satellital image clasification with neural networks step implemented – final report

Satellital Image Clasification with neural networks

Step implemented – Final Report

Susana Arias, Héctor GómezUNIVERSIDAD TÉCNICA PARTICULAR DE LOJA

ECUADOR

www.eu-eela.eu Itacuruça – Brazil, november 2 -15, 2008

http://www.eu-eela.eu/

Final Report

• Satellital Image Clasification use a neural network for clasification the percentage of land use of a satellite image.



Final Report

First Solution

● We decide to compiler the windows's application in

Linux, for that We use a mono's program (C#

interface for Linux).

1. Create info about mono repository: cd /etc/yum.repos.d

2. Download and install: wget

http://www.go-mono.com/download-stable/rhel-4-i386/mo

no.repo

3. We sure Linux kernel can run Mono applications

"natively" (like Windows), without using "mono" every

time. Following these directions, We create a script.



Final Report

• Problems encountered:

Execute the commands only like root.

[alumno@m150-e2gris1 rn]$ ./monos

./monos: line 18: /proc/sys/fs/binfmt_misc/register: Permission denied

[alumno@m150-e2gris1 rn]$ sudo ./monos

– Solution

Install mono´s program in the worker node



Final Report

Second Solution

• We translate the application from .net to C language with MPI libraries.



Final Report

Second Solution


#include <stdlib.h>

#include <stdio.h>

#include <math.h>

#include "mpi.h"

/********** M A I N ******************************************************************************/

int numprocesses, procnum;

int main(int nargs, char* argv[]) {

NET Net;

BOOL Stop;

int result=MPI_Init(&nargs, &argv);

MPI_Comm_size(MPI_COMM_WORLD, &numprocesses); // get total number of processes

MPI_Comm_rank(MPI_COMM_WORLD, &procnum); // get process number for this process

file bf.c


Final Report● Then we compiler MPI en UI, $ mpiCC● Compiler our application, $ mpiCC -o bf bf.c● Then create a .jdl

Type = “Job”;

JobType = “MPICH”;

Executable = “bf”;

CPUNumber = 10;

StdOutput = “output”;

StdError = “error”;

InputSandbox = {“bf”};

OutputSandbox = {“BPN.txt”};



Final Report•We compiler bf.c ONLY in the 64 bits machine, do not compiler the machine in 32 bits because do not have installed MPI.

[app01@m111-e2gris1 BF]$ glite-wms-job-submit -a -o jid bf.jdl

[app01@m111-e2gris1 BF]$ glite-wms-job-status -i jid

[app01@m111-e2gris1 BF]$ cd

/tmp/jobOutput/app01_776TAA4JvsR-NP2gRkgamA/BPN.txt

NMSE is 0.106 on Training Set and 0.133 on Test Set





Final Report•Then the application use a Storage Element for read the input files

(Satellital Image) and run in the worker nodes.


JOB GET OUTPUT OUTCOME

Output sandbox files for the job:https://m05-e2gris1.eela.ufrj.br:9000/aUZWfM3V6-ftNkvfdG3MGAhave been successfully retrieved and stored in the directory:/tmp/jobOutput/app01_aUZWfM3V6-ftNkvfdG3MGA

[app01@m111-e2gris1 app01_aUZWfM3V6-ftNkvfdG3MGA]$ ls

BPN.txt error output watchdog.log


Final Report•Finally We use a GENIUS portal for submit the jobs, not with MPI.


Final Report: MrBayes As the same time, We worked in another

application like Mrbayes (bionformatics), We install mrbayes at the UI, and We try to run mrbayes with condor, but it was not possible because there was not condor in the CE, finally We saw how to mrbyes runs with mpi and find out how to put some directives to run in the WN.


Final Report: MrBayes

•We send MrBayes application to GENIUS

portal.

• Normally the time for run is 2 weeks, in 1

CPU, and the output files is a string

sequence of 360GB



Thanks!


Questions?

Thanks!


satellital image clasification with neural networks step implemented – final report

Documents