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out of memory error(given solution did not work)

I am running following script for starting my bea weblogic workshow 8.1.4, workshop start properly and function very well

C:\\bea\\weblogic81\\workshop C:\\bea\\jdk142_05\\bin\\javaw.exe -XX:-UseThreadPriorities -Xmx512m -Xms512m -Xss256k -client -Dbpelexport.java.home="C:\\bea10.3\\jdk160_05\\" -Dsun.io.useCanonCaches=false -Dsun.java2d.noddraw=true -Dsun.java2d.d3d=false -Djava.system.class.loader="workshop.core.AppClassLoader" -cp "C:\\bea\\weblogic81\\workshop\\wlw-ide.jar" workshop.core.Workshop

But when i start exporting my process(means these lines come in picture -Dbpelexport.java.home="C:\bea10.3\jdk160_05\") I am getting following error

java.lang.OutOfMemoryError: Java heap space
    at java.util.Arrays.copyOf(Arrays.java:2760)
    at java.util.Arrays.copyOf(Arrays.java:2734)
    at java.util.ArrayList.ensureCapacity(ArrayList.java:167)
    at java.util.ArrayList.add(ArrayList.java:351)
    at javelin.SourceBuffer.read(SourceBuffer.java:123)
    at javelin.SourceBuffer.getReader(SourceBuffer.java:63)
    at javelin.SourceFile.getBufferedReader(SourceFile.java:378)
    at javelin.SourceFile.getReader(SourceFile.java:405)
    at javelin.SourceNode.getReader(SourceNode.java:221)
    at javelin.java.JavaCompiler$Parser.parse(JavaCompiler.java:77)
    at javelin.work.WorkParse._parseNode(WorkParse.java:224)
    at javelin.work.WorkParse.parse(WorkParse.java:156)
    at javelin.work.WorkParse.run(WorkParse.java:91)
    at javelin.threading.WorkList.runItem(WorkList.java:500)
    at javelin.threading.WorkItem.ensureComplete(WorkItem.java:103)
    at javelin.work.WorkCompile.run(WorkCompile.java:69)
    at javelin.threading.WorkList.runItem(WorkList.java:500)
    at javelin.threading.WorkList$WorkerThread.run(WorkList.java:292)

My system has 3 GB of RAM.

is there any way i can supply memory parameters to jdk1.6 java.exe also in the same script.

suggest me something...

Modify the -Xmx argument to give the process more memory, such as -Xmx=2G to allow Java use 2 gigs of memory. Adjust as needed.

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