Transcript Integrating Computing Resources on Multiple Grid-enabled Job Scheduling Systems Through a Grid

Integrating Computing Resources
on Multiple Grid-enabled Job
Scheduling Systems Through a Grid
RPC System
Yoshihiro Nakajima, Mitsuhisa Sato,
Yoshiaki Aida,Taisuke Boku
Proceedings of the Sixth IEEE International Symposium on
Cluster Computing and the Grid,2006
Reporter:Tung-Yen Haieh
Outline
Introduction
 Design of Grid RPC System Integrating
Computing Resources on a Multiple
Gridenabled Job Scheduling System
 Experimental Results
 Conclusion

Introduction(Cont.)

The demands for high-throughput
computing is increasing, several gridenabled job scheduling systems (GJSSs)
that support high-throughput computing,
such as by XtremWeb , Condor and
CyberGRIP
Introduction(Cont.)

However, each GJSS has its own user
interfaces and each GJSS has its own user
interfaces that the management policy for
the GJSS may also be different on each site.

They propose a framework for integrating
and utilizing computing resources managed
by a GJSS in different organizations by using
Grid RPC style programming.
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
The proposed system realizes following
objectives:
 A uniform and parallel programming
model by remote procedure call on the
grid-enabled job scheduling system.

A fault-tolerant Grid RPC system on the
computing resource side.
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)

Simultaneous exploitation of massive
computing resources provided on sites
that are managed by different
organizations.

An easy-to-use execution environment
from a cluster to Grid-enabled Job
Scheduling Systems without any change
in the application source program.
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)

General APIs to absorb differences
between GJSSs.

General APIs to adapt to new GJSSs.
Automatic deployment of execution
programs on remote
 computing resources.

Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
We have extended OmniRPC for the
proposed system as follows:

A OmniRPC agent process to handle
protocol conversion between the OmniRPC
client program and each GJSS server was
added.
Design of Grid RPC System Integrating
Computing Resources on a Multiple
GJSS(cont.)
The remote executable module of
OmniRPC can handle I/O data through
files.
 Alternative methods are available to
manage the information of the remote
function.
 Easy-to-use APIs by which the proposed
system can adapt to new GJSSs are
provided.

Experimental Results(cont.)
GJSSs as backbends of OmniRPC are
XtremWeb version 1.5, CyberGRIP version
2.2 (CyberGRIP uses JTX), Condor version
7.10.7, and Open Source Grid Engine
Version 6.0u6.
Experimental Results(cont.)
Experimental Results(cont.)
Conclusion
They have presented a framework for a
parallel programming model by remote
procedure calls bridging between largescale computing resource pools managed
by multiple GJSSs.
 They found that the proposed system can
achieve approximately the same
performance as using OmniRPC and can
handle interruptions in worker programs
on remote nodes.
