1. Grid and Cloud Computing

2. Grid: Resource-Sharing Environment
Users:
1000s from 10s institutions
Well-established communities
Resources:
Computers, data, instruments, storage, applications
Owned/administered by institutions
Applications: data- and compute-intensive processing
Approach: common infrastructure

4. Grid: Definitions
Definition 1: Infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities (1998)
Definition 2: A system that coordinates resources not subject to centralized control, using open, general-purpose protocols to deliver nontrivial Quality of Service (2002)

5. Grid Computing
Grid computing is the ability to process information by utilizing a collection of networked heterogeneous information-processing components (hardware and software), all of which are provisioned from various geographical locations and across organizational boundaries.[5]

6. Cont.
In grid computing the concept of Virtual Organizations (VOs) rises. Which means that all resources were owned by a single organization.
Two key outcomes exist in grids:
The Open Grid Service Architecture (OGSA)
The Globus Toolkit.
OGSA means how grids are created and maintained.

7. Cont..
The Globus Toolkit is a software middleware package. All that is required is to install and configure Globus and then create all required resources and services.
grid security approach is the Grid Security Infrastructure (GSI) which has been implemented in
the Globus Toolkit

8. An Example: The Globus Toolkit
- Initially developed at Argonne National Lab/University of Chicago and ISI/University of Southern California

9. How It Started
While helping to build/integrate a diverse range of distributed applications, the same problems kept showing up over and over again.
Too hard to keep track of authentication data (ID/password) across institutions
Too hard to monitor system and application status across institutions
Too many ways to submit jobs
Too many ways to store & access files and data
Too many ways to keep track of data
Too easy to leave “dangling” resources lying around (robustness)

10. grid architecture in a nutshell

11. Forget Homogeneity!
Trying to force homogeneity on users is futile. Everyone has their own preferences, sometimes even dogma.
The Internet provides the model…

12. Cloud: just a new name for Grid?
Nevertheless YES:
Problems are the same in clouds and grids
Common need to manage large facilities
Define methods to discover, request and use resources
Implement highly parallel computations
Grid Computing, MIERSI, DCC/FCUP

13. Cloud: just a new name for Grid?
YES:
Reduce the cost of computing
Increase reliability
Increase flexibility (third party)
Grid Computing, MIERSI, DCC/FCUP

14. Cloud: just a new name for Grid?
NO:
Great increase demand for computing (clusters, high speed networks)
Billions of dollars being spent by Amazon, Google, Microsoft to create real commercial large-scale systems with hundreds of thousands of computers – shows computers with 100,000+ cores
Analysis of massive data
Grid Computing, MIERSI, DCC/FCUP

15. Clouds: side-by-side comparison with grids Resource management
Compute model
Grids: batch-scheduled (queueing systems)
Clouds: resources shared by all users at the same time (??!) in contrast to dedicated resources in queueing systems
Maybe one of the major challenges in clouds: QoS!
Grid Computing, MIERSI, DCC/FCUP

16. Clouds: side-by-side comparison with grids Resource management
Data model:
Grids: concept of virtual data, replica, metadata catalog, abstract structural representation
Data locality: to achieve good scalability data must be distributed over many computers
Clouds: use map-reduce mechanism like in Google to maintain data locality
Grids: rely on shared file systems (NFS, GPFS, PVFS, Lustre)
Grid Computing, MIERSI, DCC/FCUP

17. Clouds: side-by-side comparison with grids Resource management
Virtualization:
Abstraction and encapsulation
Clouds: rely heavily on virtualization
Grids: do not rely on virtualization as much as clouds. One example of use in Grids: Nimbus (previous Virtual Workspace Service)
Grid Computing, MIERSI, DCC/FCUP

18. Grid Projects
NAREGI ( National Research Grid Initiative) is a grid project that focuses on the research and development of grid middleware.
The test contains almost 3000 CPUs and is capable of 17 teraflops of processing power, offered from various research institutions throughout Japan.
BOINC is an Open-source software for volunteer computing and grid computing.
BOINC is supported by the National Science Climateprediction.net)

19. Grid vs Cloud
Neither grids nor clouds have a commonly accepted definition.
Grids are publicly funded and operated, whereas clouds are privately funded and operated.
Grids and clouds are instantiations of distributed systems, which is a common feature of them.
Grids evolve slowly and clouds evolve fast, and The level of expertise to use a cloud is significantly lower than that of a grids.