// *
public static void main(String[] args) throws Exception {
Comm.init(args);
Comm world = Comm.world();
int rank = world.rank();
int size = world.size();
int dim = DEFAULT_D, kay = DEFAULT_K, datasize = Integer.MAX_VALUE;
String infile = DEFAULT_IN;
switch (args.length) {
case 4:
if (isInteger(args[3])) dim = Integer.valueOf(args[3]);
case 3:
if (isInteger(args[2])) kay = Integer.valueOf(args[2]);
case 2:
if (isInteger(args[1])) datasize = Integer.valueOf(args[1]);
case 1:
if (new File(args[0]).exists()) infile = args[0];
}
// the size argument to constructor is the max # of lines to read
IrisKMeans me = new IrisKMeans(infile, datasize, kay, dim);
me.prepareData();
if (rank == 0) me.prepareClusters();
// we want the actual number of elements read
datasize = me.getSize();
Range ir = new Range(0, datasize - 1);
me.setStart(ir.lb());
me.setEnd(ir.ub());
while (!me.changed()) {
// broadcast ciuster assignments
double[][] assignments = new double[kay][dim];
DoubleBuf dbuf = DoubleBuf.buffer(assignments);
if (rank == 0) dbuf = DoubleBuf.buffer(me.clusterCenters());
world.broadcast(0, dbuf);
me.assignmentStep();
if (rank == 0) {
// gather total-count pairs
me.updateStep();
}
}
}
/**
* main method
*
* @param args
* @throws IOException
*/
public static void main(String[] args) throws IOException {
if (args.length != 4) { // usage check
usage();
}
seed = Integer.parseInt(args[0]); // see for rand
m = Integer.parseInt(args[1]);
n = Integer.parseInt(args[2]); // number of rows/columns
filename = args[3]; // output file name
// matrices and vectors
matrixA = new int[m][n];
vectorX = new int[n];
vectorY = new int[m];
long t1 = System.currentTimeMillis();
Comm.init(args);
Comm world = Comm.world();
int size = world.size();
int rank = world.rank();
blockrow = m / size;
blockcol = n / size;
// split the matrixA into rows equally for processors
rangerow = new Range(0, m - 1).subranges(size);
myrangerow = rangerow[rank];
rowlb = myrangerow.lb();
rowub = myrangerow.ub();
// split the vectorX into cols equally for processors
rangecol = new Range(0, n - 1).subranges(size);
myrangecol = rangecol[rank];
collb = myrangecol.lb();
colub = myrangecol.ub();
// row slicing in matrixA and slicing in vectorX
slicesA = IntegerBuf.rowSliceBuffers(matrixA, rangerow);
mysliceA = slicesA[rank];
slicesX = IntegerBuf.sliceBuffers(vectorX, rangecol);
mysliceX = slicesX[rank];
slicesY = IntegerBuf.sliceBuffers(vectorY, rangerow);
mysliceY = slicesY[rank];
Random number = Random.getInstance(seed);
number.skip(rowlb * n);
// matrixA generated by idividual processors
for (int i = rowlb; i <= rowub; i++) {
for (int j = 0; j < n; j++) {
matrixA[i][j] = number.nextInt(10);
}
}
number = Random.getInstance(seed);
number.skip(m * n + collb);
// vectorX generated by individual processors
for (int i = collb; i <= colub; i++) {
vectorX[i] = number.nextInt(10);
}
// allGather in sliceX
world.allGather(0, mysliceX, slicesX);
// matrix-vector calculation performed in individual processor
for (int i = rowlb; i <= rowub; i++) {
for (int j = 0; j < n; j++) {
vectorY[i] = vectorY[i] + matrixA[i][j] * vectorX[j];
}
}
// gather everything to processor 0
world.gather(0, mysliceY, slicesY);
long t2 = System.currentTimeMillis();
System.out.println((t2 - t1) + " msec");
// display the result
if (rank == 0) {
FileWriter fstream = new FileWriter(filename);
BufferedWriter out = new BufferedWriter(fstream);
out.write("Matrix C : \n");
for (int i = 0; i < m; i++) {
out.write(vectorY[i] + " ");
}
out.close();
}
}