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3. StarPU Java Interface

The StarPU Java Interface provides the ability to execute Java applications on top of StarPU.

The interface allows to write either StarPU-like applications

package fr.labri.hpccloud.starpu.examples;
import fr.labri.hpccloud.starpu.Codelet;
import fr.labri.hpccloud.starpu.StarPU;
import fr.labri.hpccloud.starpu.data.DataHandle;
import fr.labri.hpccloud.starpu.data.IntegerVariableHandle;
import fr.labri.hpccloud.starpu.data.VectorHandle;
import java.util.Random;
import static fr.labri.hpccloud.starpu.data.DataHandle.AccessMode.*;
public class VectorScal
{
public static final int NX = 10;
public static final Float factor = 3.14f;
static final Codelet scal = new Codelet()
{
@Override
public void run(DataHandle[] buffers)
{
VectorHandle<Float> array = (VectorHandle<Float>)buffers[0];
int n = array.getSize();
System.out.println(String.format("scaling array %s with %d elements", array, n));
for (int i = 0; i < n; i++)
{
array.setValueAt(i, factor * array.getValueAt(i));
}
}
@Override
public DataHandle.AccessMode[] getAccessModes()
{
return new DataHandle.AccessMode[]
{
STARPU_RW
};
}
};
public static void main(String[] args) throws Exception
{
int nx = (args.length == 0) ? NX : Integer.valueOf(args[0]);
compute(nx);
}
public static void compute(int nx) throws Exception
{
StarPU.init();
System.out.println(String.format("VECTOR[#nx=%d]", nx));
VectorHandle<Float> arrayHandle = VectorHandle.register(nx);
System.out.println(String.format("scaling array %s", arrayHandle));
for(int i=0 ; i<nx ; i++)
{
arrayHandle.setValueAt(i, i+1.0f);
}
StarPU.submitTask(scal, false, arrayHandle);
arrayHandle.acquire();
for(int i=0 ; i<nx ; i++)
{
System.out.println(String.format("v[%d] = %f", i, arrayHandle.getValueAt(i)));
}
arrayHandle.release();
arrayHandle.unregister();
StarPU.shutdown();
}
}
STARPU_RW
@ STARPU_RW
Definition starpu_data.h:60

or Spark applications.

package fr.labri.hpccloud.starpu.examples;
import fr.labri.hpccloud.starpu.StarPU;
import fr.labri.hpccloud.starpu.data.DataPairSet;
import fr.labri.hpccloud.starpu.data.DataSet;
import fr.labri.hpccloud.starpu.data.Tuple2;
import java.io.File;
import java.io.FileInputStream;
import java.io.InputStream;
import java.util.Arrays;
import java.util.regex.Pattern;
public class WordCount
{
static InputStream openFile(String filename) throws Exception
{
return WordCount.class.getResourceAsStream(filename);
}
private static final Pattern SPACE = Pattern.compile(" ");
public static void main(String[] args ) throws Exception
{
InputStream input = new FileInputStream(args[0]);
StarPU.init();
compute(input);
input.close();
StarPU.shutdown();
}
private static void compute(InputStream input) throws Exception
{
DataSet<String> lines = DataSet.readFile (input, s->s).splitByBlocks(10);
DataSet<String> words = lines.flatMap(s -> Arrays.asList(SPACE.split(s)).iterator()).splitByBlocks(10);
DataPairSet<String,Integer> ones = (DataPairSet<String,Integer>)words.mapToPair(w-> new Tuple2<>(w,1));
DataPairSet<String,Integer> counts = ones.reduceByKey((c1,c2)-> c1 + c2);
for(Tuple2<String,Integer> p : counts.collect())
{
System.out.println("("+p._1()+","+p._2()+")");
}
}
}

The installation process is not yet included in the StarPU autotools mechanism. However, a file `INSTALL.org` is provided in the `starpujni` directory to explain how to proceed with the installation, and shows how to run some basic examples.

`hadoop` needs to be installed before running the installation process.