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Web 2.0 for e-Science Environments

SKG2007Xi’an Hotel, Xi’an China

October 29 2007

Geoffrey Fox and Marlon PierceComputer Science, Informatics, Physics

Community Grids LaboratoryIndiana University Bloomington IN 47401

gcf@indiana.eduhttp://www.infomall.org

Applications, Infrastructure, Technologies

This field is confused by inconsistent use of terminology; I define Web Services, Grids and (aspects of) Web 2.0 (Enterprise 2.0) are

technologies Grids could be everything (Broad Grids implementing some sort

of managed web) or reserved for specific architectures like OGSA or Web Services (Narrow Grids)

These technologies combine and compete to build electronic infrastructures termed e-infrastructure or Cyberinfrastructure

e-moreorlessanything is an emerging application area of broad importance that is hosted on the infrastructures e-infrastructure or Cyberinfrastructure

e-Science or perhaps better e-Research is a special case of e-moreorlessanything

Relevance of Web 2.0 They say that Web 1.0 was a read-only Web while Web

2.0 is the wildly read-write collaborative Web Web 2.0 can help e-Science in many ways Its tools can enhance scientific collaboration, i.e.

effectively support virtual organizations, in different ways from grids

The popularity of Web 2.0 can provide high quality technologies and software that (due to large commercial investment) can be very useful in e-Science and preferable to Grid or Web Service solutions

The usability and participatory nature of Web 2.0 can bring science and its informatics to a broader audience

Web 2.0 can even help the emerging challenge of using multicore chips i.e. in improving parallel computing programming and runtime environments

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“Best Web 2.0 Sites” -- 2006 Extracted from http://web2.wsj2.com/ All important capabilities for e-Science Social Networking

Start Pages

Social Bookmarking

Peer Production News

Social Media Sharing

Online Storage (Computing)

Web 2.0, Grids and Web Services I Web Services have clearly defined protocols (SOAP) and a well

defined mechanism (WSDL) to define service interfaces• There is good .NET and Java support• The so-called WS-* specifications provide a rich sophisticated but

complicated standard set of capabilities for security, fault tolerance, meta-data, discovery, notification etc.

“Narrow Grids” build on Web Services and provide a robust managed environment with growing but still small adoption in Enterprise systems and distributed science (so called e-Science)

Web 2.0 supports a similar architecture to Web services but has developed in a more chaotic but remarkably successful fashion with a service architecture with a variety of protocols including those of Web and Grid services• Over 500 Interfaces defined at http://www.programmableweb.com/apis

Web 2.0 also has many well known capabilities with Google Maps and Amazon Compute/Storage services of clear general relevance

There are also Web 2.0 services supporting novel collaboration modes and user interaction with the web as seen in social networking sites, portals, MySpace, YouTube

Web 2.0 Systems like Grids have Portals, Services, Resources

Captures the incredible development of interactive Web sites enabling people to create and collaborate

Web 2.0, Grids and Web Services II I once thought Web Services were inevitable but this is no longer

clear to me Web services are complicated, slow and non functional

• WS-Security is unnecessarily slow and pedantic (canonicalization of XML)

• WS-RM (Reliable Messaging) seems to have poor adoption and doesn’t work well in collaboration

• WSDM (distributed management) specifies a lot There are de facto Web 2.0 standards like Google Maps and

powerful suppliers like Google/Microsoft which “define the architectures/interfaces”

One can easily combine SOAP (Web Service) based services/systems with HTTP messages but dominance of “lowest common denominator” suggests additional structure/complexity of SOAP will not easily survive

Distribution of APIs and Mashups per Protocol

REST SOAP XML-RPC REST,XML-RPC

REST,XML-RPC,

SOAP

REST,SOAP

JS Other

google google mapsmaps

netvibesnetvibes

live.comlive.com

virtual virtual earthearth

google google searchsearch

amazon S3amazon S3

amazon amazon ECSECS

flickrflickrebayebay

youtubeyoutube

411sync411syncdel.icio.usdel.icio.us

yahoo! searchyahoo! searchyahoo! geocodingyahoo! geocoding

technoratitechnorati

yahoo! imagesyahoo! imagestrynttrynt

yahoo! localyahoo! local

Number ofMashups

Number ofAPIs

SOAP is quite a small fraction

Where did Narrow Grids and Web Services go wrong? Too much Computing: historically one (including narrow grids) has tried to

increase computing capabilities by• Optimizing performance of codes at cost of re-usability• Exploiting all possible CPU’s such as Graphics co-processors and “idle

cycles” (across administrative domains)• Linking central computers together such as NSF/DoE/DoD

supercomputer networks without clear user requirements Next Crisis in technology area will be the opposite problem – commodity

chips will be 32-128way parallel in 5 years time and we currently have no idea how to use them – especially on clients• Only 2 releases of standard software (e.g. Office) in this time span

Interoperability Interfaces will be for data not for infrastructure• Google, Amazon, TeraGrid, European Grids will not interoperate at the

resource or compute (processing) level but rather at the data streams flowing in and out of independent Grid islands

• Data focus is consistent with Semantic Grid/Web but not clear if latter has learnt the usability message of Web 2.0

One needs to share computing, data, people in e-moreorlessanything, Grids initially focused on computing but data and people are more important

eScience is healthy as is e-moreorlessanything Most Grids are solving wrong problem at wrong point in stack with a

complexity that makes friendly usability difficult

Some Web 2.0 Activities at IU Use of Blogs, RSS feeds, Wikis etc. Use of Mashups for Cheminformatics Grid workflows Moving from Portlets to Gadgets in portals (or at least

supporting both) Use of Connotea to produce tagged document collections

such as http://www.connotea.org/user/crmc for parallel computing

Semantic Research Grid integrates multiple tagging and search systems and copes with overlapping inconsistent annotations

MSI-CIEC portal augments Connotea to tag a mix of URL and URI’s e.g. NSF TeraGrid use, PI’s and Proposals• Hopes to support collaboration (for Minority Serving

Institution faculty) Multicore SALSA project using for Parallel Programming 2.0

Use blog to create posts.

Display blog RSS feed in MediaWiki.

Semantic Research Grid (SRG) Integrates tagging and search system that allows users to use

multiple sites and consistently integrate them with traditional citation databases

We built a mashup linking to del.icio.us, CiteULike, Connotea allowing exchange of tags between sites and between local repositories

Repositories also link to local sources (PubsOnline) and Google Scholar (GS) and Windows Academic Live (WLA)• GS has number of cited publications. • WLA has Digital Object Identifier (DOI)

We implement a rather more powerful access control mechanism We build heuristic tools to mine “web lists” for citations We have an “event” based architecture (consistency model)

allowing change actions to be preserved and selectively changed• Supports integrating different inconsistent views of a given document and

its updates on different tagging systems

04/10/2312

MSI-CIEC Portal

MSI-CIECMinority Serving Institution CyberInfrastructure Empowerment Coalition

NSF Grants Tag System NSF has the ability to get information (in XML) on all of the

grants a particular person worked on We downloaded, parsed, and bookmarked this info using a

little scavenger robot.• Each grant is represented by a bookmark and tagged with

relevant information in MSI-CIEC Portal

• Grant tags point to URLs of the NSF award page. The investigators are imported as users Each has a bookmark for each project they worked on

• They are also represented in the tags of these projects. Can now form research collaborations by linking

researchers with common tags Hopefully will enable broader collaborations and not

just those between “usual suspects”

Superior (from broad usage) technologies of Web 2.0

Mash-ups can replace Workflow

Gadgets can replace Portlets

UDDI replaced by user generated registries

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Mashups v Workflow? Mashup Tools are reviewed at

http://blogs.zdnet.com/Hinchcliffe/?p=63 Workflow Tools are reviewed by Gannon and Fox

http://grids.ucs.indiana.edu/ptliupages/publications/Workflow-overview.pdf Both include scripting

in PHP, Python, sh etc. as both implement distributed programming at level of services

Mashups use all types of service interfaces and perhaps do not have the potential robustness (security) of Grid service approach

Mashups typically “pure” HTTP (REST)

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Grid Workflow Datamining in Earth Science Work with Scripps Institute Grid services controlled by scripting workflow process

real time data from ~70 GPS Sensors in Southern California

Streaming DataSupport

TransformationsData Checking

Hidden MarkovDatamining (JPL)

Display (GIS)

NASA GPS

Earthquake

Real Time

Archival

Grid Workflow Data Assimilation in Earth Science Grid services triggered by abnormal events and controlled by workflow process real

time data from radar and high resolution simulations for tornado forecasts

Typical graphical interface to service composition

Taverna another well known Grid/Web Service workflow tool

Recent Web 2.0 visual Mashup tools include Yahoo Pipes and Microsoft Popfly

Parallel Programming 2.0 Web 2.0 Mashups will (by definition the largest market)

drive composition tools for Grid, web and parallel programming

Parallel Programming 2.0 will build on Mashup tools like Yahoo Pipes and Microsoft Popfly

Yahoo Pipes

Web 2.0 Mashups and APIs

http://www.programmableweb.com/apis has (Sept 12 2007) 2312 Mashups and 511 Web 2.0 APIs and with GoogleMaps the most often used in Mashups

This is the Web 2.0 UDDI (service registry)

The List of Web 2.0 API’s

Each site has API and its features

Divided into broad categories

Only a few used a lot (49 API’s used in 10 or more mashups)

RSS feed of new APIs Google maps

dominates but Amazon S3 growing in popularity

Now to Portals2222

Grid-style portal as used in Earthquake GridThe Portal is built from portlets

– providing user interface fragments for each service that are composed into the full interface – uses OGCE technology as does planetary science VLAB portal with University of Minnesota

QuakeSim has a typical Grid technology portal

Such Server side Portlet-based approaches to portals are being challenged by client side gadgets from Web 2.0

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Portlets v. Google Gadgets Portals for Grid Systems are built using portlets with

software like GridSphere integrating these on the server-side into a single web-page

Google (at least) offers the Google sidebar and Google home page which support Web 2.0 services and do not use a server side aggregator

Google is more user friendly! The many Web 2.0 competitions is an interesting model

for promoting development in the world-wide distributed collection of Web 2.0 developers

I guess Web 2.0 model will win!

Note the many competitions powering Web 2.0 Mashup and Gadget Development

Typical Google Gadget Structure

… Lots of HTML and JavaScript </Content> </Module>Portlets build User Interfaces by combining fragments in a standalone Java ServerGoogle Gadgets build User Interfaces by combining fragments with JavaScript on the client

Google Gadgets are an example of Start Page Web 2.0 term for portals) technologySee http://blogs.zdnet.com/Hinchcliffe/?p=8

Web 2.0 can also help address long standing difficulties with

parallel programming environments

Too much computing addresses too much data andimplies need for multicore datamining algorithms

ClusteringPrincipal Component Analysis (SVD)

Expectation-Maximization EM (mixture models)Hidden Markov Models HMM

Multicore SALSA at CGL Service Aggregated Linked Sequential Activities

• http://www.infomall.org/multicore Aims to link parallel and distributed (Grid) computing by

developing parallel applications as services and not as programs or libraries• Improve traditionally poor parallel programming development

environments Can use messaging to link parallel and Grid services but

performance – functionality tradeoffs different• Parallelism needs few µs latency for message latency and thread

spawning

• Network overheads in Grid 10-100’s µs Developing set of services (library) of multicore parallel

data mining algorithms

Parallel Programming Model If multicore technology is to succeed, mere mortals must be able to build

effective parallel programs There are interesting new developments – especially the Darpa HPCS

Languages X10, Chapel and Fortress However if mortals are to program the 64-256 core chips expected in 5-7

years, then we must use today’s technology and we must make it easy• This rules out radical new approaches such as new languages

The important applications are not scientific computing but most of the algorithms needed are similar to those explored in scientific parallel computing• Intel RMS analysis

We can divide problem into two parts:• High Performance scalable (in number of cores) parallel kernels or

libraries• Composition of kernels into complete applications

We currently assume that the kernels of the scalable parallel algorithms/applications/libraries will be built by experts with a

Broader group of programmers (mere mortals) composing library members into complete applications.

Scalable Parallel Components There are no agreed high-level programming environments for

building library members that are broadly applicable. However lower level approaches where experts define

parallelism explicitly are available and have clear performance models.

These include MPI for messaging or just locks within a single shared memory.

There are several patterns to support here including the collective synchronization of MPI, dynamic irregular thread parallelism needed in search algorithms, and more specialized cases like discrete event simulation.

We use Microsoft CCR http://msdn.microsoft.com/robotics/ as it supports both MPI and dynamic threading style of parallelism• It already supports a Web 2.0 compatible service model DSS

Composition of Parallel Components The composition step has many excellent solutions as this does not

have the same drastic synchronization and correctness constraints as for scalable kernels• Unlike kernel step which has no very good solutions

Task parallelism in languages such as C++, C#, Java and Fortran90; General scripting languages like PHP Perl Python Domain specific environments like Matlab and Mathematica Functional Languages like MapReduce, F# HeNCE, AVS and Khoros from the past and CCA from DoE Web Service/Grid Workflow like Taverna, Kepler, InforSense KDE,

Pipeline Pilot (from SciTegic) and the LEAD environment built at Indiana University.

Web solutions like Mash-ups and DSS Many scientific applications use MPI for the coarse grain composition

as well as fine grain parallelism but this doesn’t seem elegant The new languages from Darpa’s HPCS program support task

parallelism (composition of parallel components) decoupling composition and scalable parallelism will remain popular and must be supported.

“Service Aggregation” in SALSA Kernels and Composition must be supported both inside

chips (the multicore problem) and between machines in clusters (the traditional parallel computing problem) or Grids.

The scalable parallelism (kernel) problem is typically only interesting on true parallel computers as the algorithms require low communication latency.

However composition is similar in both parallel and distributed scenarios and it seems useful to allow the use of Grid and Web 2.0 composition tools for the parallel problem. • This should allow parallel computing to exploit large

investment in service programming environments Thus in SALSA we express parallel kernels not as traditional

libraries but as (some variant of) services so they can be used by non expert programmers

For parallelism expressed in CCR, DSS represents the natural service (composition) model.

Inside the SALSA Services We generalize the well known CSP (Communicating

Sequential Processes) of Hoare to describe the low level approaches to fine grain parallelism as “Linked Sequential Activities” in SALSA.

We use term “activities” in SALSA to allow one to build services from either threads, processes (usual MPI choice) or even just other services.

We choose term “linkage” in SALSA to denote the different ways of synchronizing the parallel activities that may involve shared memory rather than some form of messaging or communication.

There are several engineering and research issues for SALSA• There is the critical communication optimization

problem area for communication inside chips, clusters and Grids.

• We need to discuss what we mean by services

MPI Exchange Latency in µs (20-30 µs computation between messaging)

Machine OS Runtime Grains Parallelism MPI Exchange Latency

Intel8c:gf12

(8 core 2.33 Ghz)

(in 2 chips)

Redhat MPJE (Java) Process 8 181

MPICH2 (C) Process 8 40.0

MPICH2: Fast Process 8 39.3

Nemesis Process 8 4.21

Intel8c:gf20

(8 core 2.33 Ghz)

Fedora MPJE Process 8 157

mpiJava Process 8 111

MPICH2 Process 8 64.2

Intel8b

(8 core 2.66 Ghz)

Vista MPJE Process 8 170

Fedora MPJE Process 8 142

Fedora mpiJava Process 8 100

Vista CCR (C#) Thread 8 20.2

AMD4

(4 core 2.19 Ghz)

XP MPJE Process 4 185

Redhat MPJE Process 4 152

mpiJava Process 4 99.4

MPICH2 Process 4 39.3

XP CCR Thread 4 16.3

Intel4 (4 core 2.8 Ghz) XP CCR Thread 4 25.8

SALSA Performance

The macroscopic inter-service DSS Overhead is about 35µs

DSS is composed from CCR threads that have4µs overhead for spawning threads in dynamic search applications20µs overhead for MPI Exchange

Renters

Total

Asian

Hispanic

Renters

IUB

Purdue

10 Clusters

Total

Asian

Hispanic

Renters

30 Clusters

Clustering is typical of data mining methods that are needed for tomorrow’s clients or servers bathed in a data rich environment

Clustering Census data in Indiana on dual quadcore processorsImplemented with CCR and DSS

Use deterministic annealing that uses multiscale method to avoid local minima

Efficiency is 90% limited by peculiar Windows thread scheduling effects

Parallel Multicore GISDeterministic Annealing Clustering

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0 0.5 1 1.5 2 2.5 3 3.5 4

Parallel Overheadon 8 Threads Intel 8b

Speedup = 8/(1+Overhead)

10000/(Grain Size n = points per core)

Overhead = Constant1 + Constant2/n

Constant1 = 0.02 to 0.1 (Windows) due to threadruntime fluctuations

10 Clusters

20 Clusters

Web 2.0 v Narrow Grid I Web 2.0 and Grids are addressing a similar application class

although Web 2.0 has focused on user interactions• So technology has similar requirements

Web 2.0 chooses simplicity (REST rather than SOAP) to lower barrier to everyone participating

Web 2.0 and Parallel Computing tend to use traditional (possibly visual) (scripting) languages for equivalent of workflow whereas Grids use visual interface backend recorded in BPEL

Web 2.0 and Grids both use SOA Service Oriented Architectures Services will be used everywhere: Grids, Web 2.0 and Parallel

Computing “System of Systems”: Grids and Web 2.0 are likely to build

systems hierarchically out of smaller systems• We need to support Grids of Grids, Webs of Grids, Grids of

Services etc. i.e. systems of systems of all sorts• Web 2.0 suggest data not infrastructure system linkage 3535

Web 2.0 v Narrow Grid II Web 2.0 has a set of major services like GoogleMaps or Flickr

but the world is composing Mashups that make new composite services• End-point standards are set by end-point owners• Many different protocols covering a variety of de-facto standards

Narrow Grids have a set of major software systems like Condor and Globus and a different world is extending with custom services and linking with workflow

Popular Web 2.0 technologies are PHP, JavaScript, JSON, AJAX and REST with “Start Page” e.g. (Google Gadgets) interfaces

Popular Narrow Grid technologies are Apache Axis, BPEL WSDL and SOAP with portlet interfaces

Robustness of Grids demanded by the Enterprise? Not so clear that Web 2.0 won’t eventually dominate other

application areas and with Enterprise 2.0 it’s invading GridsThe world does itself in large numbers!

Web 2.0 v Narrow Grid III Narrow Grids have a strong emphasis on standards and structure Web 2.0 lets a 1000 flowers (protocols) and a million developers bloom

and focuses on functionality, broad usability and simplicity• Interoperability at user (data) level not at service level• Puts semantics into application (user) level (like KML for maps) and

minimizes general system level semantics Semantic Web/Grid has structure to allow reasoning

• Annotation in sites like del.icio.us and uploading to MySpace/YouTube is unstructured and free text search replaces structured ontologies?

• Flickr has geocoded (structured) and unstructured tags Portals are likely to feature both Web and “desktop client” technology

although it is possible that Web approach will be adopted more or less uniformly

Web 2.0 has a very active portal activity which has similar architecture to Grids • A page has multiple user interface fragments

Web 2.0 user interface integration is typically Client side using Gadgets AJAX and JavaScript while• Grids are in a special JSR168 portal server side using Portlets WSRP

and Java

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The Ten areas covered by the 60 core WS-* Specifications

WS-* Specification Area Typical Grid/Web Service Examples

1: Core Service Model XML, WSDL, SOAP

2: Service Internet WS-Addressing, WS-MessageDelivery; Reliable Messaging WSRM; Efficient Messaging MOTM

3: Notification WS-Notification, WS-Eventing (Publish-Subscribe)

4: Workflow and Transactions BPEL, WS-Choreography, WS-Coordination

5: Security WS-Security, WS-Trust, WS-Federation, SAML, WS-SecureConversation

6: Service Discovery UDDI, WS-Discovery

7: System Metadata and State WSRF, WS-MetadataExchange, WS-Context

8: Management WSDM, WS-Management, WS-Transfer

9: Policy and Agreements WS-Policy, WS-Agreement

10: Portals and User Interfaces WSRP (Remote Portlets)

WS-* Areas and Web 2.0 WS-* Specification Area Web 2.0 Approach

1: Core Service Model XML becomes optional but still usefulSOAP becomes JSON RSS ATOM WSDL becomes REST with API as GET PUT etc.Axis becomes XmlHttpRequest

2: Service Internet No special QoS. Use JMS or equivalent?

3: Notification Hard with HTTP without polling– JMS perhaps?

4: Workflow and Transactions (no Transactions in Web 2.0)

Mashups, Google MapReduceScripting with PHP JavaScript ….

5: Security SSL, HTTP Authentication/Authorization, OpenID is Web 2.0 Single Sign on

6: Service Discovery http://www.programmableweb.com

7: System Metadata and State Processed by application – no system state – Microformats are a universal metadata approach

8: Management==Interaction WS-Transfer style Protocols GET PUT etc.

9: Policy and Agreements Service dependent. Processed by application

10: Portals and User Interfaces Start Pages, AJAX and Widgets(Netvibes) Gadgets

Looking to the Future Web 2.0 has momentum as it is driven by success of social web

sites and the user friendly protocols attracting many developers of mashups

Grids momentum driven by the success of eScience and the commercial web service thrusts largely aimed at Enterprise

We expect applications such as business and military where predictability and robustness important might be built on a Web Service (Narrow Grid) core with perhaps Web 2.0 functionality enhancements• But even this Web Service application may not survive

Multicore usability driving Parallel Programming 2.0 Simplicity, supporting many developers are forces pressuring

Grids! Robustness and coping with unstructured blooming of a 1000

flowers are forces pressuring Web 2.0