DOCSLIB.ORG

Flood Prediction Model Simulation with Heterogeneous Trade-Offs in High Performance Computing Framework

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Flood Prediction Model Simulation with Heterogeneous Trade-Offs in High Performance Computing Framework FLOOD PREDICTION MODEL SIMULATION WITH HETEROGENEOUS TRADE-OFFS IN HIGH PERFORMANCE COMPUTING FRAMEWORK Antoni Portero Simone Libutti Radim Vavrik Giuseppe Massari Stepan Kuchar William Fornaciari Martin Golasowski Politecnico di Milano Vit Vondrak Dipartimento di Elettronica, IT4Innovations Informazione e Bioengegneria (DEIB) VSB-Technical University of Ostrava Milano, Italy Ostrava, Czech Republic Email: [email protected] Email: [email protected] KEYWORDS that need on-demand computation are emerging. Looking into the future, we might imagine event-driven and data-driven Hydrology model simulation; High Performance Comput- HPC applications running on demand to predict any kind of ing systems; disaster management; reliability models; com- event, e.g. running air pollution dispersion models at real time puting resource management; multi and many-cores systems; to predict hazardous substance dispersion caused by some parallel systems accident. Of course, as we build confidence in these emerging computations, they will move from the scientists workbench ABSTRACT into critical decision-making paths, but HPC clusters will still In this paper, we propose a safety-critical system with be needed to execute and analyse these simulations in a short a run-time resource management that is used to operate an time frame and they will have to provide the results in a application for flood monitoring and prediction. This applica- reliable way based on the specified operational requirements. tion can run with different Quality of Service (QoS) levels The intent of this paper is to describe the characteristics depending on the current hydrometeorological situation. and constraints of disaster management (DM) applications for industrial environments. The system operation can follow two main scenarios - stan- dard or emergency operation. The standard operation is active We therefore propose an HPC system running with a Run- when no disaster occurs, but the system still executes short- Time Resource Manager (RTRM) that monitors the healthiness term prediction simulations and monitors the state of the river of the platform. Our in-house disaster management application discharge and precipitation intensity. Emergency operation is called Floreon+ (Martinovic,ˇ Kuchar,ˇ Vondrak,´ Vondrak,´ Sˇ´ır & active when some emergency situation is detected or predicted Unucka 2010) is running on the system. The application can by the simulations. The resource allocation can either be used run with different Quality of Service (QoS) levels depending for decreasing power consumption and minimizing needed on the situation. Taking the current situation in mind, the resources in standard operation, or for increasing the precision resource allocation can be used either for decreasing power and decreasing response times in emergency operation. This consumption and minimizing needed resources in standard paper shows that it is possible to describe different optimal operation or increasing the precision and decreasing response points at design time and use them to adapt to the current times in emergency operation. Power consumption is a critical quality of service requirements during run-time. consideration in high performance computing systems and it is becoming the limiting factor to build and operate petascale INTRODUCTION and exascale systems in the future. When studying the power consumption of existing systems running HPC workloads, we Urgent computing (Beckman 2008) prioritises and provides find that power, energy and performance are closely related immediate access to supercomputers and grids for emergency leading to the possibility to optimize energy without sacrificing computation such as severe weather prediction during disaster performance. situations. For these urgent computations, late results are use- less results, because the decisions based on these results have This paper shows that it is possible to describe different op- to be made before the disaster happens and endangers human timal points at design time and use them to adapt to the current lives or property. As theHigh Performance Computing (HPC) QoS requirements during run-time. The proposed process can community builds increasingly realistic models, applications then be used to prepare an operational environment with high Proceedings 29th European Conference on Modelling and Simulation ©ECMS Valeri M. Mladenov, Petia Georgieva, Grisha Spasov, Galidiya Petrova (Editors) ISBN: 978-0-9932440-0-1 / ISBN: 978-0-9932440-1-8 (CD) availability and varying energy cost and model precision levels. the application’s behaviour based on the different ways the We manage to adapt the precision of the model by changing its system can be used in its over-all context, system scenarios input parameters and configuration, e.g. changing the number classify the behaviour based on the multi-dimensional cost of Monte-Carlo samples used for uncertainty modelling. The trade-off during the implementation (Gheorghita, Vandeputte, change of precision alters the model execution time and/or Bosschere, Palkovic, Hamers, Vandecappelle, Mamagkakis, the number of required computational resources, effectively Basten, Eeckhout, Corporaal & Catthoor 2009). changing the energy cost of the simulation. The decision to focus on the precision or energy cost is taken by the RTRM RTRM: Run-Time Resource Manager that computes the best-trade off for the current QoS. The RTRM (Run-Time Resource Manager) framework This paper is divided into seven sections. A section contain- (Bellasi, Massari & Fornaciari 2015) is the core of a highly ing the current state-of the art follows this introduction section. modular and extensible run-time resource manager which In section three, we introduce our driving disaster management provides support for an easy integration and management of example in the form of a rainfall-runoff uncertainty model. multiple applications competing on the usage of one (or more) Section four describes the run-time operating (RTRM) system shared many-core computation devices. The framework design, that monitors the sensors and knobs of the platform. Section which exposes different plug-in interfaces, provides support five shows the possible way of RTRM deployment in an for pluggable policies for both resource scheduling and the HPC environment. Section six presents the results of possible management of applications coordination and reconfiguration. optimal computation points that are obtained at design time for the described solution deployed on single computing node With RTRM, it is possible to make a suitable instrumen- and on multiple nodes. These optimal points are used by the tation to support Design-Space-Exploration (DSE) techniques, RTRM at run-time and the results show the performance and which could be used to profile application behaviour to either energy efficiency of the deployed solution. The final section optimize them at design time or support the identification provides a summary of the presented research and possible of optimal QoS requirement goals as well as their run-time future work. monitoring. Suitable platform abstraction layers, built on top of GNU/Linux kernel interfaces, allow an easy porting of the framework to different platforms and its integration with THE STATE OF THE ART specific execution environments. Elastic computing cloud (Galante & de Bona 2012) can The configuration of a run-time tunable application is provide thousands of virtual machine images rapidly and defined by a set of parameters. Some of them could impact the cost effectively. Unfortunately, one of the main drawbacks of application behaviour (e.g. the uncertainty of rainfall-runoff elastic computing is the application scalability due to computer models can produce different results for different scenarios) limited bandwidth communication. Another problem is the while other have direct impact on the amount of required feasibility of allocating resources and the infrastructure size resources (e.g. the amount of Monte-Carlo method samples that can be used on demand in case of emergency; sometimes, in uncertainty modelling and the time between simulation it cannot be determined fast enough. Therefore, one of the batches leads to different requirements for allocating system goals of the future HPC systems is to develop automated resources). frameworks that use power and performance knobs to make applications-aware energy optimizations during execution us- FLOOD MONITORING AND PREDICTION ing techniques like dynamic voltage and frequency scaling MODEL (DVFS) (Iraklis Anagnostopoulos 2013) for reducing the speed (clock frequency) in exchange for reduced power. Power gating The studied flood prediction model is a modular part technique then allows for the reduction of power consumption of the Floreon+ system (Martinovicˇ et al. 2010). The main by shutting off the current to blocks of the circuit that are objective of the Floreon+ system is to create a platform for not in use, in case that diverse computations have different integration and operation of monitoring, modelling, prediction power requirements. For example, when a CPU is waiting and decision support for disaster management. Modularity for resources or data, the frequency can be reduced to lower of the Floreon+ system allows for a simple integration of power consumption with minimal performance impact (Tiwari, different thematic areas, regions and data. The central thematic Laurenzano, Peraza, Carrington & Snavely 2012). area of the project is flood monitoring and prediction.
Load more

Recommended publications
  • Communicating Between the Kernel and User-Space in Linux Using Netlink Sockets
    SOFTWARE—PRACTICE AND EXPERIENCE Softw. Pract. Exper. 2010; 00:1–7 Prepared using speauth.cls [Version: 2002/09/23 v2.2] Communicating between the kernel and user-space in Linux using Netlink sockets Pablo Neira Ayuso∗,∗1, Rafael M. Gasca1 and Laurent Lefevre2 1 QUIVIR Research Group, Departament of Computer Languages and Systems, University of Seville, Spain. 2 RESO/LIP team, INRIA, University of Lyon, France. SUMMARY When developing Linux kernel features, it is a good practise to expose the necessary details to user-space to enable extensibility. This allows the development of new features and sophisticated configurations from user-space. Commonly, software developers have to face the task of looking for a good way to communicate between kernel and user-space in Linux. This tutorial introduces you to Netlink sockets, a flexible and extensible messaging system that provides communication between kernel and user-space. In this tutorial, we provide fundamental guidelines for practitioners who wish to develop Netlink-based interfaces. key words: kernel interfaces, netlink, linux 1. INTRODUCTION Portable open-source operating systems like Linux [1] provide a good environment to develop applications for the real-world since they can be used in very different platforms: from very small embedded devices, like smartphones and PDAs, to standalone computers and large scale clusters. Moreover, the availability of the source code also allows its study and modification, this renders Linux useful for both the industry and the academia. The core of Linux, like many modern operating systems, follows a monolithic † design for performance reasons. The main bricks that compose the operating system are implemented ∗Correspondence to: Pablo Neira Ayuso, ETS Ingenieria Informatica, Department of Computer Languages and Systems.
    [Show full text]
  • Mellanox Linux Switch †
    SOFTWARE PRODUCT BRIEF Mellanox Linux Switch † – Taking Open Ethernet to the next level, Mellanox Linux Switch provides users with the ability to deploy any standard Linux operating HIGHLIGHTS system on their switch devices – Mellanox Linux Switch enables users to natively install and use any standard Linux distribution as • 100% free open source software the switch operating system on the Open Ethernet Mellanox Spectrum® switch platforms. Mellanox Linux Switch is based on Switchdev, a Linux kernel driver model for Ethernet switches. Mellanox is • L2/L3 switch system as standard Linux the first switch vendor to embrace this model by implementing the switchdev driver for its Mellanox server Spectrum switches. This revolutionary concept breaks the dependency of using vendor-specific • Uniform Linux interfaces software development kits (SDK). Instead of proprietary APIs, fully standard Linux kernel interfaces are used to control the switch chip. This allows users to natively install and use any standard Linux • Fully supported by the Linux distribution as the switch operating system, while the switchdev driver ensures all network traffic is community seamlessly offloaded to the switch hardware. • Hardware independent abstraction layer Openness and Freedom • User choice of Linux operating The 100% free open-source Mellanox switchdev driver is developed and maintained as part of the systems and network applications Linux kernel and is promoted by the Linux community. There is no longer a need for closed code from switch vendors, no more binary blobs, and no need to sign a service level agreement (SLA). • Industry’s highest performance switch systems portfolio, including the high- Linux Switch provides users the flexibility to customize and optimize the switch to their exact needs density half-width Mellanox SN2100 without paying for expensive proprietary software that includes features they neither need nor will never use.
    [Show full text]
  • LPIC-2 Study Guide Second Edition
    LPIC-2 Study Guide Second Edition ffirs.indd 09/14/2016 Page i LPIC-2: Linux Professional Institute Certification Study Guide Exam 201 and Exam 202 Second Edition Christine Bresnahan Richard Blum ffirs.indd 09/14/2016 Page iii Senior Acquisitions Editor: Kenyon Brown Development Editor: Gary Schwartz Technical Editor: Kevin Ryan Production Editor: Christine O’Connor Copy Editor: Linda Rectenwald Editorial Manager: Mary Beth Wakefield Production Manager: Kathleen Wisor Executive Publisher: Jim Minatel Book Designers: Judy Fung and Bill Gibson Proofreader: Rebecca Rider Indexer: John Sleeva Project Coordinator, Cover: Brent Savage Cover Designer: Wiley Cover Image: Getty Images Inc./Jeremy Woodhouse Copyright © 2016 by John Wiley & Sons, Inc., Indianapolis, Indiana Published simultaneously in Canada ISBN: 978-1-119-15079-4 ISBN: 978-1-119-15081-7 (ebk.) ISBN: 978-1-119-15080-0 (ebk.) Manufactured in the United States of America No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hobo- ken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions.
    [Show full text]
  • Vorlage Für Dokumente Bei AI
    OSS Disclosure Document Date: 16-October-2017 BEG-VS OSS Licenses used in Alpine AS1 Project Page 1 Open Source Software Attributions for Alpine AS1 0046_170818 AI_PRJ_ALPINE_LINUX_17.0F17 This document is provided as part of the fulfillment of OSS license conditions and does not require users to take any action before or while using the product. © Bosch Engineering GmbH. All rights reserved, also regarding any disposal, exploitation, reproduction, editing, distribution, as well as in the event of applications for industrial property rights. OSS Disclosure Document Date: 16-October-2017 BEG-VS OSS Licenses used in Alpine AS1 Project Page 2 Table of content 1 Overview ............................................................................................................................................................. 12 2 OSS Licenses used in the project ......................................................................................................................... 12 3 Package details for OSS Licenses usage .............................................................................................................. 14 3.1 7 Zip - LZMA SDK ...................................................................................................................................... 14 3.2 ACL 2.2.51 ................................................................................................................................................... 14 3.3 Alsa Libraries 1.0.27.2 ................................................................................................................................
    [Show full text]
  • License Terms & Condition
    Date:7-June-2016 OSS Disclosure Document CM_CI1/EGM-P OSS Licenses used in GM-MY17 Project Page 1 1 Overview .................................................. 10 2 OSS Licenses used in the project .......................... 10 3 Package details for OSS Licenses usage .................... 11 3.1 7 Zip - LZMA SDK - 9.2/4.01 .................................. 11 3.2 ACL - 2.2.51 ................................................. 11 3.3 AES - Advanced Encryption Standard – 1.0 ..................... 11 3.4 Alsa Libraries - 1.0.27.2 .................................... 11 3.5 Alsa Plugins - 1.0.26 ........................................ 11 3.6 Alsa Utils - 1.0.27.2 ........................................ 12 3.7 APMD - 3.2.2 ................................................. 12 3.8 ATK - 2.8.0 .................................................. 12 3.9 Attr - 2.4.46 ................................................ 12 3.10 Audio File Library - 0.2.7 ................................. 12 3.11 Android - platform - bootable – recovery -4.2 .............. 12 3.12 Android - platform - system – core -4.2 .................... 12 3.13 Avahi - 0.6.31 ............................................. 13 3.14 Bash - 3.2.48 .............................................. 13 3.15 Bison with GPL 3.0 exception - 2.7.1 ....................... 13 3.16 Blktrace - 1.0.5 ........................................... 13 3.17 BlueZ - 4.101/5.15 ......................................... 13 3.18 Boost C++ Libraries- boost 1.50.0 .......................... 13 3.19 BPSTL .....................................................
    [Show full text]
  • Vorlage Für Dokumente Bei AI
    OSS Disclosure Document Date: 27-Apr-2018 CM-AI/PJ-CC OSS Licenses used in Suzuki Project Page 1 Table of content 1 Overview ..................................................................................................................... 11 2 OSS Licenses used in the project ................................................................................... 11 3 Package details for OSS Licenses usage ........................................................................ 12 3.1 7 Zip - LZMA SDK ............................................................................................................. 12 3.2 ACL 2.2.51 ...................................................................................................................... 12 3.3 Alsa Libraries 1.0.27.2 ................................................................................................... 12 3.4 AES - Advanced Encryption Standard 1.0 ......................................................................... 12 3.5 Alsa Plugins 1.0.26 ........................................................................................................ 13 3.6 Alsa Utils 1.0.27.2 ......................................................................................................... 13 3.7 APMD 3.2.2 ................................................................................................................... 13 3.8 Atomic_ops .................................................................................................................... 13 3.9 Attr 2.4.46 ...................................................................................................................
    [Show full text]
  • Software Fault Isolation with Api Integrity and Multi-Principal Modules
    Software Fault Isolation with Api Integrity and Multi-Principal Modules The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Yandong Mao, Haogang Chen, Dong Zhou, Xi Wang, Nickolai Zeldovich, and M. Frans Kaashoek. 2011. Software fault isolation with API integrity and multi-principal modules. In Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (SOSP '11). ACM, New York, NY, USA, 115-128. As Published http://dx.doi.org/10.1145/2043556.2043568 Publisher Association for Computing Machinery (ACM) Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/72580 Terms of Use Creative Commons Attribution-Noncommercial-Share Alike 3.0 Detailed Terms http://creativecommons.org/licenses/by-nc-sa/3.0/ Software fault isolation with API integrity and multi-principal modules Yandong Mao, Haogang Chen, Dong Zhou†, Xi Wang, Nickolai Zeldovich, and M. Frans Kaashoek MIT CSAIL, †Tsinghua University IIIS ABSTRACT complex, irregular kernel interfaces such as the ones found in the The security of many applications relies on the kernel being secure, Linux kernel and exploited by attackers. but history suggests that kernel vulnerabilities are routinely discov- Previous systems such as XFI [9] have used software isola- ered and exploited. In particular, exploitable vulnerabilities in kernel tion [26] to isolate kernel modules from the core kernel, thereby modules are common. This paper proposes LXFI, a system which protecting against a class of attacks on kernel modules. The chal- isolates kernel modules from the core kernel so that vulnerabilities lenge is that modules need to use support functions in the core in kernel modules cannot lead to a privilege escalation attack.
    [Show full text]
  • Istnanosat-1 Heart Processing and Digital Communications Unit
    ISTNanosat-1 Heart Processing and digital communications unit Joao˜ Andre´ Henriques Ferreira Dissertation submitted to obtain the Master Degree in Communication Networks Engineering Jury Chairman: Prof. Doutor Paulo Jorge Pires Ferreira Supervisor: Prof. Doutor Rui Manuel Rodrigues Rocha Co-Supervisor: Prof. Doutor Moises´ Simoes˜ Piedade Members: Prof. Doutor Mario´ Serafim dos Santos Nunes October 2012 Acknowledgments First of all, I would like to thank Professor Doutor Rui Manuel Rocha and Professor Doutor Moises´ Simoes˜ Piedade for giving me the opportunity to join the ISTNanosat project. The constant supervision from Professor Rui Rocha with his scientific background on embedded systems design and networking architectures allied with Professor Moises´ Piedade knowledge on electronics constraints and expected behaviours, were very useful during all project phases. I would also like to thank all the AMSAT-CT engineers for bringing me a lot of technical information on space related technology through very interesting discussions. I also want to highlight my colleagues on GEMS group, specially the Ph.D candidate Jose´ Catela for his useful knowledge and availability helping me on one of the implementation board programming and its details, sometimes until late evening. To all my course colleagues for the healthy acquaintanceship even during the long hard work nights, specially to Bruno Henriques for his valuable friendship since my first hour at IST. I’d like to thank my girlfriend Susana Rodrigues for her support and patience specially during the stress periods and to my grandparents for all the attention and affection. Finally, I want to express my deep thankfulness and gratitude to my parents for the unconditional support since the beginning.
    [Show full text]
  • Chapter 1 Starting with Linu Shells What Is Linux?
    - % >/J . >/ , I/# >/ , E# >/ . ! ,# >/ !"" C # . >/ !" ." , ; ! , # >/ / !"" . >/ ! > . C , >/ . " !. " .. . C" " ! >4 ?0 ,# >/ !,# !. % # # . >/ . . " ! !, /! ; ! , " . " . >/ " . ,# !"" ! = . " ", >/ "' ; >/ , ; ?0 1 #! , " 1! . I! . . !.! D >/ " I! . . C . ! #" . . # ! >/ " + 55 ; >/ " ; ! ! . " # . , # ! !" >/ " & ? ; ! . >/ " ; , ! . . !" " !# ! /!# . 7 . C .# >/ C " > ; > . !# . >/ , . 0 . :, : ! . 0/ " " # " " 1. # >/ , > !"" ! ## . "# ; " ! . !" # " & > !# ## ." . #"" ." 1# !# #""# ! , !" ! ; ". # > ! ! . "" ## " >C ! ! ## ! , ; " !! ! >/ , ! /! . D > !# , ! " . , , ; , " . " .!' & " "" "#" &. #" "#" : "#" = " "#" ; .# ! / ! . .! " # ) #) F . " .! . # " , "" "#" , "# ! "" ! ! "# "" "" ! / # ! , ! ##! ; , ! . "" ! !, . ." ! ! ! "" ; " , " "" ! / + - + 56 ; >/ " "" " ; "" ! # !, ! # ; , ! ! # . "" ! "" ! ; , " . "" # ! ! # ! "" ! # , ; , , !, . ! "" # "! ! "" # !! . . " ! +! ##- . C "" % #" !! "" # , " ", " . ! "" # .. "" # 7 # ." ! F ! , " ! # ! ; ! . # "" # . # ! ! . # >/ " # K ! ! . "" >/ " # ! . :C /" . " ' !"# $ %% & #' ()& *+' , +#% *+- ."# , +- ." *+- . , +- .# / +0 12 "% 12 !# 3)'
    [Show full text]
  • Resilient and Fast Persistent Container Storage Leveraging Linux’S Storage Functionalities Philipp Reisner, CEO LINBIT LINBIT - the Company Behind It
    Resilient and Fast Persistent Container Storage Leveraging Linux’s Storage Functionalities Philipp Reisner, CEO LINBIT LINBIT - the company behind it COMPANY OVERVIEW TECHNOLOGY OVERVIEW • Developer of DRBD • 100% founder owned • Offices in Europe and US • Team of 30 highly experienced Linux experts • Partner in Japan REFERENCES 31 Linux Storage Gems LVM, RAID, SSD cache tiers, deduplication, targets & initiators Linux's LVM logical volume snapshot logical volume Volume Group physical volume physical volume physical volume 31 Linux's LVM • based on device mapper • original objects • PVs, VGs, LVs, snapshots • LVs can scatter over PVs in multiple segments • thinlv • thinpools = LVs • thin LVs live in thinpools • multiple snapshots became efficient! 31 Linux's LVM thin-LV thin-LV thin-sLV LV snapshot thinpool VG PV PV PV 31 Linux's RAID RAID1 • original MD code • mdadm command A1 A1 • Raid Levels: 0,1,4,5,6,10 A2 A2 • Now available in LVM as well A3 A3 A4 A4 • device mapper interface for MD code • do not call it ‘dmraid’; that is software for hardware fake-raid • lvcreate --type raid6 --size 100G VG_name 31 SSD cache for HDD • dm-cache • device mapper module • accessible via LVM tools • bcache • generic Linux block device • slightly ahead in the performance game 31 Linux’s DeDupe • Virtual Data Optimizer (VDO) since RHEL 7.5 • Red hat acquired Permabit and is GPLing VDO • Linux upstreaming is in preparation • in-line data deduplication • kernel part is a device mapper module • indexing service runs in user-space • async or synchronous writeback • Recommended to be used below LVM 31 Linux’s targets & initiators • Open-ISCSI initiator IO-requests • Ietd, STGT, SCST Initiator Target data/completion • mostly historical • LIO • iSCSI, iSER, SRP, FC, FCoE • SCSI pass through, block IO, file IO, user-specific-IO • NVMe-OF • target & initiator 31 ZFS on Linux • Ubuntu eco-system only • has its own • logic volume manager (zVols) • thin provisioning • RAID (RAIDz) • caching for SSDs (ZIL, SLOG) • and a file system! 31 Put in simplest form DRBD – think of it as ..
    [Show full text]
  • The Sysfs Filesystem
    The sysfs Filesystem Patrick Mochel [email protected] Abstract sysfs is a core piece of kernel infrastructure, which means that it provides a relatively sim- ple interface to perform a simple task. Rarely sysfs is a feature of the Linux 2.6 kernel that al- is the code overly complicated, or the descrip- lows kernel code to export information to user tions obtuse. However, like many core pieces processes via an in-memory filesystem. The or- of infrastructure, it can get a bit too abstract ganization of the filesystem directory hierarchy and far removed to keep track of. To help al- is strict, and based the internal organization of leviate that, this paper takes a gradual approach kernel data structures. The files that are created to sysfs before getting to the nitty-gritty details. in the filesystem are (mostly) ASCII files with (usually) one value per file. These features en- First, a short but touching history describes its sure that the information exported is accurate origins. Then crucial information about mount- and easily accessible, making sysfs one of the ing and accessing sysfs is included. Next, most intuitive and useful features of the 2.6 ker- the directory organization and layout of sub- nel. systems in sysfs is described. This provides enough information for a user to understand the organization and content of the information that Introduction is exported through sysfs, though for reasons of time and space constraints, not every object and its attributes are described. sysfs is a mechanism for representing kernel objects, their attributes, and their relationships The primary goal of this paper is to pro- with each other.
    [Show full text]
  • The Effects of SSD Caching on the I/O Performance of Unified Storage Systems
    LA-UR-14-26016 The Effects of SSD Caching on the I/O Performance of Unified Storage Systems Unclassified Team Chartreuse Heidi Sandoval Matthew Dwyer Anthony Pearson California State Lynchburg College St. Cloud State University University LA-UR-14-26016 Outline ● Unified Storage ● SSD/Flash Caching ● Testbed ● Obstacles ● Conclusions ● Future Work Unclassified LA-UR-14-26016 Introduction ● The Lab is currently utilizing tape drives as its primary backup storage method ○ Slow and expensive ○ Will this continue to scale? ● This experiment tests a Unified Storage System with a layer SSD/Flash caching ○ Faster I/O performance ○ Enhanced fault tolerance Unclassified LA-UR-14-26016 Goals 1. Implement a Unified Storage System 2. Test the impact of SSD/Flash caching on the I/O performance of the Unified Storage System Unclassified LA-UR-14-26016 Unified Storage ● Combination of two different storage systems that creates a single integrated storage structure using: ○ Storage Area Network (SAN) ○ Cloud object storage 10 GigE Switch Unclassified LA-UR-14-26016 Storage Area Network (SAN) ● Block level protocols ● Communicates over Fibre Channel ○ Hardware used: ■ QLogic Corp. ISP2532 8Gb Fibre Channel ● Uses the Encapsulated SCSI protocol ○ Allows nodes to discover SCSI target devices ○ Software used: ■ targetCLI ● Enforces POSIX style file environment Unclassified LA-UR-14-26016 Cloud Object Storage ● Communicates over TCP/IP ○ Connected in a ring topology ○ Hardware used: ■ 10GigE Ethernet Switch ■ Mellanox MT26448 10GigE ■ Myricom Myri-10G ● Servers
    [Show full text]