ZFS on Linux Performance Evaluation
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Elastic Storage for Linux on System Z IBM Research & Development Germany
Peter Münch T/L Test and Development – Elastic Storage for Linux on System z IBM Research & Development Germany Elastic Storage for Linux on IBM System z © Copyright IBM Corporation 2014 9.0 Elastic Storage for Linux on System z Session objectives • This presentation introduces the Elastic Storage, based on General Parallel File System technology that will be available for Linux on IBM System z. Understand the concepts of Elastic Storage and which functions will be available for Linux on System z. Learn how you can integrate and benefit from the Elastic Storage in a Linux on System z environment. Finally, get your first impression in a live demo of Elastic Storage. 2 © Copyright IBM Corporation 2014 Elastic Storage for Linux on System z Trademarks The following are trademarks of the International Business Machines Corporation in the United States and/or other countries. AIX* FlashSystem Storwize* Tivoli* DB2* IBM* System p* WebSphere* DS8000* IBM (logo)* System x* XIV* ECKD MQSeries* System z* z/VM* * Registered trademarks of IBM Corporation The following are trademarks or registered trademarks of other companies. Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. -
Efficient Implementation of Data Objects in the OSD+-Based Fusion
Efficient Implementation of Data Objects in the OSD+-Based Fusion Parallel File System Juan Piernas(B) and Pilar Gonz´alez-F´erez Departamento de Ingenier´ıa y Tecnolog´ıa de Computadores, Universidad de Murcia, Murcia, Spain piernas,pilar @ditec.um.es { } Abstract. OSD+s are enhanced object-based storage devices (OSDs) able to deal with both data and metadata operations via data and direc- tory objects, respectively. So far, we have focused on designing and implementing efficient directory objects in OSD+s. This paper, however, presents our work on also supporting data objects, and describes how the coexistence of both kinds of objects in OSD+s is profited to efficiently implement data objects and to speed up some commonfile operations. We compare our OSD+-based Fusion Parallel File System (FPFS) with Lustre and OrangeFS. Results show that FPFS provides a performance up to 37 better than Lustre, and up to 95 better than OrangeFS, × × for metadata workloads. FPFS also provides 34% more bandwidth than OrangeFS for data workloads, and competes with Lustre for data writes. Results also show serious scalability problems in Lustre and OrangeFS. Keywords: FPFS OSD+ Data objects Lustre OrangeFS · · · · 1 Introduction File systems for HPC environment have traditionally used a cluster of data servers for achieving high rates in read and write operations, for providing fault tolerance and scalability, etc. However, due to a growing number offiles, and an increasing use of huge directories with millions or billions of entries accessed by thousands of processes at the same time [3,8,12], some of thesefile systems also utilize a cluster of specialized metadata servers [6,10,11] and have recently added support for distributed directories [7,10]. -
IBM Spectrum Scale CSI Driver for Container Persistent Storage
Front cover IBM Spectrum Scale CSI Driver for Container Persistent Storage Abhishek Jain Andrew Beattie Daniel de Souza Casali Deepak Ghuge Harald Seipp Kedar Karmarkar Muthu Muthiah Pravin P. Kudav Sandeep R. Patil Smita Raut Yadavendra Yadav Redpaper IBM Redbooks IBM Spectrum Scale CSI Driver for Container Persistent Storage April 2020 REDP-5589-00 Note: Before using this information and the product it supports, read the information in “Notices” on page ix. First Edition (April 2020) This edition applies to Version 5, Release 0, Modification 4 of IBM Spectrum Scale. © Copyright International Business Machines Corporation 2020. Note to U.S. Government Users Restricted Rights -- Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. iii iv IBM Spectrum Scale CSI Driver for Container Persistent Storage Contents Notices . vii Trademarks . viii Preface . ix Authors. ix Now you can become a published author, too . xi Comments welcome. xii Stay connected to IBM Redbooks . xii Chapter 1. IBM Spectrum Scale and Containers Introduction . 1 1.1 Abstract . 2 1.2 Assumptions . 2 1.3 Key concepts and terminology . 3 1.3.1 IBM Spectrum Scale . 3 1.3.2 Container runtime . 3 1.3.3 Container Orchestration System. 4 1.4 Introduction to persistent storage for containers Flex volumes. 4 1.4.1 Static provisioning. 4 1.4.2 Dynamic provisioning . 4 1.4.3 Container Storage Interface (CSI). 5 1.4.4 Advantages of using IBM Spectrum Scale storage for containers . 5 Chapter 2. Architecture of IBM Spectrum Scale CSI Driver . 7 2.1 CSI Component Overview. 8 2.2 IBM Spectrum Scale CSI driver architecture. -
Globalfs: a Strongly Consistent Multi-Site File System
GlobalFS: A Strongly Consistent Multi-Site File System Leandro Pacheco Raluca Halalai Valerio Schiavoni University of Lugano University of Neuchatelˆ University of Neuchatelˆ Fernando Pedone Etienne Riviere` Pascal Felber University of Lugano University of Neuchatelˆ University of Neuchatelˆ Abstract consistency, availability, and tolerance to partitions. Our goal is to ensure strongly consistent file system operations This paper introduces GlobalFS, a POSIX-compliant despite node failures, at the price of possibly reduced geographically distributed file system. GlobalFS builds availability in the event of a network partition. Weak on two fundamental building blocks, an atomic multicast consistency is suitable for domain-specific applications group communication abstraction and multiple instances of where programmers can anticipate and provide resolution a single-site data store. We define four execution modes and methods for conflicts, or work with last-writer-wins show how all file system operations can be implemented resolution methods. Our rationale is that for general-purpose with these modes while ensuring strong consistency and services such as a file system, strong consistency is more tolerating failures. We describe the GlobalFS prototype in appropriate as it is both more intuitive for the users and detail and report on an extensive performance assessment. does not require human intervention in case of conflicts. We have deployed GlobalFS across all EC2 regions and Strong consistency requires ordering commands across show that the system scales geographically, providing replicas, which needs coordination among nodes at performance comparable to other state-of-the-art distributed geographically distributed sites (i.e., regions). Designing file systems for local commands and allowing for strongly strongly consistent distributed systems that provide good consistent operations over the whole system. -
Solaris 10 End of Life
Solaris 10 end of life Continue Oracle Solaris 10 has had an amazing OS update, including ground features such as zones (Solaris containers), FSS, Services, Dynamic Tracking (against live production operating systems without impact), and logical domains. These features have been imitated in the market (imitation is the best form of flattery!) like all good things, they have to come to an end. Sun Microsystems was acquired by Oracle and eventually, the largest OS known to the industry, needs to be updated. Oracle has set a retirement date of January 2021. Oracle indicated that Solaris 10 systems would need to raise support costs. Oracle has never provided migratory tools to facilitate migration from Solaris 10 to Solaris 11, so migration to Solaris has been slow. In September 2019, Oracle decided that extended support for Solaris 10 without an additional financial penalty would be delayed until 2024! Well its March 1 is just a reminder that Oracle Solaris 10 is getting the end of life regarding support if you accept extended support from Oracle. Combined with the fact gdpR should take effect on May 25, 2018 you want to make sure that you are either upgraded to Solaris 11.3 or have taken extended support to obtain any patches for security issues. For more information on tanningix releases and support dates of old and new follow this link ×Sestive to abort the Unix Error Operating System originally developed by Sun Microsystems SolarisDeveloperSun Microsystems (acquired by Oracle Corporation in 2009)Written inC, C'OSUnixWorking StateCurrentSource ModelMixedInitial release1992; 28 years ago (1992-06)Last release11.4 / August 28, 2018; 2 years ago (2018-08-28)Marketing targetServer, PlatformsCurrent: SPARC, x86-64 Former: IA-32, PowerPCKernel typeMonolithic with dynamically downloadable modulesDefault user interface GNOME-2-LicenseVariousOfficial websitewww.oracle.com/solaris Solaris is the own operating system Of Unix, originally developed by Sunsystems. -
Storage Systems and Input/Output 2018 Pre-Workshop Document
Storage Systems and Input/Output 2018 Pre-Workshop Document Gaithersburg, Maryland September 19-20, 2018 Meeting Organizers Robert Ross (ANL) (lead organizer) Glenn Lockwood (LBL) Lee Ward (SNL) (co-lead) Kathryn Mohror (LLNL) Gary Grider (LANL) Bradley Settlemyer (LANL) Scott Klasky (ORNL) Pre-Workshop Document Contributors Philip Carns (ANL) Quincey Koziol (LBL) Matthew Wolf (ORNL) 1 Table of Contents 1 Table of Contents 2 2 Executive Summary 4 3 Introduction 5 4 Mission Drivers 7 4.1 Overview 7 4.2 Workload Characteristics 9 4.2.1 Common observations 9 4.2.2 An example: Adjoint-based sensitivity analysis 10 4.3 Input/Output Characteristics 11 4.4 Implications of In Situ Analysis on the SSIO Community 14 4.5 Data Organization and Archiving 15 4.6 Metadata and Provenance 18 4.7 Summary 20 5 Computer Science Challenges 21 5.1 Hardware/Software Architectures 21 5.1.1 Storage Media and Interfaces 21 5.1.2 Networks 21 5.1.3 Active Storage 22 5.1.4 Resilience 23 5.1.5 Understandability 24 5.1.6 Autonomics 25 5.1.7 Security 26 5.1.8 New Paradigms 27 5.2 Metadata, Name Spaces, and Provenance 28 5.2.1 Metadata 28 5.2.2 Namespaces 30 5.2.3 Provenance 30 5.3 Supporting Science Workflows - SAK 32 5.3.1 DOE Extreme Scale Use cases - SAK 33 5.3.2 Programming Model Integration - (Workflow Composition for on line workflows, and for offline workflows ) - MW 33 5.3.3 Workflows (Engine) - Provision and Placement MW 34 5.3.4 I/O Middleware and Libraries (Connectivity) - both on-and offline, (not or) 35 2 Storage Systems and Input/Output 2018 Pre-Workshop -
Salt Documentation Release 2014.7.6
Salt Documentation Release 2014.7.6 SaltStack, Inc. May 19, 2015 Contents 1 Introduction to Salt 1 1.1 e 30 second summary ........................................... 1 1.2 Simplicity ................................................... 1 1.3 Parallel execution ............................................... 1 1.4 Building on proven technology ....................................... 2 1.5 Python client interface ............................................ 2 1.6 Fast, flexible, scalable ............................................. 2 1.7 Open ...................................................... 2 1.8 Salt Community ................................................ 2 1.9 Mailing List .................................................. 2 1.10 IRC ....................................................... 3 1.11 Follow on Github ............................................... 3 1.12 Blogs ...................................................... 3 1.13 Example Salt States .............................................. 3 1.14 Follow on ohloh ................................................ 3 1.15 Other community links ............................................ 4 1.16 Hack the Source ................................................ 4 2 Installation 5 2.1 ick Install .................................................. 5 2.2 Platform-specific Installation Instructions ................................. 5 2.3 Dependencies ................................................. 26 2.4 Optional Dependencies ............................................ 27 2.5 Upgrading -
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. -
HFAA: a Generic Socket API for Hadoop File Systems
HFAA: A Generic Socket API for Hadoop File Systems Adam Yee Jeffrey Shafer University of the Pacific University of the Pacific Stockton, CA Stockton, CA [email protected] jshafer@pacific.edu ABSTRACT vices: one central NameNode and many DataNodes. The Hadoop is an open-source implementation of the MapReduce NameNode is responsible for maintaining the HDFS direc- programming model for distributed computing. Hadoop na- tory tree. Clients contact the NameNode in order to perform tively integrates with the Hadoop Distributed File System common file system operations, such as open, close, rename, (HDFS), a user-level file system. In this paper, we intro- and delete. The NameNode does not store HDFS data itself, duce the Hadoop Filesystem Agnostic API (HFAA) to allow but rather maintains a mapping between HDFS file name, Hadoop to integrate with any distributed file system over a list of blocks in the file, and the DataNode(s) on which TCP sockets. With this API, HDFS can be replaced by dis- those blocks are stored. tributed file systems such as PVFS, Ceph, Lustre, or others, thereby allowing direct comparisons in terms of performance Although HDFS stores file data in a distributed fashion, and scalability. Unlike previous attempts at augmenting file metadata is stored in the centralized NameNode service. Hadoop with new file systems, the socket API presented here While sufficient for small-scale clusters, this design prevents eliminates the need to customize Hadoop’s Java implementa- Hadoop from scaling beyond the resources of a single Name- tion, and instead moves the implementation responsibilities Node. Prior analysis of CPU and memory requirements for to the file system itself. -
Filesystems HOWTO Filesystems HOWTO Table of Contents Filesystems HOWTO
Filesystems HOWTO Filesystems HOWTO Table of Contents Filesystems HOWTO..........................................................................................................................................1 Martin Hinner < [email protected]>, http://martin.hinner.info............................................................1 1. Introduction..........................................................................................................................................1 2. Volumes...............................................................................................................................................1 3. DOS FAT 12/16/32, VFAT.................................................................................................................2 4. High Performance FileSystem (HPFS)................................................................................................2 5. New Technology FileSystem (NTFS).................................................................................................2 6. Extended filesystems (Ext, Ext2, Ext3)...............................................................................................2 7. Macintosh Hierarchical Filesystem − HFS..........................................................................................3 8. ISO 9660 − CD−ROM filesystem.......................................................................................................3 9. Other filesystems.................................................................................................................................3 -
A Sense of Time for Node.Js: Timeouts As a Cure for Event Handler Poisoning
A Sense of Time for Node.js: Timeouts as a Cure for Event Handler Poisoning Anonymous Abstract—The software development community has begun to new Denial of Service attack that can be used against EDA- adopt the Event-Driven Architecture (EDA) to provide scalable based services. Our Event Handler Poisoning attack exploits web services. Though the Event-Driven Architecture can offer the most important limited resource in the EDA: the Event better scalability than the One Thread Per Client Architecture, Handlers themselves. its use exposes service providers to a Denial of Service attack that we call Event Handler Poisoning (EHP). The source of the EDA’s scalability is also its Achilles’ heel. Multiplexing unrelated work onto the same thread re- This work is the first to define EHP attacks. After examining EHP vulnerabilities in the popular Node.js EDA framework and duces overhead, but it also moves the burden of time sharing open-source npm modules, we explore various solutions to EHP- out of the thread library or operating system and into the safety. For a practical defense against EHP attacks, we propose application itself. Where OTPCA-based services can rely on Node.cure, which defends a large class of Node.js applications preemptive multitasking to ensure that resources are shared against all known EHP attacks by making timeouts a first-class fairly, using the EDA requires the service to enforce its own member of the JavaScript language and the Node.js framework. cooperative multitasking [89]. An EHP attack identifies a way to defeat the cooperative multitasking used by an EDA-based Our evaluation shows that Node.cure is effective, broadly applicable, and offers strong security guarantees. -
Maximizing the Performance of Scientific Data Transfer By
Maximizing the Performance of Scientific Data Transfer by Optimizing the Interface Between Parallel File Systems and Advanced Research Networks Nicholas Millsa,∗, F. Alex Feltusb, Walter B. Ligon IIIa aHolcombe Department of Electrical and Computer Engineering, Clemson University, Clemson, SC bDepartment of Genetics and Biochemistry, Clemson University, Clemson, SC Abstract The large amount of time spent transferring experimental data in fields such as genomics is hampering the ability of scientists to generate new knowledge. Often, computer hardware is capable of faster transfers but sub-optimal transfer software and configurations are limiting performance. This work seeks to serve as a guide to identifying the optimal configuration for performing genomics data transfers. A wide variety of tests narrow in on the optimal data transfer parameters for parallel data streaming across Internet2 and between two CloudLab clusters loading real genomics data onto a parallel file system. The best throughput was found to occur with a configuration using GridFTP with at least 5 parallel TCP streams with a 16 MiB TCP socket buffer size to transfer to/from 4{8 BeeGFS parallel file system nodes connected by InfiniBand. Keywords: Software Defined Networking, High Throughput Computing, DNA sequence, Parallel Data Transfer, Parallel File System, Data Intensive Science 1. Introduction of over 2,500 human genomes from 26 populations have been determined (The 1000 Genomes Project [3]); genome Solving scientific problems on a high-performance com- sequences have been produced for 3,000 rice varieties from puting (HPC) cluster will happen faster by taking full ad- 89 countries (The 3000 Rice Genomes Project [4]). These vantage of specialized infrastructure such as parallel file raw datasets are but a few examples that aggregate into systems and advanced software-defined networks.