lightweight virtualization technologies claim to offer superior existing gap compared to a non-virtualized environment. performance. In this paper, we present a detailed performance The remainder of this paper is structured as follows: in comparison of traditional hypervisor based virtualization and Section II, literature review and a brief description of all the new lightweight solutions. In our measurements, we use several technologies and platforms evaluated is provided. The benchmarks tools in order to understand the strengths, methodology used to realize our performance comparison is weaknesses, and anomalies introduced by these different platforms in terms of processing, storage, memory and network. introduced in Section III. The benchmark results are presented Our results show that containers achieve generally better in Section IV. Finally, some concluding remarks and future performance when compared with traditional virtual machines work are provided in Section V. and other recent solutions. Albeit containers offer clearly more dense deployment of virtual machines, the performance II. BACKGROUND AND RELATED WORK difference with other technologies is in many cases relatively small. In this section, we provide an overview of the different technologies included in the performance comparison. -
NOVA: a Log-Structured File System for Hybrid Volatile/Non
NOVA: A Log-structured File System for Hybrid Volatile/Non-volatile Main Memories Jian Xu and Steven Swanson, University of California, San Diego https://www.usenix.org/conference/fast16/technical-sessions/presentation/xu This paper is included in the Proceedings of the 14th USENIX Conference on File and Storage Technologies (FAST ’16). February 22–25, 2016 • Santa Clara, CA, USA ISBN 978-1-931971-28-7 Open access to the Proceedings of the 14th USENIX Conference on File and Storage Technologies is sponsored by USENIX NOVA: A Log-structured File System for Hybrid Volatile/Non-volatile Main Memories Jian Xu Steven Swanson University of California, San Diego Abstract Hybrid DRAM/NVMM storage systems present a host of opportunities and challenges for system designers. These sys- Fast non-volatile memories (NVMs) will soon appear on tems need to minimize software overhead if they are to fully the processor memory bus alongside DRAM. The result- exploit NVMM’s high performance and efficiently support ing hybrid memory systems will provide software with sub- more flexible access patterns, and at the same time they must microsecond, high-bandwidth access to persistent data, but provide the strong consistency guarantees that applications managing, accessing, and maintaining consistency for data require and respect the limitations of emerging memories stored in NVM raises a host of challenges. Existing file sys- (e.g., limited program cycles). tems built for spinning or solid-state disks introduce software Conventional file systems are not suitable for hybrid mem- overheads that would obscure the performance that NVMs ory systems because they are built for the performance char- should provide, but proposed file systems for NVMs either in- acteristics of disks (spinning or solid state) and rely on disks’ cur similar overheads or fail to provide the strong consistency consistency guarantees (e.g., that sector updates are atomic) guarantees that applications require. -
Towards Better Performance Per Watt in Virtual Environments on Asymmetric Single-ISA Multi-Core Systems
Towards Better Performance Per Watt in Virtual Environments on Asymmetric Single-ISA Multi-core Systems Viren Kumar Alexandra Fedorova Simon Fraser University Simon Fraser University 8888 University Dr 8888 University Dr Vancouver, Canada Vancouver, Canada [email protected] [email protected] ABSTRACT performance per watt than homogeneous multicore proces- Single-ISA heterogeneous multicore architectures promise to sors. As power consumption in data centers becomes a grow- deliver plenty of cores with varying complexity, speed and ing concern [3], deploying ASISA multicore systems is an performance in the near future. Virtualization enables mul- increasingly attractive opportunity. These systems perform tiple operating systems to run concurrently as distinct, in- at their best if application workloads are assigned to het- dependent guest domains, thereby reducing core idle time erogeneous cores in consideration of their runtime proper- and maximizing throughput. This paper seeks to identify a ties [4][13][12][18][24][21]. Therefore, understanding how to heuristic that can aid in intelligently scheduling these vir- schedule data-center workloads on ASISA systems is an im- tualized workloads to maximize performance while reducing portant problem. This paper takes the first step towards power consumption. understanding the properties of data center workloads that determine how they should be scheduled on ASISA multi- We propose that the controlling domain in a Virtual Ma- core processors. Since virtual machine technology is a de chine Monitor or hypervisor is relatively insensitive to changes facto standard for data centers, we study virtual machine in core frequency, and thus scheduling it on a slower core (VM) workloads. saves power while only slightly affecting guest domain per- formance. -
Filesystem Considerations for Embedded Devices ELC2015 03/25/15
Filesystem considerations for embedded devices ELC2015 03/25/15 Tristan Lelong Senior embedded software engineer Filesystem considerations ABSTRACT The goal of this presentation is to answer a question asked by several customers: which filesystem should you use within your embedded design’s eMMC/SDCard? These storage devices use a standard block interface, compatible with traditional filesystems, but constraints are not those of desktop PC environments. EXT2/3/4, BTRFS, F2FS are the first of many solutions which come to mind, but how do they all compare? Typical queries include performance, longevity, tools availability, support, and power loss robustness. This presentation will not dive into implementation details but will instead summarize provided answers with the help of various figures and meaningful test results. 2 TABLE OF CONTENTS 1. Introduction 2. Block devices 3. Available filesystems 4. Performances 5. Tools 6. Reliability 7. Conclusion Filesystem considerations ABOUT THE AUTHOR • Tristan Lelong • Embedded software engineer @ Adeneo Embedded • French, living in the Pacific northwest • Embedded software, free software, and Linux kernel enthusiast. 4 Introduction Filesystem considerations Introduction INTRODUCTION More and more embedded designs rely on smart memory chips rather than bare NAND or NOR. This presentation will start by describing: • Some context to help understand the differences between NAND and MMC • Some typical requirements found in embedded devices designs • Potential filesystems to use on MMC devices 6 Filesystem considerations Introduction INTRODUCTION Focus will then move to block filesystems. How they are supported, what feature do they advertise. To help understand how they compare, we will present some benchmarks and comparisons regarding: • Tools • Reliability • Performances 7 Block devices Filesystem considerations Block devices MMC, EMMC, SD CARD Vocabulary: • MMC: MultiMediaCard is a memory card unveiled in 1997 by SanDisk and Siemens based on NAND flash memory. -
I.MX 8Quadxplus Power and Performance
NXP Semiconductors Document Number: AN12338 Application Note Rev. 4 , 04/2020 i.MX 8QuadXPlus Power and Performance 1. Introduction Contents This application note helps you to design power 1. Introduction ........................................................................ 1 management systems. It illustrates the current drain 2. Overview of i.MX 8QuadXPlus voltage supplies .............. 1 3. Power measurement of the i.MX 8QuadXPlus processor ... 2 measurements of the i.MX 8QuadXPlus Applications 3.1. VCC_SCU_1V8 power ........................................... 4 Processors taken on NXP Multisensory Evaluation Kit 3.2. VCC_DDRIO power ............................................... 4 (MEK) Platform through several use cases. 3.3. VCC_CPU/VCC_GPU/VCC_MAIN power ........... 5 3.4. Temperature measurements .................................... 5 This document provides details on the performance and 3.5. Hardware and software used ................................... 6 3.6. Measuring points on the MEK platform .................. 6 power consumption of the i.MX 8QuadXPlus 4. Use cases and measurement results .................................... 6 processors under a variety of low- and high-power 4.1. Low-power mode power consumption (Key States modes. or ‘KS’)…… ......................................................................... 7 4.2. Complex use case power consumption (Arm Core, The data presented in this application note is based on GPU active) ......................................................................... 11 5. SOC -
Digital Forensics Focus Area
Digital Forensics Focus Area Barbara Guttman Forensics@NIST November 6, 2020 Digital Forensics – Enormous Scale • Computer crime is now a big volume crime (even worse now that everyone is online) - both in the number of cases and the impacts of the crimes. • Estimate of 6000% increase in spam (claiming to be PPP, WHO) • Most serious crimes have a nexus to digital forensics: Drug dealing uses phones and drones. Murderers communicate with their victims. Financial fraud uses computers. Child sexual exploitation is recorded and shared online. • 2018: Facebook sent 45 million images to LE • Digital Forensics used to support investigations and prosecutions • Used by Forensics Labs, Lawyers, Police Digital Forensics Overview Digital Forensics goal: Provide trustworthy, useful and timely information Digital Forensics has several problems meeting this goal: 1. Overwhelmed with the volume of material 2. Overwhelmed with the variety of material, the constant change and the technical skills needed to understand the material Digital Forensics needs: 1. High quality tools and techniques 2. Help with operational quality and efficiency Digital Forensic Projects • National Software Reference Library • Computer Forensics Tool Testing • Federated Testing • Computer Forensics Reference Dataset • Tool Catalog • Black Box Study and Digital Forensics Scientific Foundation National Software Reference Library (NSRL) The National Software Reference Library (NSRL): • Collects software • Populates a database with software metadata, individual files, file hashes • -
Software Performance Engineering Using Virtual Time Program Execution
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Spiral - Imperial College Digital Repository IMPERIAL COLLEGE LONDON DEPARTMENT OF COMPUTING Software Performance Engineering using Virtual Time Program Execution Nikolaos Baltas Submitted in part fullment of the requirements for the degree of Doctor of Philosophy in Computing of Imperial College London and the Diploma of Imperial College London To my mother Dimitra for her endless support The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Re- searchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. 4 Abstract In this thesis we introduce a novel approach to software performance engineering that is based on the execution of code in virtual time. Virtual time execution models the timing-behaviour of unmodified applications by scaling observed method times or replacing them with results acquired from performance model simulation. This facilitates the investigation of \what-if" performance predictions of applications comprising an arbitrary combination of real code and performance models. The ability to analyse code and models in a single framework enables performance testing throughout the software lifecycle, without the need to to extract perfor- mance models from code. This is accomplished by forcing thread scheduling decisions to take into account the hypothetical time-scaling or model-based performance specifications of each method.