Grid Computing seminars report

[seminar surveyer]

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ABSTRACT
Grid computing, emerging as a new paradigm for next-generation computing, enables the sharing, selection and aggregation of geographically distributed heterogeneous resources for solving large scale problems in science, engineering, and commerce. The resources in the grid are heterogeneous and geographically distributed. Availability, usage and cost policies vary depending on the particular user, time, priorities and goals. It enables the regulation of supply and demand for resource; provides and incentive for resource owners who participate in the grid; and motivates the users to trade of between deadline, budget, and the required level of quantity – of –service. A grid is a collection of mechanics, sometimes referred to as “nodes”, “resources”, “members”, “donors”, “clients”, “host”, “engines” and many other such terms. They all contribute any combination of resources to the grid as a whole. Some resources may be used by all users of the grid while others may have specific restrictions. IT budgets are declining and data continues to grow at an exponential rate. SAS applications with high volumes of data can take


many hours or possibly days or even weeks to complete. In some cases, a job is so big that it
cannot be completed at all even given today’s processor speeds. Whether you call it grid computing or not, you want to be able to complete your SAS applications in a reasonable amount of time without making a huge investment in new hardware.

OVERVIEW
 What is grid?
 Grid infrastructure requirements.
 Types of grid
 Grid components and services
 Applications
 Grid computing standards
 Security
 Future trends
 Future direction for SAS & Grid computing
 Case studies
 Conclusion

WHAT IS A GRID?
Advances in computer technology, including ever more powerful hardware and increasingly sophisticated software, have made it possible to apply computers to solving a wide range of complex problems in the fields of science, engineering, and business. There are still any numbers of problems that are beyond the capabilities of the current generation of supercomputers, however. Furthermore, the nature of these problems often requires access to resources not often found on a single computer. Grid computing provides one type of solution to these issues.
The original purpose behind Grid computing was to page link together supercomputers spread across wide distances, but the aims have since moved beyond this scope. The term Grid was coined as an analogy with the power grid, supplying consistent, dependable, and transparent access to an electrical supply. Grid computing is intended to provide an equally consistent, dependable, and transparent collection of computing resources.
A Grid comprises a network of resources, each of which operates autonomously under local, control, but which collaborate and communicate with each other. In this respect, a Grid differs from other architectures, such as a cluster where distributed resources are typically owned and managed by a centralized resource management and scheduling system (all users of a cluster connect through a centralized system that allocates resources to tasks).
Grids can be constructed using entire clusters as nodes in the Grid, together with other localized low-level middleware systems. Grids can additionally make use of other distributed paradigms; the Globus OGSI* (Open Grid Services Infrastructure) is based on Web services.

Grid Infrastructure Requirements
A key precept of the Grid paradigm is that Grids should be transparent and seamless. Users: Applications and services should be able to view the Grid as a single virtual computer. Grid architectures are based on resource brokers, resolves, and other pieces of Grid middleware that perform resource discovery, scheduling, and processing of jobs.
In order to maintain the seamless nature of a Grid, any architecture must consider a number of issues, including the following:
 The need to respect the local autonomy of the various administrative domains that comprise the Grid. The systems linked together will be managed by local administrators who must be allowed to implement their own security policies and protect their own resources as they see fit.
 The different computing resources will inevitably span a variety of heterogeneous hardware.
 An appreciation of the dynamic nature of the Grid. Computers may join or leave the Grid at any time. The architecture implemented by the Grid must be scalable, supporting anything from a small number of nodes to thousands of computers, without imposing an overhead that degrades performance. .
 The importance of resilience. In any network, the chances of a single node failing increases as more and more nodes are added to the system. In a network involving many thousands of computers, it is likely that at least some computers will be offline. The Grid must be able to adapt dynamically, maintaining an up-to-date catalog of available resources.
 A Grid-must is non-intrusive to applications, services, and users not making use of it. There should be no observable degradation in service to local users accessing a computer that is also part of a Grid. This goal can be accomplished by careful scheduling of Grid tasks, and by ensuring that those tasks execute at a suitably low priority.


TYPES OF GRID
Many grid implementations are oriented towards supplying specific types of resources. Grids can be categorized according to these resources. The most common types of grid are
 Computational Grids: It provides resources for executing tasks, using spare cpu cycles on networked computers. Grid tasks are often scheduled to run as background tasks, to be performed when no higher priority local jobs are being executed.
 Data grids: It provides secure access to, and management of, large distributed data sets. A data grid typically implements replication and catalogue services, giving the illusion that the entire data set is actually held on a single piece of data storage. The data is usually processed using a computational grid.
 Application grids: It extends the notions of computational and data grids to provide transparent access to remote libraries and applications. In many instances, they can be implemented using web services acting as facades for remote services in conjunction with UDDI (universal description, discovery, integration), proving location transparency.
Other types of grid are available, knowledge grids, for ex., provide services that use information to help solve particular problems using specific algorithms.

Grid Components and Services
A grid must be designed to provide services that hide the underlying differences between the computers in the network and present a single, unified view of the entire scheme:
Communications: A grid can comprise a variety of network technologies of varying quality, and it can implement many different protocols. The communications infra structure provides by a grid must be robust enough to handle and resolve communications failures between nodes, and it must support protocols that can transmit much diverse type of data in a reliable manner.
 Authentication and Authorization: In any networked environment, security is a complex issue. With grids, that complexity is particularly acute .grid security must interoperate with local security systems.

 Naming services and location Transparency: Resources must be identifiable and locatable. A single uniform name space that spans entire grid is essential.a grid- wide directory service such as grid index information services (GI IS) can combine views from multiple local catalogues, usually based on standard protocols such as LDAP (light weight directory access protocol).

 Distributed File System: Distributed applications executing on a Grid need access to data held in files that may be spread across a large number of computers. A distributed file system provides a single view of the data storage available throughout the Grid and makes the physical location of files transparent to applications accessing those files.

 Resource Management: Different network applications can have varying network flows, incorporating periods of high and low latency. A Grid must provide a sufficient quality of service to cater to these differing rates and to ensure resource availability whenever possible.

 Fault Tolerance: It is vital that Grids provide tools for monitoring, maintaining, and reconfiguring resources. These tools can be used to implement transparent failover in the event that a particular resource becomes unavailable.
The facilities of a Grid should be .easily accessible to users and administrators. It is common, therefore, to provide graphical interfaces that allow users to submit jobs and monitor tasks as they are executed by the Grid. The Internet supplies an ideal framework for providing access to remote services, due to the connectivity available and the portable nature of the interfaces that can be generated.

APPLICATIONS
Applications developed to take advantage of a Grid can be built using Grid-enabled tools and technologies. A Grid should provide the interfaces, libraries, utilities, and programming APIs to support the development effort required. Common tools and libraries for building Grid applications include High Performance C++ (HPC++) and the Message Passing Interface (MPI).
 Consist of user applications
 Can be constructed by services defined at any layer

GRIDCOMPUTINGSTANDARDS
The Globus Toolkit has emerged as the-de facto standard for grid middleware. The Globus Alliance conducts research and development to create fundamental technologies behind the Grid, which lets people share computing power, databases, and other on-line tools securely across corporate, institutional, and
geographic boundaries without sacrificing local autonomy. Globus has protocols to handle grid resource management. These are:
 Grid Resource Management Protocol (GRAM)
 Information Services: Monitoring and Discovery Service (MDS)
 Data Movement and management: Global Access to Secondary Storage (GASS)
 Grid FTP

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