Cloud Computing

Cloud Computing
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10 minute read

We describe the central role of Parallel computing in Clouds and Big Data which is decomposed into lots of Little data running in individual cores. Many examples are given and it is stressed that issues in parallel computing are seen in day to day life for communication, synchronization, load balancing and decomposition. Cyberinfrastructure for e-moreorlessanything or moreorlessanything-Informatics and the basics of cloud computing are introduced. This includes virtualization and the important as a Service components and we go through several different definitions of cloud computing.

Gartner’s Technology Landscape includes hype cycle and priority matrix and covers clouds and Big Data. Two simple examples of the value of clouds for enterprise applications are given with a review of different views as to nature of Cloud Computing. This IaaS (Infrastructure as a Service) discussion is followed by PaaS and SaaS (Platform and Software as a Service). Features in Grid and cloud computing and data are treated. We summarize the 21 layers and almost 300 software packages in the HPC-ABDS Software Stack explaining how they are used.

Cloud (Data Center) Architectures with physical setup, Green Computing issues and software models are discussed followed by the Cloud Industry stakeholders with a 2014 Gartner analysis of Cloud computing providers. This is followed by applications on the cloud including data intensive problems, comparison with high performance computing, science clouds and the Internet of Things. Remarks on Security, Fault Tolerance and Synchronicity issues in cloud follow. We describe the way users and data interact with a cloud system. The Big Data Processing from an application perspective with commercial examples including eBay concludes section after a discussion of data system architectures.

Parallel Computing (Outdated)

We describe the central role of Parallel computing in Clouds and Big Data which is decomposed into lots of ‘‘Little data’’ running in individual cores. Many examples are given and it is stressed that issues in parallel computing are seen in day to day life for communication, synchronization, load balancing and decomposition.

Presentation Parallel Computing (33)

Decomposition

We describe why parallel computing is essential with Big Data and distinguishes parallelism over users to that over the data in problem. The general ideas behind data decomposition are given followed by a few often whimsical examples dreamed up 30 years ago in the early heady days of parallel computing. These include scientific simulations, defense outside missile attack and computer chess. The basic problem of parallel computing – efficient coordination of separate tasks processing different data parts – is described with MPI and MapReduce as two approaches. The challenges of data decomposition in irregular problems is noted.

Parallel Computing in Society

This lesson from the past notes that one can view society as an approach to parallel linkage of people. The largest example given is that of the construction of a long wall such as that (Hadrian’s wall) between England and Scotland. Different approaches to parallelism are given with formulae for the speed up and efficiency. The concepts of grain size (size of problem tackled by an individual processor) and coordination overhead are exemplified. This example also illustrates Amdahl’s law and the relation between data and processor topology. The lesson concludes with other examples from nature including collections of neurons (the brain) and ants.

Parallel Processing for Hadrian’s Wall

This lesson returns to Hadrian’s wall and uses it to illustrate advanced issues in parallel computing. First We describe the basic SPMD – Single Program Multiple Data – model. Then irregular but homogeneous and heterogeneous problems are discussed. Static and dynamic load balancing is needed. Inner parallelism (as in vector instruction or the multiple fingers of masons) and outer parallelism (typical data parallelism) are demonstrated. Parallel I/O for Hadrian’s wall is followed by a slide summarizing this quaint comparison between Big data parallelism and the construction of a large wall.

Resources

Introduction

We discuss Cyberinfrastructure for e-moreorlessanything or moreorlessanything-Informatics and the basics of cloud computing. This includes virtualization and the important ‘as a Service’ components and we go through several different definitions of cloud computing.Gartner’s Technology Landscape includes hype cycle and priority matrix and covers clouds and Big Data. The unit concludes with two simple examples of the value of clouds for enterprise applications. Gartner also has specific predictions for cloud computing growth areas.

Presentation Introduction (45)

Cyberinfrastructure for E-Applications

This introduction describes Cyberinfrastructure or e-infrastructure and its role in solving the electronic implementation of any problem where e-moreorlessanything is another term for moreorlessanything-Informatics and generalizes early discussion of e-Science and e-Business.

What is Cloud Computing: Introduction

Cloud Computing is introduced with an operational definition involving virtualization and efficient large data centers that can rent computers in an elastic fashion. The role of services is essential – it underlies capabilities being offered in the cloud. The four basic aaS’s – Software (SaaS), Platform (Paas), Infrastructure (IaaS) and Network (NaaS) – are introduced with Research aaS and other capabilities (for example Sensors aaS are discussed later) being built on top of these.

What and Why is Cloud Computing: Other Views I

This lesson contains 5 slides with diverse comments on ‘‘what is cloud computing’’ from the web.

Gartner’s Emerging Technology Landscape for Clouds and Big Data

This lesson gives Gartner’s projections around futures of cloud and Big data. We start with a review of hype charts and then go into detailed Gartner analyses of the Cloud and Big data areas. Big data itself is at the top of the hype and by definition predictions of doom are emerging. Before too much excitement sets in, note that spinach is above clouds and Big data in Google trends.

Simple Examples of use of Cloud Computing

This short lesson gives two examples of rather straightforward commercial applications of cloud computing. One is server consolidation for multiple Microsoft database applications and the second is the benefits of scale comparing gmail to multiple smaller installations. It ends with some fiscal comments.

Value of Cloud Computing

Some comments on fiscal value of cloud computing.

Resources

Software and Systems

We cover different views as to nature of architecture and application for Cloud Computing. Then we discuss cloud software for the cloud starting at virtual machine management (IaaS) and the broad Platform (middleware) capabilities with examples from Amazon and academic studies. We summarize the 21 layers and almost 300 software packages in the HPC-ABDS Software Stack explaining how they are used.

Presentation Software and Systems (32)

What is Cloud Computing

This lesson gives some general remark of cloud systems from an architecture and application perspective.

Introduction to Cloud Software Architecture: IaaS and PaaS I

We discuss cloud software for the cloud starting at virtual machine management (IaaS) and the broad Platform (middleware) capabilities with examples from Amazon and academic studies. We cover different views as to nature of architecture and application for Cloud Computing. Then we discuss cloud software for the cloud starting at virtual machine management (IaaS) and the broad Platform (middleware) capabilities with examples from Amazon and academic studies. We summarize the 21 layers and almost 300 software packages in the HPC-ABDS Software Stack explaining how they are used.

We discuss cloud software for the cloud starting at virtual machine management (IaaS) and the broad Platform (middleware) capabilities with examples from Amazon and academic studies. We cover different views as to nature of architecture and application for Cloud Computing. Then we discuss cloud software for the cloud starting at virtual machine management (IaaS) and the broad Platform (middleware) capabilities with examples from Amazon and academic studies. We summarize the 21 layers and almost 300 software packages in the HPC-ABDS Software Stack explaining how they are used.

Using the HPC-ABDS Software Stack

Using the HPC-ABDS Software Stack.

Resources

Architectures, Applications and Systems

We start with a discussion of Cloud (Data Center) Architectures with physical setup, Green Computing issues and software models. We summarize a 2014 Gartner analysis of Cloud computing providers. This is followed by applications on the cloud including data intensive problems, comparison with high performance computing, science clouds and the Internet of Things. Remarks on Security, Fault Tolerance and Synchronicity issues in cloud follow.

scroll: Architectures (64)

Cloud (Data Center) Architectures

Some remarks on what it takes to build (in software) a cloud ecosystem, and why clouds are the data center of the future are followed by pictures and discussions of several data centers from Microsoft (mainly) and Google. The role of containers is stressed as part of modular data centers that trade scalability for fault tolerance. Sizes of cloud centers and supercomputers are discussed as is “green” computing.

Analysis of Major Cloud Providers

Gartner 2014 Analysis of leading cloud providers.

Use of Dropbox, iCloud, Box etc.

Cloud Applications I

This short lesson discusses the need for security and issues in its implementation. Clouds trade scalability for greater possibility of faults but here clouds offer good support for recovery from faults. We discuss both storage and program fault tolerance noting that parallel computing is especially sensitive to faults as a fault in one task will impact all other tasks in the parallel job.

Science Clouds

Science Applications and Internet of Things.

Security

This short lesson discusses the need for security and issues in its implementation.

Comments on Fault Tolerance and Synchronicity Constraints

Clouds trade scalability for greater possibility of faults but here clouds offer good support for recovery from faults. We discuss both storage and program fault tolerance noting that parallel computing is especially sensitive to faults as a fault in one task will impact all other tasks in the parallel job.

Resources

Data Systems

We describe the way users and data interact with a cloud system. The unit concludes with the treatment of data in the cloud from an architecture perspective and Big Data Processing from an application perspective with commercial examples including eBay.

Presentation Data Systems (49)

The 10 Interaction scenarios (access patterns) I

The next 3 lessons describe the way users and data interact with the system.

The 10 Interaction scenarios. Science Examples

This lesson describes the way users and data interact with the system for some science examples.

Remaining general access patterns

This lesson describe the way users and data interact with the system for the final set of examples.

Video Access Patterns (11:36)

Data in the Cloud

Databases, File systems, Object Stores and NOSQL are discussed and compared. The way to build a modern data repository in the cloud is introduced.

Video Data in the Cloud (10:24)

Applications Processing Big Data

This lesson collects remarks on Big data processing from several sources: Berkeley, Teradata, IBM, Oracle and eBay with architectures and application opportunities.

Video Processing Big Data (8:45)

Resources

Last modified June 17, 2021 : add aliasses (6b7beab5)