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AIST Grid Initiative in Japan and the Asia Pacific Region. Yoshio Tanaka Grid Technology Research Center, A dvanced I ndustrial S cience and T echnology, Japan. Talk Contents. Introduction myself and AIST Research Activities Ninf-G: GridRPC Programming Middleware

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aist grid initiative in japan and the asia pacific region

AIST Grid Initiative in Japan and the Asia Pacific Region

Yoshio Tanaka

Grid Technology Research Center,

Advanced Industrial Science and Technology, Japan

talk contents
Talk Contents
  • Introduction
    • myself and AIST
  • Research Activities
    • Ninf-G: GridRPC Programming Middleware
    • ApGrid: Asia Pacific Grid
    • Grid PSE Builder
self introduction
Self Introduction
  • 1995
    • Received Ph.D from Keio University
      • Parallel GC (Garbage Collection)
  • 1996~1999: Real World Computing Partnership (RWCP)
    • Programming and performance evaluation of SMP clusters
    • Firewall-compliant Globus Toolkit + MPICH-G
  • 2000: Electrotechnical Laboratory (ETL)
    • Ninf-G, ApGrid
  • 2001~: AIST
what is the aist
What is the AIST ?
  • One of the largest Nat’l Labs in Japan
  • Research topics include
    • Environment
    • Material
    • Bio/Life science
    • Standards (JIS/OSI)
    • Geographical survey
    • Semiconductor device
    • Computer Science
    • etc.
  • 3,500 employee + 3,000 staff
  • roughly $1,400M USD/FY2002

AIST Tsukuba Main Campus

7 other campuses across Japan

Tsukuba

40km

Narita

50km

Tokyo

50km

grid technology research center
Grid Technology Research Center
  • Establishment
    • Since Jan. 1, 2002
    • 7 years term
    • 24th Research Center of AIST
  • Location
    • Tsukuba Central

Umezono 1-1, Tsukuba

    • Tokyo Office
      • Ueno area
      • 30 people for software development
  • Engaged in developing grid middleware, applications and system technologies
  • Research $$ approx. 1000M JPY

One of the world’s foremost GRID Research Center, the largest in Japan

slide6

Grid Tech. Research Center

Director: Satoshi Sekiguchi

Deputy Director: Mitsuo Yokokawa

aist gtrc grid super cluster
AIST GTRC (Grid) Super Cluster

P32: IBM eServer325

Opteron 2.0GHz, 6GB

2way x 1074 node

Myrinet 2000

8.59TFlops/peak

10,200mm

Myrinet

M64: Intel Tiger 4

Madison 1.3GHz, 16GB

4way x 131 node

Myrinet 2000

2.72TFlops/peak

10,800mm

F32: Linux Networx

Xeon 3.06GHz, 2GB

2way x 256+ node

GbE

3.13TFlops/peak

P32

M64

total 14.5TFlops/peak, 3188 CPUs

slide8

National Research Grid Initiative (NAREGI) Project:Overview

  • A new Japanese MEXT National Grid R&D project
  • ~$(US)17M FY’03 (similar until FY’07) + $45mil
  • One of two major Japanese Govt. Grid Projects
    • c.f. “BusinessGrid” (~$(US)25M FY’03-05) METI
  • Collaboration of National Labs. Universities and Major Computing and Nanotechnology Industries
  • - Acquisition of Computer Resources underway (FY2003)

MEXT:Ministry of Education, Culture, Sports,Science and Technology

naregi software stack
NAREGI Software Stack

WP6: Grid-Enabled Apps

WP3: Grid Visualization

WP3: Grid PSE

WP3: Grid Workflow

WP2: Grid Programming-Grid RPC

-Grid MPI

WP4: Packaging

WP1: Grid Monitoring & Accounting

WP1: SuperScheduler

(Globus,Condor,UNICOREOGSA)

WP5: Grid PKI

WP1: Grid VM

WP5: High-Performance Grid Networking

layered programming model method
Layered Programming Model/Method

Easy but

inflexible

Portal / PSE

GridPort, HotPage,

GPDK, Grid PSE Builder,

etc…

High-level Grid Middleware

MPI (MPICH-G2, PACX-MPI, …)

GridRPC (Ninf-G, NetSolve, …)

MPI

Low-level Grid Middleware

Globus Toolkit

Primitives

Socket, system calls, …

Difficult

but flexible

some significant grid programming models systems
Some Significant Grid Programming Models/Systems
  • Data Parallel
    • MPI - MPICH-G2, Stampi, PACX-MPI, MagPie
  • Task Parallel
    • GridRPC – Ninf, Netsolve, Punch…
  • Distributed Objects
    • CORBA, Java/RMI, …
  • Data Intensive Processing
    • DataCutter, Gfarm, …
  • Peer-To-Peer
    • Various Research and Commercial Systems
      • UD, Entropia, Parabon, JXTA, …
  • Others…
gridrpc rpc based programming model
GridRPC: RPC based Programming model

Utilization of remote

supercomputers

② Notify results

Internet

user

① Call remote

procedures

Call remote libraries

Large scale computing utilizing multiple supercomputers on the Grid

gridrpc rpc tailored for the grid
GridRPC: RPC “tailored” for the Grid
  • Medium to Coarse-grained calls
    • Call Duration < 1 sec to > week
  • Task-Parallel Programming on the Grid
    • Asynchronous calls, 1000s of scalable parallel calls
  • Large Matrix Data & File Transfer
    • Call-by-reference, shared-memory matrix arguments
  • Grid-level Security(e.g., Ninf-G with GSI)
  • Simple Client-side Programming & Management
    • No client-side stub programming or IDL management
  • Other features…
gridrpc cont d
GridRPC (cont’d)
  • v.s. MPI
    • Client-server programming is suitable for task-parallel applications.
    • Does not need co-allocation
    • Can use private IP address resources if NAT is available (at least when using Ninf-G)
    • Better fault tolerancy
  • Activities at the GGF GridPRC WG
    • Define standard GridRPC API; later deal with protocol
    • Standardize only minimal set of features; higher-level features can be built on top
    • Provide several reference implementations
      • Ninf-G, NetSolve, …
typical scenario optimization problems and parameter study on cluster of clusters
Typical Scenario: Optimization Problems and Parameter Study on Cluster of Clusters

rpc

rpc

rpc

Structural Optimization

Vehicle Routing Problem

Slide by courtesy of Prof. Fujisawa

sample architecture and protocol of gridrpc system ninf

Connect back

Interface

Reply

Generate

Invoke

Executable

Interface

Request

fork

Remote Library

Executable

Register

Sample Architecture and Protocol of GridRPC System – Ninf -

Server side

  • Call remote library
    • Retrieve interface information
    • Invoke Remote Library Executable
    • It Calls back to the client

Client side

  • Server side setup
    • Build Remote Library Executable
    • Register it to the Ninf Server

IDL file

Numerical

Library

Client

IDL Compiler

Ninf Server

gridrpc based on client server model
GridRPC: based on Client/Server model
  • Server-side setup
    • Remote libraries must be installed in advance
      • Write IDL files to describe interface to the library
      • Build remote libraries
    • Syntax of IDL depends on GridRPC systems
      • e.g. Ninf-G and NetSolve have different IDL
  • Client-side setup
    • Write a client program using GridRPC API
    • Write a client configuration file
    • Run the program
the gridrpc api
The GridRPC API
  • Provide standardized, portable, and simple programming interface for Remote Procedure Call
  • Attempt to unify client access to existing grid computing systems (such as NetSolve and Ninf-G)
  • Working towards standardization through the GGF GridRPC WG
    • Initially standardize API; later deal with protocol
    • Standardize only minimal set of features; higher-level features can be built on top
    • Provide several reference implementations
      • Not attempting to dictate any implementation details
rough steps for rpc
Rough steps for RPC
  • Initialize
  • Create a function handle
    • Abstraction to a remote library
  • RPC
    • Call remote procedure

grpc_initialize(config_file);

grpc_function_handle_t handle;

grpc_function_handle_init(

&handle, host, port, “lib_name”);

grpc_call(&handle, args…);

or

grpc_call_async(&handle, args…);

data parallel application
Data Parallel Application
  • Call parallel libraries (e.g. MPI apps).
  • Backend “MPI” orBackend “BLACS”should be specifiedin the IDL

Parallel Computer

Parallel Numerical Libraries

Parallel Applications

task parallel application

Server

Server

Server

Server

Task Parallel Application
  • Parallel RPCs using asynchronous call.
task parallel application1
Task Parallel Application
  • Asynchronous Call
  • Waiting for reply

Client

ServerA

ServerB

grpc_call_async(...);

grpc_call_async

grpc_call_async

grpc_wait_all

grpc_wait(sessionID);

grpc_wait_all();

grpc_wait_any(idPtr);

grpc_wait_and(idArray, len);

grpc_wait_or(idArray, len, idPtr);

grpc_cancel(sessionID);

Various task parallel programs spanning clusters are easy to write

ninf project
Ninf Project
  • Started in 1994
  • Collaborators from various organizations
    • AIST
      • Satoshi Sekiguchi, Umpei Nagashima, Hidemoto Nakada, Hiromitsu Takagi, Osamu Tatebe, Yoshio Tanaka,Kazuyuki Shudo , Hirotaka Ogawa
    • University of Tsukuba
      • Mitsuhisa Sato, Taisuke Boku
    • Tokyo Institute of Technology
      • Satoshi Matsuoka, Kento Aida
    • Tokyo Electronic University
      • Katsuki Fujisawa
    • Ochanomizu University
      • Atsuko Takefusa
    • Kyoto University
      • Masaaki Shimasaki
history of ninf project
History of Ninf Project

1994

1997

2000

2003

Ninf-G

development

Ninf project

launched

Ninf-G

Ver.2.0.0

Release

Standard GridRPC

API proposed

Release Ninf

version 1

GridRPC WG

at GGF8 / GGF9

Start collaboration

with NetSolve team

Release Ninf-G

version 0.9

Release Ninf-G

version 1.0

what is ninf g
What is Ninf-G?
  • A software package which supports programming and execution of Grid applications using GridRPC.
  • Ninf-G includes
    • C/C++, Java APIs, libraries for software development
    • IDL compiler for stub generation
    • Shell scripts to
      • compile client program
      • build and publish remote libraries
    • sample programs
    • manual documents
ninf g features at a glance
Ninf-G: Features At-a-Glance
  • Ease-of-use, client-server, Numerical-oriented RPC system
  • No stub information at the client side
  • User’s view: ordinary software library
    • Asymmetric client vs. server
  • Built on top of the Globus Toolkit
    • Uses GSI, GRAM, MDS, GASS, and Globus-IO
  • Supports various platforms
    • Ninf-G is available on Globus-enabled platforms
  • Client APIs: C/C++, Java, Fortran
architecture of ninf g

Connect back

Invoke

Executable

fork

Architecture of Ninf-G

Client side

Server side

IDL file

Numerical

Library

Client

IDL Compiler

Generate

Globus-IO

Interface

Request

Interface

Reply

Remote Library

Executable

GRAM

GRIS

Interface Information

LDIF File

retrieve

demo system of a climate simulation

Ninf-g

Ninf-g

Grid

Lib

Ninf-g

Ninf-g

Ninf-g

user

Demo System of a Climate Simulation
  • Integrating 2 Ninf-G programs
    • Climate Simulation program
    • Visualization program
  • Executed in a pipelined fashion
  • Accessing through GridLib portal

S-model Program

Reading Data

Averaging results

Solving Equations

Solving Equations

Solving Equations

Visualizing Results

replica exchange monte calro simulation

Ttotal = Nsmpl*Tcalc

Nsmpl = 105 ~ 106

Ttotal ~ 30 years!

Replica Exchange Monte-Calro Simulation
  • Potential survey of molecules using direct method (ab-initio calc.)
    • Random walk survey
      • enables survey of complicated potential surface
    • Ab-initio calculation
      • enables precise energy calculation of molecules
    • Replica Exchange method
      • Enables efficient MC survey
gridifying the program
Gridifying the program
  • Two levels of parallelization
    • Coarse grained: parallel monte-carlo sampling
    • Fine grained: parallel ab-initio energy calculation
  • Dynamic task scheduling, machine reconfiguration
    • Task scheduling for balancing load on a heterogeneous computing resources
    • Machine scheduling for reconfiguring machine sets on the fly

Bookkeeper

Reconfiguration request

Dynamic scheduling

Energy calc.

REXMC client

Task allocation

Monitoring

Reconfiguration

T1

T2

MC

Sampling

Servers

T3

meta-computing test bed

10 institutes/20 Supercomputers

ab initio calculation

hpc challenge in sc2002

AIST

REXMC Client

For C20 triplet

REXMC Client

For C20 singlet

Bookkeeper

HPC Challenge in SC2002

Metacomputing Test-bed

  • 10 institutions (3 continentals) / 20 parallel computer (7 types)
    • High Performance Computing Center Stuttgart (HLRS),
    • Sandia National Laboratories (SNL),
    • Pittsburgh Supercomputing Center (PSC),
    • Grid Technology Research Center (AIST),
    • Manchester Computing Centre (MCC),
    • National Center for High Performance Computing (NCHC),
    • Japan Atomic Energy Research Institute (JAERI),
    • Korea Institute of Science and Technology Information (KISTI),
    • European Center of Parallelism in Barcelona (CEPBA/CIRI),
    • Finnish IT center for Science (CSC).
current status
Current Status
  • Ninf-G Ver. 2 alpha is available at http://ninf.apgrid.org/
  • Ninf-G Ver. 2 will be released by the end of this March
apgrid asia pacific partnership for grid computing1
ApGrid: Asia Pacific Partnership for Grid Computing

North

America

Europe

  • International Collaboration
  • Standardization

Asia

ApGrid Testbed

International Grid Testbed over the Asia Pacific countries

  • ApGrid focuses on
    • Sharing resources, knowledge, technologies
    • Developing Grid technologies
    • Helping the use of our technologies in create new applications
    • Collaboration on each others work
  • Possible Applications on the Grid
  • Bio Informatics
  • (Rice Genome, etc.)
  • Earth Science
  • (Weather forecast, Fluid prediction, Earthquake prediction, etc.)
slide36

PRAGMA

Pacific Rim Application

andGrid Middleware Assembly

http://www.pragma-grid.net

history and future plan
History and Future Plan

2000

2002

2001

Kick-off meeting

Yokohama, Japan

Demo @ HPCAsia

Gold Coast, Australia

demo @

SC2002

Baltimore,

USA

(50cpu)

Presentation @ GF5

Boston, USA

1st ApGrid Workshop

Tokyo, Japan

presentation @ SC2001

SC Global Event

demo @

iGrid2002

Amsterdam,

Netherland

1st Core Meeting

Phuket, Thailand

ApGrid

PRAGMA

Presentation

@ APAN

Shanghai,

China

1st PRAGMA Workshop

San Diego, USA

2nd PRAGMA

Workshop

Seoul, Korea

2nd ApGid Workshop/Core Meeting

Taipei, Taiwan

history and future plan cont d
History and Future Plan (cont’d)

2003

2004

3rd PRAGMA

Workshop

Fukuoka,

Japan

presentation

@ APAN

Hawaii, USA

demo @ SC2004

Pittsburgh, USA

7th PRAGMA

Workshop

San Diego, USA

demo @ CCGrid

Tokyo, Japan

(100cpu)

6th PRAGMA

Workshop

Beijing, China

Asia Grid Workshop

(HPC Asia)

Oomiya, Japan

4th PRAGMA Workshop

Melbourne, Australia

(200cpu)

demo @ SC2003

Joing Demo with TeraGrid

Phoenix, USA

(853CPU)

demo &

ApGrid Informal Meeting

@ APAC’03

Gold Coast, Australia

(250cpu)

5th PRAGMA Workshop

Hsinchu, Taiwan

(300cpu)

slide40

Sun Grid Engine

on the ApGrid Testbed

Ultra Enterprise Cluster

+

Sun Grid Engine (AIST, Japan)

Sun Demo Station

Denver, USA

622Mbps x 2

Job submisssion via

Globus

slide41

Large-scale

Sun Grid Engine

Grid Testbed in Asia Pacific

slide42

ApGrid/PRAGMA Testbed

  • Architecture, technology
    • Based on GT2
      • Allow multiple CAs
      • Build MDS Tree
    • Grid middleware/tools from Asia Pacific
      • Ninf-G (GridRPC programming)
      • Nimrod-G (parametric modeling system)
      • SCMSWeb (resource monitoring)
      • Grid Data Farm (Grid File System), etc.
  • Status
    • 26 organizations (10 countries)
    • 27 clusters (889 CPUs)
lessons learned
Lessons Learned
  • We have to pay much efforts for initiation
    • Problems on installation of GT2/PBS/jobmanger
      • Installation/configuration of GT2/PBS/jobmanager is still not so easy for application people.
      • Most sites needed help for the installation.
    • Software requirements depends on the application and middleware used by the application.
      • In order to run GridRPC (Ninf-G) applications, I asked
        • Open firewall/TCP Wrapper
        • Additionally build Info SDK bundle with gcc32dbg
        • Install Ninf-G
        • change configuration of xinetd/inetd
        • Enable NAT
lessons learned cont d
Lessons Learned (cont’d)
  • MDS is not scalable and still unstable
    • Terrible performance
      • GIIS lookup takes several ten seconds ~ minutes
    • Some parameters in grid-info-slapd.conf such as sizelimit, timeout, cahcettl, etc., should be set to appropriate values depends on your environment (number of registered objects, network performance between GRISes and GIISes, etc.).
  • Well known problem 
    • Firewall, private IP addresses…
lessons learned cont d1
Lessons Learned (cont’d)
  • Difficulties caused by the grass-roots approach.
    • It is not easy to keep the GT2 version coherent between sites.
    • Different requirements for the Globus Toolkit between users.
      • Middleware developers needs the newest one.
      • Application developers satisfy with using the stable (older) one.
      • It is not easy to catch up frequent version up of the Globus Toolkit.
      • CoG is a current problem 
lessons learned cont d2
Lessons Learned (cont’d)
  • Difficulties caused by the grass-roots approach (cont’d)
    • Most resources are not dedicated to the ApGrid Testbed. (though this is a common problem for Grids)
      • There may be busy resources
      • Need grid level scheduler, fancy Grid reservation system?
lessons learned cont d3
Lessons Learned (cont’d)
  • Some resources are not stable
    • example: If I call many RPCs, some of them fails (but sometimes all will done)
    • not yet resolved
    • GT2? Ninf-G? OS? Hardware?
  • Other instability
    • System maintenance (incl. version up of software) without notification
      • realized when the application would fail.
      • it worked well yesterday, but I’m not sure whether it works today
  • But this is the Grid 
observations
Observations
  • Still being a “grass roots” organization
    • Less administrative formality
      • cf. PRAGMA, APAN, APEC/TEL, etc.
      • Difficulty in establishing collaboration with others
    • Unclear membership rules
      • Join/leave, membership levels
      • Rights/Obligations
    • Vague mission, but already collected (potentially) large computing resources
observations cont d
Observations (cont’d)
  • Duplication of efforts on “similar” activities
    • Organization-wise
      • APAN - participation by country
      • PRAGMA – most organizations are overlapped
    • Operation-wise
      • ApGrid testbed vs PRAGMA-resource
        • may cause confusion
        • technically, the same approach
      • Multi-grid federation
    • Network-wise
      • Primary APAN – TransPAC
        • Skillful engineering team
summary of current status
Summary of current status
  • Difficulties are caused by not technical problems but sociological/political problems
  • Each site has its own policy
    • account management
    • firewalls
    • trusted CAs
  • Differences in interests
    • Application, middleware, networking, etc.
  • Differences in culture, language, etc.
    • Human interaction is very important
summary of current status cont d
Summary of current status (cont’d)
  • Activities at the GGF
    • Production Grid Management RG
      • Draft a Case Study Document (ApGrid Testbed)
    • Groups in the Security Area
      • Policy Management Authority RG (not yet approved)
        • Discuss with representatives from DOE Science Grid, NASA IPG, EUDG, etc.
      • Federation/publishing of CAs (will kick off)
        • I’ll be one of co-chairs
summary of current status cont d1
Summary of current status (cont’d)
  • What has been done?
    • Resource sharing between more than 10 sites (853cpus are used by Ninf-G application)
    • Use GT2 as a common software
  • What hasn’t?
    • Formalize “how to use the Grid Testbed”
      • I could use, but it is difficult for others
        • I was given an account at each site by personal communication
      • Provide documentation
    • Keep the testbed stable
    • Develop management tools
      • Browse information
      • CA/Cert. management
future plan
Future Plan
  • Draft “Asia Pacific Grid Middleware Deployment Guide”, which is a recommendation document for deployment of Grid middleware
    • Minimum requirements
    • Configuration
  • Draft “Instruction of Grid Operation in the Asia Pacific Region”, which guides how to run Grid Operation Center to support management of stable Grid testbed.
future plan cont d
Future Plan (cont’d)
  • Should think about GT3/GT4-based Grid Testbed
  • Each CA must provide CP/CPS
  • International Collaboration
    • TeraGrid, UK eScience, EUDG, etc.
  • Run more applications to evaluate feasibility of Grid
    • large-scale cluster + fat link
    • many small cluster + thin link
overview of grid asp

Portal

Overview of Grid ASP
  • Grid ASP provides users PSE( Grid services )
  • Portal system hides Grid environment from users

GridASP

(Grid Service Provider)

User

  • PSE components
  • (Grid Services)
  • Application service
  • Storage service
  • Computing service
  • DB service
  • :

Main service is a batch job

activities @ gtrc aist
Activities @ GTRC, AIST
  • Software toolkit for constructing portal
    • Grid PSE Builder (GridLib)
  • Grid application portals
    • ISV software( Gaussian, Phoenics, ... )
    • user programming application
  • Experiment of Grid ASP (planning)
    • Feasibility study with real business players
overview of the grid pse builder
Overview of the Grid PSE Builder
  • Framework for building an application portal on a grid environment

Globus Toolkit 2.x (MDS, GRAM, GSI)

single sign on session manager

HTTP server

+

Servlet

(Apache + Tomcat)

user

JDBC Interface

(TCP/IP)

Single Sign On / Session Manager

Delegation

using

(JWS/Applet)

client auth.

AIST GridLib Portal

SignOn/SignOff

Job Control

submission/query

/cancel

globusrun

Job Queuing

Manager

&

Signing Server

Accounting

DB

(Postgress)

accounting

information

pse component information

<application

xmlns="http://www.aist.go.jp/vcc"

xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

xsi:schemaLocation="http://www.aist.go.jp/vcc application_schema.xml">

<appname>cat</appname>

<appid>1</appid>

<appcomment>Concatenate file(s).</appcomment>

<argspec>/bin/cat %option% %files%</argspec>

<arglist>

<args use="option" separate="true">

<title>Operation Option</title>

<checkbox name="option">

<box value="-b">number nonblank output lines</box>

<box value="-E">display $ at end of each line</box>

<box value="-n">number all output lines</box>

<box value="-s">never more than one single blank line</box>

<box value="-T">display TAB characters as ^I</box>

<box value="-v">use ^ and M- notation, except for LFD and TAB</box>

</checkbox>

</args>

<args use="required">

<title>files</title>

<file name="files" max="unbounded" />

</args>

</arglist>

</application>

PSE Component information
  • Interface of application
    • XML-based Web page description language
      • Application name, location ...
      • Contents
      • Arguments (input parameters, ..)
      • Options
demo summary
Demo Summary
  • Application: Climate Simulation
    • Short- to Middle- term climate simulation
    • Barotropic S-Model
  • Portal: Grid PSE Builder
    • Visit AIST Booth #739 for more detail
  • Middleware used for the implementation of Grid-enabled climate simulation: Ninf-G V2 (alpha)
    • GridRPC middleware based on the Globus Toolkit which is used for gridifying the original (sequential) application
  • Resources: ApGrid/TeraGrid Testbed (500cpu)
    • NCSA (225cpu), AIST (50cpu), TITECH (200cpu), KISTI (25cpu)
why the climate simulation
Why the climate simulation?
  • Climate simulation is used as a test application to evaluate progress of resource sharing between ApGrid/PRAGMA institutions
  • We can confirm achievements of
    • Globus-level resource sharing
      • Globus is correctly installed
      • Mutual authentication based on GSI
    • High-level Middleware (GridRPC) –level resource sharing
      • JobManager works well
      • Network configuration of the cluster(note that most clusters use private IP addresses)
application climate simulation

……

Application: Climate Simulation
  • Goal
    • Short- to Middle- term, global climate simulation
      • Winding of Jet-Stream
      • Blocking phenomenon of high atmospheric pressure
  • Barotropic S-Model
    • Climate simulation model proposed by Prof. Tanaka (U. of Tsukuba)
    • Simple and precise

Modeling complicated 3D turbulence as a horizontal one

Keep high precision over long periods

      • Taking a statistical ensemble mean
        • ~ several 100 simulations
      • Introducing perturbation at every time step
    • Typical parameter survey
ninfy the original seq climate simulation

Ninf-g

Ninf-g

Ninf-g

Grid

PSE

Web browser

Ninf-g

Ninf-g

user

Ninfy the original (seq.) climate simulation
  • Dividing a program into two parts as a client-server system
    • Client:
      • Pre-processing: reading input data
      • Post-processing: averaging results of ensembles
    • Server
      • climate simulation, visualize

S-model Program

Reading data

Solving Equations

Solving Equations

Solving Equations

Averaging results

VIsualize

slide67

ApGrid / PRAGMA Testbed

      • 10 countries
      • 21 organizations
      • 22 clusters
      • 853 CPUs
behavior of the system
Behavior of the System

Severs

NCSA Cluster (225 CPU)

Ninf-G

Client

(AIST)

Severs

AIST Cluster (50 CPU)

Titech Cluster (200 CPU)

KISTI Cluster (25 CPU)

preliminary evaluation
Preliminary Evaluation
  • Testbed: 500 CPU
    • TeraGrid: 225 CPU (NCSA)
    • ApGrid: 275 CPU (AIST, TITECH, KISTI)
  • Ran 1000 Simulations
    • 1 simulation = 12 seconds
    • 1000 simulation = 12000 seconds = 3 hours 20 min(if runs on a single PC)
  • Results
    • 150 seconds = 2.5 min
  • Insights
    • Confirm application-level resource sharing among 21 sites
    • Ninf-G2 efficiently works on large-scale cluster of cluster
    • Ninf-G2 provides good performance for fine grain task-parallel applications on large-scale Grid.
qc grid gaussian portal

GridLib Server

Internet

FireWall

Client

QC Grid Portal

Apache

Globus gate-keeper

AIST DMZ

Job Manager

LoadLeveler

Job Manager

PBS

FireWall

DB, Oracle

Compaq

GS 160

IBM xSeries,

Linux Cluster

@Tsukuba

IBM pSeries, AIX

@Tohoku

Execution nodes

AIST Ltd. Access LAN

QC Grid / Gaussian Portal
  • Web based User-Interface
  • Input Analyzer
    • CPU time estimation
    • Results reference (Quick and Detailed)
  • Database and Archives
    • Knowledge DB
    • Input and Result Archives
  • Resource allocation scheduler
goal and feature of grid datafarm

SC02 – November 2002

National Institute of Advanced Industrial Science and Technology

Goal and feature of Grid Datafarm
  • Goal
    • Dependable data sharing among multiple organizations
    • High-speed data access, High-speed data processing
  • Grid Datafarm
    • Grid File System – Global dependable virtual file system
      • Integrates CPU + storage
    • Global parallel and distributed processing
  • Features
    • Secured based on Grid Security Infrastructure
    • From small scale to world wide scale depending the data size and usage scenarios
    • Data location transparent data access
    • Automatic and transparent replica access for fault tolerance
    • High-performance data access and processing by accessing multiple dispersed storages in parallel

Source: Osamu Tatebe

slide74

Efficient use around the peak rate in long fat networks

    • IFG (interframe gap)-based precise pacing (using large input
    • buffer 16 Mb) with GNET-1 -> packet loss free network
    • Stable network flow even with HighSpeed TCP
p3 personal power plant
P3: Personal Power Plant
  • Middleware for distributed computation
    • Traditional goals
      • Cycle scavenging
        • Harvest compute power of existing PCs.
      • Internet-wide distributed computing
        • E.g. distributed.net, SETI@home
    • Challenging goals
      • Aggregate PCs and expose them as an integrated Grid resource.
        • Integrate P3 with Grid middleware ?
      • Circulation of computational resources
        • Transfer individual resources (C2C, C2B) and also aggregated resources (B2B).
        • Commercial dealings need a market and a system supporting it.

Conventional dist. computing

Transfer and aggregation of individual resources

for more info
For more Info
  • http://www.aist.go.jp/
  • http://unit.aist.go.jp/grid/
  • http://ninf.apgrid.org/
  • http://www.apgrid.org/
  • yoshio.tanaka@aist.go.jp