Grid Computing An Overview

1
Grid Computing - An Overview

• Michael P. Cummings
• Laboratory of Molecular Evolution
• Center for Bioinformatics and Computational
  Biology

2
Acknowledgments

• Core Middleware Development
• Adam Bazinet
• Daniel Myers
• John Fuetsch
• Stephen McLellan, Chris Milliron, Deji Akinyemi
• Semantic Web Grid Services/Workflows
• Sung Lee, Fujitsu Laboratories of America
• Nada Hashmi, UMIACS (now CBA, Saudi Arabia)
• David Wang, UMIACS

3
Outline

• Grid computing introduction and motivation
• Goals of The Lattice Project
• Basic architecture
• Our current production Grid system
• Implementation details
• Results of usage
• Research and development

4
Grid Computing A Definition

• A model of distributed computing that uses
  geographically and administratively disparate
  resources. In Grid computing, individual users
  can access computers and data transparently,
  without having to consider location, operating
  system, account administration, and other
  details. In Grid computing, the details are
  abstracted, and the resources are virtualized.

5
Grid Computing Characteristics

• Resources are heterogeneous
• Resources are administratively disparate
• Resources are geographically disparate
• Users do not have to worry about system details
  (e.g., location, operating system, accounts)

6
Grid Computing Advantages

• Provides increased resources for research
• Utilizes resources already purchased
• Space and HVAC needs already met
• Little increased administrative burden
• Economically and environmentally appealing

7
Types of Grid Middleware

• Heavyweight/feature rich (e.g., Globus Toolkit)
• Multiple users and multiple applications
• Mechanisms for authentication, authorization,
  communication, file access, resource discovery
  and specification
• Push model jobs are assigned to specific
  resources

8
Types of Grid Middleware

• Desktop Grids (e.g., Berkeley Open Infrastructure
  for Network computing BOINC)
• Single user and single application
• Limited features
• Pull model clients contact server for jobs

9
An Example SETI_at_home

• A scientific experiment that uses
  Internet-connected computers in the Search for
  Extraterrestrial Intelligence (SETI), a
  scientific effort seeking to determine if there
  is intelligent life outside Earth. The project
  analyzes radio signals to look for patterns that
  might be associated with intelligent life.

10
SETI_at_home statistics (Monday)

• Total participants 5,521,708
• Rate of signup a new participant every 96
  seconds
• Effective number of computers At any given
  moment there are the equivalent of gt412,000
  computers working full time
• Results received 2,200,991,756
• Total CPU time 2,555,681 years

11
Why Go Grid?

• To speed research
• Parallel execution means higher throughput
• To make compute resources commodities
• Analogous to the electrical power grid
• To foster efficiency and interaction in the
  research community
• Use of the Grid spans departments and domains
• Grid resources are typically shared resources

12
Outline

• Grid computing introduction and motivation
• Goals of The Lattice Project
• Basic architecture
• Our current production Grid system
• Implementation details
• Results of usage
• Research and development

13
The Lattice Project Initial Goals

• Develop a Grid system for research that
• Speeds up workflows by Grid-enabling various
  programs
• Is simple and intuitive
• Takes advantage of heterogeneous resources
• Is capable of managing large numbers of jobs
  (thousands)
• Supports multiple users and lowers the barriers
  to getting involved
• Is community-driven and supported

14
Principles of Design

• Make use of well supported open source software
• Globus Toolkit
• BOINC
• Condor
• Engineered software should be scalable, modular,
  and robust
• Expose programs as well-defined services
• Arbitrary user-supplied code cannot be run

15
Grid Development Challenges

• Many middleware systems are not compatible
• Middleware is cumbersome
• Developing a Grid service is often difficult

16
Outline

• Grid computing introduction and motivation
• Goals of The Lattice Project
• Basic architecture
• Our current production Grid system
• Implementation details
• Usage statistics
• Research and development

17
Terminology

• Client A Grid user interface OR a machine that
  performs computation
• Grid Service A Grid-enabled program
• Scheduler A program that decides where Grid jobs
  will run
• Resource Executes Grid jobs

18
Basic Architecture (1 of 3)
19
Basic Architecture (2 of 3)
20
Basic Architecture (3 of 3)
21
Outline

• Grid computing introduction and motivation
• Goals of The Lattice Project
• Basic architecture
• Our current production Grid system
• Implementation details
• Results of usage
• Research and development

22
Software Components

• Globus Toolkit version 3.2.1
• Backbone of the Grid
• http//www.globus.org/
• Condor-G
• Grid-level scheduler / resource broker
• http//www.cs.wisc.edu/condor/
• BOINC Berkeley Open Infrastructure for Network
  Computing
• SETI_at_home-style desktop grid
• http//boinc.berkeley.edu/
• Custom components
• GSBL, GSG, Globus-BOINC adaptor, MDS-matchmaking
  bridge, user interface(s), administrative
  scripts, and much more

23
Globus Toolkit 3

• Key components
• Globus Core
• Grid service hosting environment
• GSI Grid Security Infrastructure
• Uses public key cryptography
• Secures communication
• Authenticates and authorizes Grid users
• WS GRAM Job management
• GASS Point to point file transfer
• MDS2 Information provider

24
Condor-G

• Condor-G is part of the Condor suite
• Resources and jobs send Condor-G descriptions of
  themselves called ClassAds
• Condor-G matches Grid jobs to suitable resources,
  then submits and manages them
• This process is called matchmaking

25
BOINC

• Most novel feature of our Grid
• Public computing model
• Untrusted resources
• Potentially our largest resource
• We have targeted 3 platforms
• Windows / Linux x86 / Mac OS X

26
Our Current Grid System
27
User Interface

• The Grid Brick a machine used to submit Grid
  jobs
• Our primary interface for Grid users
• Command line clients mimic normal program
  execution
• Lattice Intranet
• Provides instructions for submitting jobs and
  managing data input and output
• Provides tools for describing and monitoring jobs
• Other possibilities
• Web portal model of job submission
• A client capable of composing complex workflows
  using Task Computing and Semantic Web technology
  developed by collaborators at Fujitsu

28
Basic Architecture Client/Service
29
Grid Client Stack
Command-line Interface
Perl
Java
Service-specific templates and stubs are
created by the Grid Service Generator
30
Grid Service Stack
Grid Service Hosting Environment, a.k.a. the
container
Java
Service-specific templates and stubs are
created by the Grid Service Generator
31
Tools for Writing Grid Services

• Grid Service Base Library (GSBL)
• Java API for building Grid services with the
  Globus Toolkit
• Shields programmers from having to work with the
  Globus API directly
• Provides a high-level interface for operations
  such as job submission and file transfer
• Grid Service Generator (GSG)
• Simplifies the process of creating Grid Services
• Intended for use with GSBL

32
GSBL Design and Features

• Classes for
• Clients and services (base classes)
• Argument description and processing
• File transfers
• Job submission and control
• Security configuration
• Java synchronization and Globus notifications to
  paper over event-based model

33
Grid Service Generator

• Deploying a Grid service with Globus is absurdly
  complicated
• Many files, namespaces lots of potential typos
• GSG takes as input a few parameters (service
  name, location, an XML argument description,
  etc.) and generates all requisite configuration
  files and skeleton Java classes

34
Grid Services
35
Grid Services

• Creating Grid Services requires
• Knowledge of the application
• Techniques for compiling and porting the
  application to various platforms
• Knowledge of the infrastructure so it can be
  effectively tested and deployed
• Challenges
• Maintaining bodies of Grid Service code as the
  number of applications grow and new versions of
  applications are released
• Minimizing the number of updates that need to be
  applied when the framework changes

36
Basic Architecture - Scheduling
37
Condor-G ClassAds

• Resources and jobs send Condor-G descriptions of
  themselves called ClassAds
• Jobs require certain capabilities of resources
• Resources advertise their capabilities
• Similar to a dating service central broker
  points pairs of compatible jobs/resources at each
  other

38
Condor G ClassAds
39
Generating ClassAds

• Job ClassAds are generated by the Condor-G job
  manager
• Job requirements are specified in the Grid
  service configuration files
• Resource ClassAds are generated by extracting
  information from MDS
• Lattice information providers supply data
  required for matchmaking

40
Monitoring and Discovery System (MDS2)

• Globus information services component
• LDAP-based (new version XML-based)
• Answers questions like
• What resources are available?
• What capabilities do these resources have?
• What is the load on these resources?
• This in turn allows for intelligent decisions to
  be made in areas such as scheduling and resource
  accounting

41
Basic Architecture - Resources
42
Current Grid Resources

• http//lattice.umiacs.umd.edu/resources/
• UMIACS Condor pool
• gt 400 processors
• BOINC pools
• Clients on campus gt 100
• Public (off-campus) clients gt 1000

43
BOINC

• Works on the pull model, that is
• One or more servers create workunits
• Clients connect asynchronously, pull down work,
  and return the results
• Clients are relatively lightweight and easy to
  install and manage
• One client can process work for multiple projects
• Participants can join teams and are given credit
  for the work they complete
• http//lattice.umiacs.umd.edu/boinc_public

44
Globus-BOINC Adapter

• Consists of a number of components that allow us
  to run Grid Services on BOINC
• BOINC job manager
• Custom validator and assimilator
• Registers BOINC with Globus as a GRAM-addressable
  resource
• BOINC compatibility library eases the process of
  porting applications to BOINC

45
Research Projects Using the Grid

• The Laboratory of David Fushman has run
  protein-protein docking algorithms on Lattice
• CNS is the primary Grid service in this project
• Floyd Reed and Holly Mortensen from the
  Laboratory of Sarah Tishkoff have run a number of
  population genetics analyses
• MDIV and IM are the primary Grid services
• The Laboratory of Molecular Evolution has run
  statistical phylogenetic analyses
• GSI is the primary Grid service

46
Results of Grid Usage

• IM 0.13 CPU years (BOINC)
• MDIV 4.93 CPU years (BOINC)
• CNS 12.4 CPU years (BOINC)
• GSI 94.05 CPU years (Condor)
• Total 111.51 CPU years
• BOINC participants in 21 countries

47
Outline

• Grid computing introduction and motivation
• Goals of The Lattice Project
• Basic architecture
• Our current production Grid system
• Implementation details
• Results of usage
• Research and development

48
GT4 Research and Development

• We are currently upgrading the Grid system to use
  Globus Toolkit 4.0
• GT4 adheres strictly to emerging and established
  Web service standards
• Actively developed and supported
• Many components have been greatly improved
• GridFTP/RFT (will replace GASS)
• WS GRAM
• MDS4 (XML based replaces MDS2, LDAP based)
• Our basic architecture remains the same, and the
  upgrade has been made easier because of tools we
  have already developed (GSBL, GSG)

49
More Information

• Lattice Website
• http//lattice.umiacs.umd.edu/