Foss-Based Grid-Computing
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Grid Computing: What Is It, and Why Do I Care?*
Grid Computing: What Is It, and Why Do I Care?* Ken MacInnis <[email protected]> * Or, “Mi caja es su caja!” (c) Ken MacInnis 2004 1 Outline Introduction and Motivation Examples Architecture, Components, Tools Lessons Learned and The Future Questions? (c) Ken MacInnis 2004 2 What is “grid computing”? Many different definitions: Utility computing Cycles for sale Distributed computing distributed.net RC5, SETI@Home High-performance resource sharing Clusters, storage, visualization, networking “We will probably see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country.” Len Kleinrock (1969) The word “grid” doesn’t equal Grid Computing: Sun Grid Engine is a mere scheduler! (c) Ken MacInnis 2004 3 Better definitions: Common protocols allowing large problems to be solved in a distributed multi-resource multi-user environment. “A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities.” Kesselman & Foster (1998) “…coordinated resource sharing and problem solving in dynamic, multi- institutional virtual organizations.” Kesselman, Foster, Tuecke (2000) (c) Ken MacInnis 2004 4 New Challenges for Computing Grid computing evolved out of a need to share resources Flexible, ever-changing “virtual organizations” High-energy physics, astronomy, more Differing site policies with common needs Disparate computing needs -
Clustering with Openmosix
Clustering with openMosix Maurizio Davini (Department of Physics and INFN Pisa) Presented by Enrico Mazzoni (INFN Pisa) Introduction • What is openMosix? – Single-System Image – Preemptive Process Migration – The openMosix File System (MFS) • Application Fields • openMosix vs Beowulf • The people behind openMosix • The openMosix GNU project • Fork of openMosix code 12/06/2003 HTASC 2 The openMosix Project MileStones • Born early 80s on PDP-11/70. One full PDP and disk-less PDP, therefore process migration idea. • First implementation on BSD/pdp as MS.c thesis. • VAX 11/780 implementation (different word size, different memory architecture) • Motorola / VME bus implementation as Ph.D. thesis in 1993 for under contract from IDF (Israeli Defence Forces) • 1994 BSDi version • GNU and Linux since 1997 • Contributed dozens of patches to the standard Linux kernel • Split Mosix / openMosix November 2001 • Mosix standard in Linux 2.5? 12/06/2003 HTASC 3 What is openMOSIX • Linux kernel extension (2.4.20) for clustering • Single System Image - like an SMP, for: – No need to modify applications – Adaptive resource management to dynamic load characteristics (CPU intensive, RAM intensive, I/O etc.) – Linear scalability (unlike SMP) 12/06/2003 HTASC 4 A two tier technology 1. Information gathering and dissemination – Support scalable configurations by probabilistic dissemination algorithms – Same overhead for 16 nodes or 2056 nodes 2. Pre-emptive process migration that can migrate any process, anywhere, anytime - transparently – Supervised by adaptive -
Load Balancing Experiments in Openmosix”, Inter- National Conference on Computers and Their Appli- Cations , Seattle WA, March 2006 0 0 5 4 9
Machine Learning Approach to Tuning Distributed Operating System Load Balancing Algorithms Dr. J. Michael Meehan Alan Ritter Computer Science Department Computer Science Department Western Washington University Western Washington University Bellingham, Washington, 98225 USA Bellingham, Washington, 98225 USA [email protected] [email protected] Abstract 2.6 Linux kernel openMOSIX patch was in the process of being developed. This work concerns the use of machine learning techniques (genetic algorithms) to optimize load 2.1 Load Balancing in openMosix balancing policies in the openMosix distributed The standard load balancing policy for openMosix operating system. Parameters/alternative algorithms uses a probabilistic, decentralized approach to in the openMosix kernel were dynamically disseminate load balancing information to other altered/selected based on the results of a genetic nodes in the cluster. [4] This allows load information algorithm fitness function. In this fashion optimal to be distributed efficiently while providing excellent parameter settings and algorithms choices were scalability. The major components of the openMosix sought for the loading scenarios used as the test load balancing scheme are the information cases. dissemination and migration kernel daemons. The information dissemination daemon runs on each 1 Introduction node and is responsible for sending and receiving The objective of this work is to discover ways to load messages to/from other nodes. The migration improve the openMosix load balancing algorithm. daemon receives migration requests from other The approach we have taken is to create entries in nodes and, if willing, carries out the migration of the the /proc files which can be used to set parameter process. Thus, the system is sender initiated to values and select alternative algorithms used in the offload excess load. -
HPC with Openmosix
HPC with openMosix Ninan Sajeeth Philip St. Thomas College Kozhencheri IMSc -Jan 2005 [email protected] Acknowledgements ● This document uses slides and image clippings available on the web and in books on HPC. Credit is due to their original designers! IMSc -Jan 2005 [email protected] Overview ● Mosix to openMosix ● Why openMosix? ● Design Concepts ● Advantages ● Limitations IMSc -Jan 2005 [email protected] The Scenario ● We have MPI and it's pretty cool, then why we need another solution? ● Well, MPI is a specification for cluster communication and is not a solution. ● Two types of bottlenecks exists in HPC - hardware and software (OS) level. IMSc -Jan 2005 [email protected] Hardware limitations for HPC IMSc -Jan 2005 [email protected] The Scenario ● We are approaching the speed and size limits of the electronics ● Major share of possible optimization remains with software part - OS level IMSc -Jan 2005 [email protected] Hardware limitations for HPC IMSc -Jan 2005 [email protected] How Clusters Work? Conventional supe rcomputers achieve their speed using extremely optimized hardware that operates at very high speed. Then, how do the clusters out-perform them? Simple, they cheat. While the supercomputer is optimized in hardware, the cluster is so in software. The cluster breaks down a problem in a special way so that it can distribute all the little pieces to its constituents. That way the overall problem gets solved very efficiently. - A Brief Introduction To Commodity Clustering Ryan Kaulakis IMSc -Jan 2005 [email protected] What is MOSIX? ● MOSIX is a software solution to minimise OS level bottlenecks - originally designed to improve performance of MPI and PVM on cluster systems http://www.mosix.org Not open source Free for personal and academic use IMSc -Jan 2005 [email protected] MOSIX More Technically speaking: ● MOSIX is a Single System Image (SSI) cluster that allows Automated Load Balancing across nodes through preemptive process migrations. -
Contributions to Desktop Grid Computing Gilles Fedak
Contributions to Desktop Grid Computing Gilles Fedak To cite this version: Gilles Fedak. Contributions to Desktop Grid Computing : From High Throughput Computing to Data-Intensive Sciences on Hybrid Distributed Computing Infrastructures. Calcul parallèle, distribué et partagé [cs.DC]. Ecole Normale Supérieure de Lyon, 2015. tel-01158462v2 HAL Id: tel-01158462 https://hal.inria.fr/tel-01158462v2 Submitted on 7 Dec 2015 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. Copyright University of Lyon Habilitation `aDiriger des Recherches Contributions to Desktop Grid Computing From High Throughput Computing to Data-Intensive Sciences on Hybrid Distributed Computing Infrastructures Gilles Fedak 28 Mai 2015 Apr`esavis de : Christine Morin Directeur de Recherche, INRIA Pierre Sens Professeur, Universit´eParis VI Domenico Talia Professeur, University of Calabria Devant la commission d'examen form´eede : Vincent Breton Directeur de Recherche, CNRS Christine Morin Directeur de Recherche, INRIA Manish Parashar Professeur, Rutgers University Christian Perez Directeur de Recherche, INRIA Pierre Sens Professeur, Universit´eParis VI Domenico Talia Professeur, University of Calabria Contents 1 Introduction 9 1.1 Historical Context . .9 1.2 Contributions . 13 1.3 Summary of the Document . 16 2 Evolution of Desktop Grid Computing 19 2.1 A Brief History of Desktop Grid and Volunteer Computing . -
Introduction Course Outline Why Does This Fail? Lectures Tutorials
Course Outline • Prerequisites – COMP2011 Data Organisation • Stacks, queues, hash tables, lists, trees, heaps,…. Introduction – COMP2021 Digital Systems Structure • Assembly programming • Mapping of high-level procedural language to assembly COMP3231/9201/3891/9283 language – or the postgraduate equivalent (Extended) Operating Systems – You are expected to be competent Kevin Elphinstone programmers!!!! • We will be using the C programming language – The dominant language for OS implementation. – Need to understand pointers, pointer arithmetic, explicit 2 memory allocation. Why does this fail? Lectures • Common for all courses (3231/3891/9201/9283) void func(int *x, int *y) • Wednesday, 2-4pm { • Thursday, 5-6pm *x = 1; *y = 2; – All lectures are here (EE LG03) – The lecture notes will be available on the course web site } • Available prior to lectures, when possible. void main() – The lecture notes and textbook are NOT a substitute for { attending lectures. int *a, *b; func(a,b); } 3 4 Tutorials Assignments • Assignments form a substantial component of • Start in week 2 your assessment. • A tutorial participation mark will • They are challenging!!!! – Because operating systems are challenging contribute to your final assessment. • We will be using OS/161, – Participation means participation, NOT – an educational operating system attendance. – developed by the Systems Group At Harvard – Comp9201/3891/9283 students excluded – It contains roughly 20,000 lines of code and comments • You will only get participation marks in your enrolled tutorial. 5 6 1 Assignments Assignments • Assignments are in pairs • Don’t under estimate the time needed to do the – Info on how to pair up available soon assignments. • We usually offer advanced versions of the – ProfQuotes: [About the midterm] "We can't keep you working assignments on it all night, it's not OS.“ Ragde, CS341 – Available bonus marks are small compared to amount of • If you start a couple days before they are due, you will be late. -
Resume Ivo Janssen
Ivo J. Janssen 13266 Kerrville Folkway Austin, TX 78729 (512) 750-9455 / [email protected] Objective To be part of a successful professional services team in a pre-sales and post-sales architecture and deployment role. Summary I'm an experienced, enthusiastic and skilled professional services consultant with experience in architecting and supporting large-scale enterprise software, with extensive experience in designing and implementing custom solutions as part of pre- and post sales support activities in diverse industry verticals across five continents. I'm as comfortable in designing and coding in an engineering role as I am in on-site planning, executing and troubleshooting customer deployments in a professional services role, as well as in participating in sales calls and drafting proposals in a sales engineering role. I'm able to adapt to new environments quickly and rapidly become proficient with new systems, tools and skills. I'm a good team player who thinks beyond the problem at hand instead of following the established paths in order to find a better solution that meets both current and future needs. Professional experience • Virtual Bridges , Austin, TX, USA (Nov 2010 – present) Senior Solution Architect o Solution architect for VDI product line. • Initiate Systems / IBM , Austin, TX, USA (Sep 2008 – Nov 2010) Senior Consultant o Senior implementation engineer for Healthcare sector of Master Data Management product line. o Responsibilities include requirements gathering, product installation and configuration, custom coding, connectivity scripting on Windows and Unix, database performance tuning, customer training workshops, pre/post-sales support. o Successfully architected, implemented and brought live custom implementation projects for major hospital systems and labs in the US, including customers with up to 250 million records (1TB database) connected to 20 auxiliary systems. -
Grid Computing in Research and Business Status and Direction
Unicore Summit, Sophia Antipolis Oct 11 – 12, 2005 Grid Computing In Research and Business Status and Direction Wolfgang Gentzsch, D-Grid and RENCI Unicore Summit Sophia Antipolis, October 11 – 12, 2005 Topics of the Day What is a Grid ? Why should we care about Grid ? Grid Examples: Research, Industry, Community 12 good reasons why grids are ready for research and early adopters in business Grid challenges and opportunities in business The future of Grid Computing Unicore Summit Sophia Antipolis, October 11 – 12, 2005 What is a Grid ? 1001 Definitions Distributed, networked computing & data resources Networking and computing infrastructure for utility computing Distributed platform for sharing scientific experiments and instruments The next generation of enterprise IT architecture The next generation of the Internet and the WWW Computing from the wall socket The Advanced Network …and 994 more… Unicore Summit Sophia Antipolis, October 11 – 12, 2005 What is a Grid ? 1001 Definitions It’s all about distributed, networked, shared resources in (virtual) organizations Unicore Summit Sophia Antipolis, October 11 – 12, 2005 Industry is on a Journey Old World New World Static Dynamic Silo Shared Physical Virtual Courtesy Mark Linesch, GGF Manual Automated Application Service Transitioning from Silo Oriented Architecture to Service Oriented Architecture Unicore Summit Sophia Antipolis, October 11 – 12, 2005 Example: Tele-Science Grid coordinated problem solving on dynamic and heterogeneous resource assemblies DATA ADVANCED ACQUISITION VISUALIZATION ,ANALYSIS QuickTime™ and a decompressor are needed to see this picture. COMPUTATIONAL RESOURCES IMAGING INSTRUMENTS LARGE-SCALE DATABASES Courtesy of Ellisman & Berman /UCSD&NPACI Unicore Summit Sophia Antipolis, October 11 – 12, 2005 Why should we care about Grids ? Three Examples Research Grid Industry Grid Community Grid Unicore Summit Sophia Antipolis, October 11 – 12, 2005 Grids for Research: NEES, Network for Earthquake Engineering Simulation NEESgrid links earthquake researchers across the U.S. -
The Utility Coprocessor: Massively Parallel Computation from the Coffee Shop
The Utility Coprocessor: Massively Parallel Computation from the Coffee Shop John R. Douceur, Jeremy Elson, Jon Howell, and Jacob R. Lorch Microsoft Research Abstract slow jobs that take several minutes without UCop be- UCop, the “utility coprocessor,” is middleware that come interactive (15–20 seconds) with it. Thanks to makes it cheap and easy to achieve dramatic speedups the recent emergence of utility-computing services like of parallelizable, CPU-bound desktop applications using Amazon EC2 [8] and FlexiScale [45], which rent com- utility computing clusters in the cloud. To make UCop puters by the hour on a moment’s notice, anyone with a performant, we introduced techniques to overcome the credit card and $10 can use UCop to speed up his own low available bandwidth and high latency typical of the parallel applications. networks that separate users’ desktops from a utility One way to describe UCop is that it effectively con- computing service. To make UCop economical and easy verts application software into a scalable cloud service to use, we devised a scheme that hides the heterogene- targeted at exactly one user. This goal entails five re- ity of client configurations, allowing a single cluster to quirements. Configuration transparency means the ser- serve virtually everyone: in our Linux-based prototype, vice matches the user’s application, library, and con- the only requirement is that users and the cluster are us- figuration state. Non-invasive installation means UCop ing the same major kernel version. works with a user’s existing file system and application This paper presents the design, implementation, and configuration. -
Legoos: a Disseminated, Distributed OS for Hardware Resource
LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation Yizhou Shan, Yutong Huang, Yilun Chen, and Yiying Zhang, Purdue University https://www.usenix.org/conference/osdi18/presentation/shan This paper is included in the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’18). October 8–10, 2018 • Carlsbad, CA, USA ISBN 978-1-939133-08-3 Open access to the Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation is sponsored by USENIX. LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation Yizhou Shan, Yutong Huang, Yilun Chen, Yiying Zhang Purdue University Abstract that can fit into monolithic servers and deploying them in datacenters is a painful and cost-ineffective process that The monolithic server model where a server is the unit often limits the speed of new hardware adoption. of deployment, operation, and failure is meeting its lim- We believe that datacenters should break mono- its in the face of several recent hardware and application lithic servers and organize hardware devices like CPU, trends. To improve resource utilization, elasticity, het- DRAM, and disks as independent, failure-isolated, erogeneity, and failure handling in datacenters, we be- network-attached components, each having its own con- lieve that datacenters should break monolithic servers troller to manage its hardware. This hardware re- into disaggregated, network-attached hardware compo- source disaggregation architecture is enabled by recent nents. Despite the promising benefits of hardware re- advances in network technologies [24, 42, 52, 66, 81, 88] source disaggregation, no existing OSes or software sys- and the trend towards increasing processing power in tems can properly manage it. -
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. -
The Grid: Past, Present, Future
1 The Grid: past, present, future Fran Berman,1 Geoffrey Fox,2 and Tony Hey3,4 1University of California, San Diego, California, 2Indiana University, Bloomington, Indiana, 3EPSRC, Swindon, United Kingdom, 4University of Southampton, Southampton, United Kingdom 1.1 THE GRID The Grid is the computing and data management infrastructure that will provide the elec- tronic underpinning for a global society in business, government, research, science and entertainment [1–5]. Grids idealized in Figure 1.1 integrate networking, communication, computation and information to provide a virtual platform for computation and data man- agement in the same way that the Internet integrates resources to form a virtual platform for information. The Grid is transforming science, business, health and society. In this book we consider the Grid in depth, describing its immense promise, potential and com- plexity from the perspective of the community of individuals working hard to make the Grid vision a reality. The Grid infrastructure will provide us with the ability to dynamically link together resources as an ensemble to support the execution of large-scale, resource-intensive, and distributed applications. Grid Computing – Making the Global Infrastructure a Reality, edited by F. Berman, G. Fox and T. Hey. 2002 John Wiley & Sons, Ltd. 10 FRAN BERMAN, GEOFFREY FOX, AND TONY HEY Data Advanced acquisition visualization Analysis Computational resources Imaging instruments Large-scale databases Figure 1.1 Managed digital resources as building blocks of the Grid. Large-scale Grids are intrinsically distributed, heterogeneous and dynamic. They pro- mise effectively infinite cycles and storage, as well as access to instruments, visualization devices and so on without regard to geographic location.