SSI-OSCAR: a Cluster Distribution for High Performance
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Time-Stamp Incremental Checkpointing and Its Application for an Optimization of Execution Model to Improve Performance of CAPE
https://doi.org/10.31449/inf.v42i3.2244 Informatica 42 (2018) 301–311 301 Time-stamp Incremental Checkpointing and its Application for an Optimization of Execution Model to Improve Performance of CAPE Van Long Tran Samovar, Télécom SudParis, CNRS, Université Paris-Saclay - 9 rue Charles Fourier, Évry, France E-mail: [email protected] and www.telecom-sudparis.eu Hue Industrial College - 70 Nguyen Hue street, Hue city, Vietnam E-mail: [email protected] and www.hueic.edu.vn Éric Renault Samovar, Télécom SudParis, CNRS, Université Paris-Saclay - 9 rue Charles Fourier, Évry, France E-mail: [email protected] and www.telecom-sudparis.eu Viet Hai Ha College of Education, Hue University - 34 Le Loi street, Hue city, Vietnam E-mail: [email protected] and www.dhsphue.edu.vn Xuan Huyen Do College of Sciences, Hue University - 77 Nguyen Hue street, Hue city, Vietnam E-mail: [email protected] and www.husc.edu.vn Keywords: OpenMP, OpenMP on cluster, CAPE, Checkpointing-Aided Parallel Execution, Checkpointing, Incremental checkpointing, DICKPT, TICKPT Received: March 29, 2018 CAPE, which stands for Checkpointing-Aided Parallel Execution, is a checkpoint-based approach to au- tomatically translate and execute OpenMP programs on distributed-memory architectures. This approach demonstrates high-performance and complete compatibility with OpenMP on distributed-memory systems. In CAPE, checkpointing is one of the main factors acted on the performance of the system. This is shown over two versions of CAPE. The first version based on complete checkpoints is too slow as compared to the second version based on Discontinuous Incremental Checkpointing. -
View Article(3467)
Problems of information technology, 2018, №1, 92–97 Kamran E. Jafarzade DOI: 10.25045/jpit.v09.i1.10 Institute of Information Technology of ANAS, Baku, Azerbaijan [email protected] COMPARATIVE ANALYSIS OF THE SOFTWARE USED IN SUPERCOMPUTER TECHNOLOGIES The article considers the classification of the types of supercomputer architectures, such as MPP, SMP and cluster, including software and application programming interfaces: MPI and PVM. It also offers a comparative analysis of software in the study of the dynamics of the distribution of operating systems (OS) for the last year of use in supercomputer technologies. In addition, the effectiveness of the use of CentOS software on the scientific network "AzScienceNet" is analyzed. Keywords: supercomputer, operating system, software, cluster, SMP-architecture, MPP-architecture, MPI, PVM, CentOS. Introduction Supercomputer is a computer with high computing performance compared to a regular computer. Supercomputers are often used for scientific and engineering applications that need to process very large databases or perform a large number of calculations. The performance of a supercomputer is measured in floating-point operations per second (FLOPS) instead of millions of instructions per second (MIPS). Since 2015, the supercomputers performing up to quadrillion FLOPS have started to be developed. Modern supercomputers represent a large number of high performance server computers, which are interconnected via a local high-speed backbone to achieve the highest performance [1]. Supercomputers were originally introduced in the 1960s and bearing the name or monogram of the companies such as Seymour Cray of Control Data Corporation (CDC), Cray Research over the next decades. By the end of the 20th century, massively parallel supercomputers with tens of thousands of available processors started to be manufactured. -
Optimization of Memory Management on Distributed Machine Viet Hai Ha
Optimization of memory management on distributed machine Viet Hai Ha To cite this version: Viet Hai Ha. Optimization of memory management on distributed machine. Other [cs.OH]. Institut National des Télécommunications, 2012. English. NNT : 2012TELE0042. tel-00814630 HAL Id: tel-00814630 https://tel.archives-ouvertes.fr/tel-00814630 Submitted on 17 Apr 2013 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ABCDBEFAD EBDDDFADD ABCDEF EEEFAABCDEFCAADDABCDDA FCF EFECFF !" #$!"B ! "!#$!%" EC%&EF'%(' C*F+EEA ADDCDD A F !"DDDD#$% AC!AD&F'F(CA ))DC !*ADD+, F DDCADAD AD. !*(/AD !F DDCADA0, 1ADC !*2D3 C !,FF DDCDAADDD!AD4CAD !*4A)D4 DDCDAA.5 !D*(D+,!(( !"DDDD#$%4! 2012TELE0042 ABCD ABACDEAFFEBBADDEABFAEABFBFDAEFE EEABEFACAABAFAFFFFBAEABBA ADEFBFAEAABEBAADAEE EBABAFDB !"EABAFBABAEA#AEF $%&EBAEADFEFBEBADEAEAF AADA#BABBA!ABAFAAEABEBAFEFDBFB#E FB$%&EBAFDDEBBAEBF ABBEAFB$%&EBAEFDDEBBAFEA'F ACDAEABF (AADBBAFBBAEAABFDDEBA DEABFFFBAEF#EBAEFABEA ABABFBAFFBBAA#AEF ABCDEEFABCABBBFADFEFD DFEFBDDBAFFBFBDDBF DABBBBDAFEBBDEA ACA DEBDAAFB ABBB!CDCFBBEDCEFEDB " BB C E -
Architectural Review of Load Balancing Single System Image
Journal of Computer Science 4 (9): 752-761, 2008 ISSN 1549-3636 © 2008 Science Publications Architectural Review of Load Balancing Single System Image Bestoun S. Ahmed, Khairulmizam Samsudin and Abdul Rahman Ramli Department of Computer and Communication Systems Engineering, University Putra Malaysia, 43400 Serdang, Selangor, Malaysia Abstract: Problem statement: With the growing popularity of clustering application combined with apparent usability, the single system image is in the limelight and actively studied as an alternative solution for computational intensive applications as well as the platform for next evolutionary grid computing era. Approach: Existing researches in this field concentrated on various features of Single System Images like file system and memory management. However, an important design consideration for this environment is load allocation and balancing that is usually handled by an automatic process migration daemon. Literature shows that the design concepts and factors that affect the load balancing feature in an SSI system are not clear. Result: This study will review some of the most popular architecture and algorithms used in load balancing single system image. Various implementations from the past to present will be presented while focusing on the factors that affect the performance of such system. Conclusion: The study showed that although there are some successful open source systems, the wide range of implemented systems investigated that research activity should concentrate on the systems that have already been proposed and proved effectiveness to achieve a high quality load balancing system. Key words: Single system image, NOWs (network of workstations), load balancing algorithm, distributed systems, openMosix, MOSIX INTRODUCTION resources transparently irrespective of where they are available[1].The load balancing single system image Cluster of computers has become an efficient clusters dominate research work in this environment. -
Distributed-Operating-Systems.Pdf
Distributed Operating Systems Overview Ye Olde Operating Systems OpenMOSIX OpenSSI Kerrighed Quick Preview Front Back Distributed Operating Systems vs Grid Computing Grid System User Space US US US US US US Operating System OS OS OS OS OS OS Nodes Nodes Amoeba, Plan9, OpenMosix, Xgrid, SGE, Condor, Distcc, OpenSSI, Kerrighed. Boinc, GpuGrid. Distributed Operating Systems vs Grid Computing Problems with the grid. Programs must utilize that library system. Usually requiring seperate programming. OS updates take place N times. Problems with dist OS Security issues – no SSL. Considered more complicated to setup. Important Note Each node, even with distributed operating systems, boots a kernel. This kernel can vary depending on the role of the node and overall architecture of the system. User Space Operating System OS OS OS OS OS OS Nodes Amoeba Andrew S. Tanenbaum Earliest documentation: 1986 What modern language was originally developed for use in Amoeba? Anyone heard of Orca? Sun4c, Sun4m, 386/486, 68030, Sun 3/50, Sun 3/60. Amoeba Plan9 Started development in the 1980's Released in 1992 (universities) and 1995 (general public). All devices are part of the filesystem. X86, MIPS, DEC Alpha, SPARC, PowerPC, ARM. Union Directories, basis of UnionFS. /proc first implemente d here. Plan9 Rio , the Plan9 window manager showing ”faces(1), stats(8), acme(1) ” and many more things. Plan9 Split nodes into 3 distinct groupings. Terminals File servers Computational servers Uses the ”9P” protocol. Low level, byte protocol, not block. Used from filesystems, to printer communication. Author: Ken Thompso n Plan9 / Amoeba Both Plan9 and Amoeba make User Space groupings of nodes, into specific categories. -
A Multiserver User-Space Unikernel for a Distributed Virtualization System
A Multiserver User-space Unikernel for a Distributed Virtualization System Pablo Pessolani Departamento de Ingeniería en Sistemas de Información Facultad Regional Santa Fe, UTN Santa Fe, Argentina [email protected] Abstract— Nowadays, most Cloud applications are developed application components began to be deployed in Containers. using Service Oriented Architecture (SOA) or MicroService Containers (and similar OS abstractions such as Jails [7] and Architecture (MSA). The scalability and performance of them Zones [8]) are isolated execution environments or domains is achieved by executing multiple instances of its components in in user-space to execute groups of processes. Although different nodes of a virtualization cluster. Initially, they were Containers share the same OS, they provide enough security, deployed in Virtual Machines (VMs) but, they required enough performance and failure isolation. As Containers demand computational, memory, network and storage resources to fewer resources than VMs [9], they are a good choice to hold an Operating System (OS), a set of utilities, libraries, and deploy swarms. the application component. By deploying hundreds of these Another option to reduce resource requirements is to use application components, the resource requirements increase a the application component embedded in a Unikernel [10, lot. To minimize them, usually small OSs with small memory footprint are used. Another way to reduce the resource 11]. A Unikernel is defined as “specialized, single-address- requirements is integrating the application components in a space machine image constructed by using library operating Unikernel. This article proposes a Unikernel called MUK, system” [12]. A Unikernel is a technology which integrates based on a multiserver OS, to be used as a tool to integrate monolithically network, storage, and file systems services Cloud application components. -
Facilitating Both Adoption of Linux Undergraduate Operating Systems Laboratories and Students’ Immersion in Kernel Code
SOFTICE: Facilitating both Adoption of Linux Undergraduate Operating Systems Laboratories and Students’ Immersion in Kernel Code Alessio Gaspar, Sarah Langevin, Joe Stanaback, Clark Godwin University of South Florida, 3334 Winter Lake Road, 33803 Lakeland, FL, USA [alessio | Sarah | joe | clark]@softice.lakeland.usf.edu http://softice.lakeland.usf.edu/ courses, frequent re-installations… Because of this, virtual Abstract machines, such as the one provided by the User Mode Linux (UML) project [4][5][6] are becoming more common as a This paper discusses how Linux clustering and virtual machine means to enable students to safely and conveniently tinker with technologies can improve undergraduate students’ hands-on kernel internals. Security concerns are therefore addressed and experience in operating systems laboratories. Like similar re-installation processes considerably simplified. However, one 1 projects, SOFTICE relies on User Mode Linux (UML) to potential problem still remains; we have been assuming all provide students with privileged access to a Linux system along the availability of Linux workstations in the classrooms. without creating security breaches on the hosting network. We Let’s consider an instructor is interested in a Linux-based extend such approaches in two aspects. First, we propose to laboratory at an institution using exclusively Windows facilitate adoption of Linux-based laboratories by using a load- workstations. Chances are that the classroom setup will be balancing cluster made of recycled classroom PCs to remotely assigned to the instructor or that new Linux-qualified personnel serve access to virtual machines. Secondly, we propose a new will be hired. In both cases, the adoption of such laboratories approach for students to interact with the kernel code. -
Operating Systems – the Code We Love to Hate
U.S. Department of Energy Office of Science Operating Systems – the Code We Love to Hate (Operating and Runtime Systems: Status, Challenges and Futures) Fred Johnson Senior Technical Manager for Computer Science Office of Advanced Scientific Computing Research DOE Office of Science Salishan – April 2005 1 U.S. Department of Energy The Office of Science Office of Science Supports basic research that underpins DOE missions. Constructs and operates large scientific facilities for the U.S. scientific community. Accelerators, synchrotron light sources, neutron sources, etc. Six Offices Basic Energy Sciences Biological and Environmental Research Fusion Energy Sciences High Energy Nuclear Physics Advanced Scientific Computing Research Salishan – April 2005 2 U.S. Department of Energy Simulation Capability Needs -- FY2005 Timeframe Office of Science Sustained Application Simulation Need Computational Significance Capability Needed (Tflops) Climate Calculate chemical balances Provides U.S. policymakers with Science in atmosphere, including > 50 leadership data to support policy clouds, rivers, and decisions. Properly represent and vegetation. predict extreme weather conditions in changing climate. Magnetic Optimize balance between > 50 Underpins U.S. decisions about future Fusion Energy self-heating of plasma and international fusion collaborations. heat leakage caused by Integrated simulations of burning electromagnetic turbulence. plasma crucial for quantifying prospects for commercial fusion. Combustion Understand interactions > 50 Understand detonation dynamics (e.g. Science between combustion and engine knock) in combustion turbulent fluctuations in systems. Solve the “soot “ problem burning fluid. in diesel engines. Environmental Reliably predict chemical > 100 Develop innovative technologies to Molecular and physical properties of remediate contaminated soils and Science radioactive substances. groundwater. Astrophysics Realistically simulate the >> 100 Measure size and age of Universe and explosion of a supernova for rate of expansion of Universe. -
ELASTICITY THANKS to KERRIGHED SSI and XTREEMFS Elastic Computing and Storage Infrastructure Using Kerrighed SSI and Xtreemfs
ELASTICITY THANKS TO KERRIGHED SSI AND XTREEMFS Elastic Computing and Storage Infrastructure using Kerrighed SSI and XtreemFS Alexandre Lissy1, St´ephane Lauri`ere2 1Laboratoire d’Informatique, Universit´ede Tours, 64 avenue Jean Portalis, Tours, France 2Mandriva, 8 rue de la Michodi`ere, Paris, France Julien Hadba Laboratoire d’Informatique, Universit´ede Tours, 64 avenue Jean Portalis, Tours, France Keywords: Kerrighed, Cloud, Infrastructure, Elastic, XtreemFS, Storage. Abstract: One of the major feature of Cloud Computing is its elasticity, thus allowing one to have a moving infrastructure at a lower cost. Achieving this elasticity is the job of the cloud provider, whether it is IaaS, PaaS or SaaS. On the other hand, Single System Image has a hotplug capability. It allows to “transparently” dispatch, from a user perspective, the workload on the whole cluster. In this paper, we study whether and how we could build a Cloud infrastructure, leveraging tools from the SSI field. Our goal is to provide, thanks to Kerrighed for the computing power aggregation and unified system view, some IaaS and to exploit XtreemFS capabilities to provide performant and resilient storage for the associated Cloud infrastructure. 1 INTRODUCTION age: SSIs are distributed systems running on top of a network of computers, that appear as one big unique When talking about Cloud, John Mc- computer to the user. Several projects aimed at pro- Carthy’s (Garfinkel, 1999) quotation at the MIT’s viding such a system. Among them, we can cite 100th year celebration is often used: “computation MOSIX (Barak and Shiloh, 1977), openMosix (Bar, may someday be organized as a public utility”. -
Storage Research at ORNL Sudharshan Vazhkudai R. Scott
Storage Research at ORNL Presentation to HEC-IWG Workshop Sudharshan Vazhkudai Network and Cluster Computing, CSMD R. Scott Studham National Center for Computational Sciences Contributors: Sarp Oral, Hong Ong, Jeff Vetter, John Cobb, Xiaosong Ma and Micah Beck OAK RIDGE NATIONAL LABORATORY U. S. DEPARTMENT OF ENERGY 1 Application Needs and User Surveys—Initial Observations • GYRO, POP, TSI, SNS • Most users have limited IO capability because the libraries and runtime systems are inconsistent across platforms. • Limited use of Parallel NetCDF or HDF5 − POP moving to P-NetCDF − SNS uses HDF5 • Seldom use of MPI-IO • Widely varying file size distribution − 1MB, 10MB, 100MB, 1GB, 10GB OAK RIDGE NATIONAL LABORATORY U. S. DEPARTMENT OF ENERGY 2 Current Storage Efforts for NLCF • Future procurements require support for center– wide file system • Minimize the need for users to move files around for post processing. • As most applications continue to do the majority of I/O from PE0 we are focused on the single client performance to the central pool. NLCF Center Wide Filesystem OAK RIDGE NATIONAL LABORATORY U. S. DEPARTMENT OF ENERGY 3 Using Xen to test scalability of Lustre to O(100,000) processors. SSI Software OpenSSI 1.9.1 Filesystem Lustre 1.4.2 Basic OS Linux 2.6.10 Virtualization Xen 2.0.2 Single System Image with process migration OpenSSI OpenSSI OpenSSI OpenSSI XenLinux XenLinux XenLinux XenLinux Linux 2.6.10 Linux 2.6.10 Linux 2.6.10 Linux 2.6.10 Lustre Lustre Lustre Lustre Xen Virtual Machine Monitor Hardware (SMP, MMU, physical memory, Ethernet, SCSI/IDE) OAK RIDGE NATIONAL LABORATORY U. -
SSI-OSCAR: a Distribution for High Performance Computing Using a Single System Image
1 SSI-OSCAR: a Distribution For High Performance Computing Using a Single System Image Geoffroy Vallée (INRIA / ORNL / EDF), Christine Morin (INRIA), Stephen L. Scott (ORNL), Jean-Yves Berthou (EDF), Hugues Prisker (EDF) OSCAR Symposium, May 2005 2 Context • Clusters: distributed architecture • difficult to use • difficult to manage • Different approaches • do everything manually • use software suite to simplify management and use (e.g. OSCAR) • This solution does not completely hide the resources distribution • use a Single System Image (SSI) • all resources are managed at the cluster scale • transparent for users and administrators • gives the illusion that a cluster is an SMP machine 3 What is a Single System Image? • SSI features ● Transparent resource management at the cluster level ● High Availability: tolerate all undesirable events that can occurs (node failure or eviction) ● Support of programming standards (e.g. MPI, OpenMP) ● High performance • A Solution: merge OSCAR and an SSI ● Simple to install ● Simple to use ● Collaboration INRIA / EDF / ORNL 4 SSI - Implementation • Key point: global resource management Limitations for functionalities User level: middle-ware and efficiency (e.g. CONDOR) Complex to develop Kernel level: OS and maintain (e.g. MOSIX, OpenSSI, Kerrighed) Hardware level More expensive (e.g. SGI) 5 Kerrighed – Overview • SSI developed in France (Rennes), INRIA/IRISA, in collaboration with EDF • Management at the cluster scale of • memories (through a DSM) • processes (through mechanisms for global process -
Downloaded on 2018-08-23T19:11:32Z Single System Image: a Survey
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Cork Open Research Archive Title Single system image: A survey Author(s) Healy, Philip D.; Lynn, Theo; Barrett, Enda; Morrisson, John P. Publication date 2016-02-17 Original citation Healy, P., Lynn, T., Barrett, E. and Morrison, J. P. (2016) 'Single system image: A survey', Journal of Parallel and Distributed Computing, 90- 91(Supplement C), pp. 35-51. doi:10.1016/j.jpdc.2016.01.004 Type of publication Article (peer-reviewed) Link to publisher's http://dx.doi.org/10.1016/j.jpdc.2016.01.004 version Access to the full text of the published version may require a subscription. Rights © 2016 Elsevier Inc. This is the preprint version of an article published in its final form in Journal of Parallel and Distributed Computing, available https://doi.org/10.1016/j.jpdc.2016.01.004. This manuscript version is made available under the CC BY-NC-ND 4.0 licence https://creativecommons.org/licenses/by-nc-nd/4.0/ Item downloaded http://hdl.handle.net/10468/4932 from Downloaded on 2018-08-23T19:11:32Z Single System Image: A Survey Philip Healya,b,∗, Theo Lynna,c, Enda Barretta,d, John P. Morrisona,b aIrish Centre for Cloud Computing and Commerce, Dublin City University, Ireland bComputer Science Dept., University College Cork, Ireland cDCU Business School, Dublin City University, Ireland dSoftware Research Institute, Athlone Institute of Technology, Ireland Abstract Single system image is a computing paradigm where a number of distributed computing resources are aggregated and presented via an interface that maintains the illusion of interaction with a single system.