This document provides guidance on how to build a Linux cluster. It discusses that a cluster uses commodity hardware and open source software like Linux for high performance computing at a low price. It describes different types of clusters like Beowulf clusters for large-scale computing, and high availability clusters for non-stop services. The document outlines key considerations for building a cluster including implementing a single system image, using a global file system like NFS, cluster management software, and high-speed interconnects. It provides examples of specific clusters and software that support these cluster requirements.
This is the presentation on clusters computing which includes information from other sources too including my own research and edition. I hope this will help everyone who required to know on this topic.
This is the presentation on clusters computing which includes information from other sources too including my own research and edition. I hope this will help everyone who required to know on this topic.
AI&BigData Lab 2016. Сарапин Виктор: Размер имеет значение: анализ по требова...GeeksLab Odessa
4.6.16 AI&BigData Lab
Upcoming events: goo.gl/I2gJ4H
Как устроить анализ данных 40 млн. человек за 5 лет так, чтобы это выглядело почти в реальном времени.
Cluster computing is a type of computing where a group of several computers are linked together, allowing the entire group of computers to behave as if it were a single entity. There are a wide variety of different reasons why people might use cluster computing for various computer tasks. It s also used to make sure that a computing system will always be available. It is unknown when this cluster computing concept was first developed, and several different organizations have claimed to have invented it.
Dimension data cloud for the enterprise architectDavid Sawatzke
Dimension Data’s Cloud ranges from completely automated, self-provisioning public services to fully customisable, tailored private and hosted cloud services. Our Cloud services are anchored by our multivendor systems integration and a comprehensive consulting/IT outsourcing/managed services portfolio and our edge is that our Cloud services combine the automation and orchestration of public cloud offerings with the service delivery maturity developed over 30 years of IT services experience. With ongoing development and significiant R&D investment we continue to innovate and grow ourcloud services capabilities
Designing a Scalable Twitter - Patterns for Designing Scalable Real-Time Web ...Nati Shalom
Twitter is a good example for next generation real-time web applications, but building such an application imposes challenges such as handling an every growing volume of tweets and responses, as well as a large number of concurrent users, who continually *listen* for tweets from users (or topics) they follow. During this session we will review some of the key design principles addressing these challenges, including alternatives *NoSQL* alternatives and blackboard patterns. We will be using Twitter as a use case, while learning how to apply these to any real-time we application
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While virtualization technologies like Xen have been around for a long time, it is only in recent years that they have started to be targeted as viable systems for implementing middlebox processing (e.g., firewalls, NATs). But can they provide this functionality while yielding the high performance expected from hardware-based middlebox offerings? In this talk Joao Martins will introduce ClickOS, a tiny, MiniOS-based virtual machine tailored for network processing. In addition to the vm itself, Joao Martins will describe performance improvements done to the entire Xen I/O pipe. Finally, Joao Martins will discuss an evaluation showing that ClickOS can be instantiated in 30 msecs, can process traffic at 10Gb/s for almost all packet sizes, introduces delay of 40 microseconds and can run middleboxes at rates of 5 Mp/s.
The Why and How of HPC-Cloud Hybrids with OpenStack - Lev Lafayette, Universi...OpenStack
Audience Level
Intermediate
Synopsis
High performance computing and cloud computing have traditionally been seen as separate solutions to separate problems, dealing with issues of performance and flexibility respectively. In a diverse research environment however, both sets of compute requirements can occur. In addition to the administrative benefits in combining both requirements into a single unified system, opportunities are provided for incremental expansion.
The deployment of the Spartan cloud-HPC hybrid system at the University of Melbourne last year is an example of such a design. Despite its small size, it has attracted international attention due to its design features. This presentation, in addition to providing a grounding on why one would wish to build an HPC-cloud hybrid system and the results of the deployment, provides a complete technical overview of the design from the ground up, as well as problems encountered and planned future developments.
Speaker Bio
Lev Lafayette is the HPC and Training Officer at the University of Melbourne. Prior to that he worked at the Victorian Partnership for Advanced Computing for several years in a similar role.
Big Data Streams Architectures. Why? What? How?Anton Nazaruk
With a current zoo of technologies and different ways of their interaction it's a big challenge to architect a system (or adopt existed one) that will conform to low-latency BigData analysis requirements. Apache Kafka and Kappa Architecture in particular take more and more attention over classic Hadoop-centric technologies stack. New Consumer API put significant boost in this direction. Microservices-based streaming processing and new Kafka Streams tend to be a synergy in BigData world.
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
In search of the perfect IoT Stack - Scalable IoT Architectures with MQTTDominik Obermaier
Web-scale Internet of Things applications have one thing in common: They produce and process massive amounts of data. But how to design the next-generation IoT backend that is able to meet the business requirements and doesn’t explode as soon as the traffic increases? This presentation will cover how to use MQTT to connect millions of devices with commodity servers and process huge amounts of data. Learn all the common design patterns and see the technologies that actually scale. Explore when to use Cassandra, Kafka, Spark, Docker, and other tools and when to stick with your good ol’ SQL database or Enterprise Message Queue.
AI&BigData Lab 2016. Сарапин Виктор: Размер имеет значение: анализ по требова...GeeksLab Odessa
4.6.16 AI&BigData Lab
Upcoming events: goo.gl/I2gJ4H
Как устроить анализ данных 40 млн. человек за 5 лет так, чтобы это выглядело почти в реальном времени.
Cluster computing is a type of computing where a group of several computers are linked together, allowing the entire group of computers to behave as if it were a single entity. There are a wide variety of different reasons why people might use cluster computing for various computer tasks. It s also used to make sure that a computing system will always be available. It is unknown when this cluster computing concept was first developed, and several different organizations have claimed to have invented it.
Dimension data cloud for the enterprise architectDavid Sawatzke
Dimension Data’s Cloud ranges from completely automated, self-provisioning public services to fully customisable, tailored private and hosted cloud services. Our Cloud services are anchored by our multivendor systems integration and a comprehensive consulting/IT outsourcing/managed services portfolio and our edge is that our Cloud services combine the automation and orchestration of public cloud offerings with the service delivery maturity developed over 30 years of IT services experience. With ongoing development and significiant R&D investment we continue to innovate and grow ourcloud services capabilities
Designing a Scalable Twitter - Patterns for Designing Scalable Real-Time Web ...Nati Shalom
Twitter is a good example for next generation real-time web applications, but building such an application imposes challenges such as handling an every growing volume of tweets and responses, as well as a large number of concurrent users, who continually *listen* for tweets from users (or topics) they follow. During this session we will review some of the key design principles addressing these challenges, including alternatives *NoSQL* alternatives and blackboard patterns. We will be using Twitter as a use case, while learning how to apply these to any real-time we application
XPDS13: Enabling Fast, Dynamic Network Processing with ClickOS - Joao Martins...The Linux Foundation
While virtualization technologies like Xen have been around for a long time, it is only in recent years that they have started to be targeted as viable systems for implementing middlebox processing (e.g., firewalls, NATs). But can they provide this functionality while yielding the high performance expected from hardware-based middlebox offerings? In this talk Joao Martins will introduce ClickOS, a tiny, MiniOS-based virtual machine tailored for network processing. In addition to the vm itself, Joao Martins will describe performance improvements done to the entire Xen I/O pipe. Finally, Joao Martins will discuss an evaluation showing that ClickOS can be instantiated in 30 msecs, can process traffic at 10Gb/s for almost all packet sizes, introduces delay of 40 microseconds and can run middleboxes at rates of 5 Mp/s.
The Why and How of HPC-Cloud Hybrids with OpenStack - Lev Lafayette, Universi...OpenStack
Audience Level
Intermediate
Synopsis
High performance computing and cloud computing have traditionally been seen as separate solutions to separate problems, dealing with issues of performance and flexibility respectively. In a diverse research environment however, both sets of compute requirements can occur. In addition to the administrative benefits in combining both requirements into a single unified system, opportunities are provided for incremental expansion.
The deployment of the Spartan cloud-HPC hybrid system at the University of Melbourne last year is an example of such a design. Despite its small size, it has attracted international attention due to its design features. This presentation, in addition to providing a grounding on why one would wish to build an HPC-cloud hybrid system and the results of the deployment, provides a complete technical overview of the design from the ground up, as well as problems encountered and planned future developments.
Speaker Bio
Lev Lafayette is the HPC and Training Officer at the University of Melbourne. Prior to that he worked at the Victorian Partnership for Advanced Computing for several years in a similar role.
Big Data Streams Architectures. Why? What? How?Anton Nazaruk
With a current zoo of technologies and different ways of their interaction it's a big challenge to architect a system (or adopt existed one) that will conform to low-latency BigData analysis requirements. Apache Kafka and Kappa Architecture in particular take more and more attention over classic Hadoop-centric technologies stack. New Consumer API put significant boost in this direction. Microservices-based streaming processing and new Kafka Streams tend to be a synergy in BigData world.
Super, Mainframe computers are not cost effective
Cluster technology have been developed that allow multiple low cost computers to work in coordinated fashion to process applications.
In search of the perfect IoT Stack - Scalable IoT Architectures with MQTTDominik Obermaier
Web-scale Internet of Things applications have one thing in common: They produce and process massive amounts of data. But how to design the next-generation IoT backend that is able to meet the business requirements and doesn’t explode as soon as the traffic increases? This presentation will cover how to use MQTT to connect millions of devices with commodity servers and process huge amounts of data. Learn all the common design patterns and see the technologies that actually scale. Explore when to use Cassandra, Kafka, Spark, Docker, and other tools and when to stick with your good ol’ SQL database or Enterprise Message Queue.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
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1. How to Build Linux Cluster
High Performance Computing & Cluster Team
Linux One, Inc.
Lee, Bo-sung
2. What is Cluster?
High performance computers which is
composed of low price common computers
Using commodity devices, microprocessors,
network devices, etc.
Using open software such as Linux
High performance/low price
Easy to upgrade, highly expandable
3. Class of Cluster Computer
Beowulf Cluster
Developed for large scale computing, such as
aerodynamics, atmosphere, physics, etc.
Similar to MPP super computers
High Availability Cluster
Developed for non-stop services
Automatic fail-over
Web/Mail Cluster
Developed for fast internet services
4. Beowulf Cluster
First developed at 1994 in NASA
New trend in developing supercomputers
replace with high price vector supercomputers
Low price supercomputing is possible
high performance/low price processors
high speed network devices available
Numerous beowulf clusters developed
Used in various computational science fields
5. Avalon Cluster
- 140 Alpha Nodes (128 MB, 3GB)
- Alpha PC 164 LX Motherboard
- 128 MB SDRAM , 3GB Disk
- Linux RedHat 5.0
- 3Com Superstack II 3900
36-port Switch
- Cyclades Cyclom 32-YeP serial
concentrators
- 10 Gflops for $150k
- Submitted for the 1998 Gordon Bell
Price/Performance Prize with 70 Nodes
- Ranks at #113 on Top500
Supercomputers List (1998)
6. High Availability Cluster
Need of High Availability System
“Whatever can go wrong, will go wrong”
Fault Tolerant System
Specially designed, low volume, expensive hardware
High Availability System
Popular, high volume, cheaper hardware
8. Web Server Cluster
Support for large concurrent user's request
Support up to 100,000 concurrent request
E-commerce, cyber stock, etc.
High Performance and High Availability
Load balancing algorithm
Need large storage / DB server
Distributed file system ( e.g. CODA)
9. Web Server Cluster Concept
Load Balancer
Web Server 1
Web Server 4
Web Server 3
Web Server 2
100 Mbps Switch
File/DB
Server
RAID Storage
1 TB or 2 TB
(RAID Level 5)
SCS
I
Backborn Network
TCP/I
P
10. How to Build Linux Cluster
Cluster Requirements
SSI(Single System Image)
seen as single system to end user
File System Requirements
global file system with NFS
Cluster Management Software
need to manage as single system
High Speed Interconnection Network
Channel bonding / Gigabit / Myrinet / SAN
11. Single System Image
Operational Transparency
Single point of entry and control point
Single file hierarchy
Single virtual networking
Single memory space
Single job management / user interface
Availability Support
Single I/O space / process space
13. File System Requirements
Single file system is very hard to implement
GFS(Global File System)
Physically distributed, Logically single I/O space
Hard to implement
NFS(Network File System) is widely used
Slow, unsafe, and hard to manage
Strongly dependent on network performance
autofs make faster mount/umount NFS
Must be seen as single file system to end users
14. Cluster Management Tools
Management system as single workstation
Manage distributed user database ( passwd, group )
Single point software installation / uninstallation
Automatic system cloning and recovery
If one node fails, automatic recovery is essential
Propagation of system image to cluster node
System monitoring on control node
Smile CMS, bWatch, Ptools, etc.
16. High Speed Interconnection
Network
Number of cluster node increase, high speed
interconnection network is essential
Ethernet is popular but has some limitations
100 Mbps Ethernet is cheap but slow
Gigabit Ethernet will replace 100 Mbps sooner
TCP/IP has some limitations
Channel bonding
Myrinet / SAN / SCI will be used in special
cluster
17. High Speed Interconnection
Network
Gigabit
Need not special treatment in building cluster
For general cluster, gigabit is acceptable
Myrinet
Programmable and very fast interconnection network
For special cluster such as Beowulf cluster
Show poor performance in TCP/IP network
SCI / SAN
at present, very expensive
18. Cluster Related Software in
Linux
Autofs
automatic mount of file system
used in commercial cluster such as IBM SP2
rdist, rsync. cron
make cluster nodes identical, faster and efficient
time synchronization, update user data base
kernel patch for cluster system
Linux virtual server project, GFS, ip channel bonding
19. Conclusions
Linux cluster will be popular in various fields
High Performance Computing Fields
High Availability Server
High Performance Web/Mail Server
Linux is continuously enhanced
New package and tools are available
Need to develop software and tools for
clustering
Management, device drivers are need for cluster
