CARE Resource Broker (CRB)

1. CARE Resource Broker (CRB) Presented by G. Kannan Senior Research Associate CARE Project Madras Institute of Technology Campus, Anna University, Chennai kannan.gridlab@gmail.com Principal Investigator - CARE Project Dr. S. Thamarai Selvi Professor & Dean Madras Institute of Technology Campus, Anna University, Chennai stselvi@annauniv.edu, thamaraiselvis@gmail.com

2. CARE Resource Broker • Is a Grid Scheduler or Grid Metascheduler capable of • Scheduling jobs to physical resources • Creating virtual machines in a remote potential physical resource to meet the CPU requirement of an application • Creating Virtual Cluster in a remote potential physical resource to meet application’s platform requirement

3. Main Features of CRB • On the fly creation of execution environment using appropriate VM images • Dynamically create grid/cluster environment by automating globus installation and configuration • Can create virtual machine and attach it to a existing cluster

4. Motivation Application often requires number of CPUs that cannot be met by a single cluster Create virtual machines to meet the additional requirements of CPUs to execute the application Connect them to the selected cluster Application often requires a completely different software environment that no cluster in the grid can provide Create virtual clusters dynamically, deploy grid middleware, deploy necessary OS and software, execute the application Users CRB … Resource N Resource A

5. Layered Architecture

6. Layered Architecture Controller takes decision on scheduling strategies, initiates appropriate services to create VMs and Virtual Cluster,Selecting suitable resource for application execution. Monitors the status of physical and virtual resources, implements necessary services for creating virtual machines and virtual clusters, monitors application execution in it. These are services implemented in every physical resource for creating virtual clusters, VMs, and VM information aggregation

7. CRB in Action Submits jobs Request Handler Action Manager Scheduler decides which physical resources to deploy Virtual resource VRM Scheduler VRM maintains virtual resource information and initiates VCS and VMS to create virtual cluster and virtual machines in the remote physical resource Globus / Eucalyptus CRB Middleware VCS VMS Globus Aggregates Resource information Invokes VCS with number of CPUs needed and other contexts VCS VMS Middleware VCS VMS Miidleware VCS VMS Miidleware LRMS LRMS LRMS Guest OS Guest OS Guest OS Guest OS Guest OS Guest OS Host OS Host OS Host OS Guest OS Guest OS Guest OS Guest OS Guest OS Guest OS Guest OS Guest OS Guest OS CN CN CN CN CN CN CN CN CN

8. At Head Node … Request Handler Action Manager CRB service VRM Scheduler VCS VMS Globus Host Os Head Node of the selected cluster VMS VCS It makes necessary configuration such as cluster configuration, NFS, Grid middleware, (if needed), LRMS configuration Virtual resources get x509 certificate from CRB service (CRB) and jobs are submitted to it through Globus VCS selects potential compute nodes And boots Xen VM VM VM VM VM Compute Nodes Xen based Host OS Xen based Host Os Xen based Host OS Xen based Host OS

9. Resource Discovery • The resource brokering is purely depends on the resource ontology in which relationship between all concepts of Grid/Cloud domain is represented and established with the help of properties. • Resource Description – The descriptions should be added with resources for better discovery in a Grid/Cloud environment. • Resource Description Language (RDL) should follow the standards like Resource Description Framework (RDF) and Web Ontology Language (OWL) that has been used for Semantic web & Semantic Cloud as well. M.I.T, Anna Univ

10. Semantic in CRB

11. Semantic Description • The core component of the semantic component is Grid Resource Ontology template. • An ontology template is a domain specific ontology it provides hierarchy of concepts along with properties to define their characteristics. • Ontology is used for understanding the domain information. It describe the concepts in the domain and also relationships that grip between those concepts. • OWL (web ontology language) has been widely used for creating the ontology. M.I.T, Anna Univ

12. Ontology Template

13. CRB with Cloud Monitoring and Discovery Service (CMDS) User Request Semantic Knowledge Base Request Handler Service Semantic Discovery Service Response Cloud Information Updater Queuing & Scheduling Service CARE Resource Broker (CRB) Cloud Information Repository CMDA Adaptor Service Cloud Information Parser To Action Manager Service Grid Middleware Adaptor Service Cloud Information Aggregator Thread Cloud Controller Cloud Monitoring and Discovery Service (CMDS) Eucalyptus Cloud Middleware

14. Experimental Setup

15. Real World Application Execution • GROningen MAchine for Chemical Simulation (GROMACS)is a very powerful toolbox in modern molecular modeling. • It was originally developed at the University of Groningen, and it is mainly designed for testing of biochemical molecules like lipids, proteins and nucleic acids, which has lot of complex bonded interactions. • It is mainly used to understand the structure, dynamics and motion of individual atoms. • The two most commonly used methods are energy minimization and molecular dynamics that optimize the structure and simulate the natural motion of biological macromolecules. • It converts molecular coordinates from a Protein Data Bank (PDB) file into its internal format.

16. GROMACS SIMULATION PROCESS The whole simulation process consists of seven steps as given below: • Creation of topology files using Protein Data Bank (PDB) file • Solvating the protein • Energy Minimization • Equilibration run • Performing MD simulation • Viewing Trajectory files • Viewing MD simulation results

17. Visual Molecular Dynamics (VMD) Tool

18. GROMACS Simulation Output

19. Comparison of Application Execution Time of Jobs in Grid Versus Cloud Resources

20. CRB Features • Supports JSDL specification for job submission. • Provides a graphical user interface for job submission, monitoring and viewing resource information. • Semantic Description and Discovery of Grid and Cloud resources – solving interoperability problem. • Supports DAG, MPI and Batch jobs. • Creation of virtual cluster formation with either PBS or SGE as local resource manager in Grid as well as Cloud resources. • Its capability to create virtual machines on the fly will also improve the scalability. • This feature can also be applied to cloud resources while hosting a server application in which one has to increase the hardware resources dynamically depending on the need.

21. Future Extension • Service Level Agreement (SLA) • Heuristic Scheduling • Improving Scalability using P2P Overlay Network.

22. Acknowledgement • The authors sincerely thank the Ministry of Information & Communication Technology, Department of Information Technology, New Delhi, India for sponsoring Centre for Advanced Computing Research and Education (CARE).

23. Questions ?

24. Thank You