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A comprehensive collection of matrix data structures, linear solvers, least squares methods, eigenvalue, and singular value decompositions.

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/*
 * Copyright (C) 2003-2006 Bjørn-Ove Heimsund
 * 
 * This file is part of MTJ.
 * 
 * This library is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as published by the
 * Free Software Foundation; either version 2.1 of the License, or (at your
 * option) any later version.
 * 
 * This library is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License
 * for more details.
 * 
 * You should have received a copy of the GNU Lesser General Public License
 * along with this library; if not, write to the Free Software Foundation,
 * Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
 */

package no.uib.cipr.matrix.distributed;

import java.lang.reflect.Array;
import java.util.List;
import java.util.concurrent.CyclicBarrier;
import java.util.concurrent.Exchanger;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ThreadFactory;

/**
 * Inter-thread communications. Supports point-to-point communications using
 * barriers between the threads. Construct it using the
 * CollectiveCommunications.createCommunicator method.
 * 

* All Objects which are sent and recieved are arrays (for * instance, double[] or int[]), and the types * must be compatible. It follows that Object[] is an array of * native arrays, such as int[][]. * * @deprecated the no.uib.cipr.matrix.distributed package has been deprecated because * of a number of hard to fix concurrency bugs. It is distributed only for backwards compatibility, * but is not recommended. The utility of this package is questionable, as it does not allow * distribution of computation between JVMs or across a network. For many people, distributed * computing of multiple matrices can be achieved at a user-level through the * JPPF Framework. * Users who need to deal with few very large matrices may wish to implement their own storage classes * and solvers using JPPF, but this will not be supported directly in matrix-toolkits-java. */ @Deprecated public class Communicator { /** * My rank */ private final int rank; /** * Executes asynchronous operations */ private final ExecutorService executor; /** * Collective communications */ private final CollectiveCommunications coll; /** * Input and output locks for irecv/isend */ final Object[] in, out; /** * Barrier for communication with a peer */ final SendRecv[] send, recv; static class SendRecv implements Runnable { CyclicBarrier barrier = new CyclicBarrier(2, this); Object send, recv; int sendOffset, recvOffset, length; public void run() { System.arraycopy(send, sendOffset, recv, recvOffset, length); } } /** * Sets up a communicator between the given number of threads */ Communicator(int rank, final List> ex, CollectiveCommunications coll) { this.rank = rank; this.coll = coll; if (rank < 0) throw new IllegalArgumentException("rank < 0"); if (rank >= size()) throw new IllegalArgumentException("rank >= size"); // Create daemon threads for running async communications executor = Executors.newCachedThreadPool(new ThreadFactory() { public Thread newThread(Runnable r) { Thread t = new Thread(r); t.setDaemon(true); return t; } }); in = new Object[size()]; out = new Object[size()]; for (int i = 0; i < size(); ++i) { in[i] = new Object(); out[i] = new Object(); } send = new SendRecv[size()]; recv = new SendRecv[size()]; // Create local sends, and get recvs from the peers for (int i = 0; i < size(); ++i) if (i != rank) try { send[i] = new SendRecv(); recv[i] = ex.get(i).exchange(send[i]); } catch (InterruptedException e) { throw new RuntimeException(e); } } /** * Rank of this thread in the collective */ public int rank() { return rank; } /** * Size of the collective */ public int size() { return coll.size(); } /** * Gathers data from all tasks and distribute it to all. *

* Row corresponds to ranks, and columns corresponds to data. *

* Input:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1   
B1   
C1   
D1   
*

* Output:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1B1C1D1
A1B1C1D1
A1B1C1D1
A1B1C1D1
*/ public void allGather(Object sendbuf, Object[] recvbuf) { coll.allGather(sendbuf, recvbuf, rank); } /** * Combines values from all processes and distribute the result back to all * processes. */ public void allReduce(Object sendbuf, Object recvbuf, Reduction op) { coll.allReduce(sendbuf, recvbuf, op, rank); } /** * Sends data from all to all processes. *

* Row corresponds to ranks, and columns corresponds to data. *

* Input:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1A2A3A4
B1B2B3B4
C1C2C3C4
D1D2D3D4
*

* Output:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1B1C1D1
A2B2C2D2
A3B3C3D3
A4B4C4D4
*/ public void allToAll(Object[] sendbuf, Object[] recvbuf) { coll.allToAll(sendbuf, recvbuf, rank); } /** * Blocks until all process have reached this routine. */ public void barrier() { coll.barrier(); } /** * Broadcasts a message from the process with rank "root" to all other * processes of the group. *

* Row corresponds to ranks, and columns corresponds to data. *

* Input:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1   
    
    
    
*

* Output:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1   
A1   
A1   
A1   
*/ public void broadcast(Object buffer, int root) { coll.broadcast(buffer, root, rank); } /** * Gathers together values from a group of processes. *

* Row corresponds to ranks, and columns corresponds to data. *

* Input:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1   
A2   
A3   
A4   
*

* Output:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1A2A3A4
    
    
    
*/ public void gather(Object sendbuf, Object[] recvbuf, int root) { coll.gather(sendbuf, recvbuf, root, rank); } /** * Reduces values on all processes to a single value */ public void reduce(Object sendbuf, Object recvbuf, Reduction op, int root) { coll.reduce(sendbuf, recvbuf, op, root, rank); } /** * Sends data from one task to all other tasks in a group. *

* Row corresponds to ranks, and columns corresponds to data. *

* Input:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1A2A3A4
    
    
    
*

* Output:

* * * * * * * * * * * * * * * * * * * * * * * * *
A1   
A2   
A3   
A4   
*/ public void scatter(Object[] sendbuf, Object recvbuf, int root) { coll.scatter(sendbuf, recvbuf, root, rank); } /** * Sends data[offset:offset+length] to peer */ public void send(Object data, int offset, int length, int peer) { checkArgs(data, offset, length, peer); send[peer].length = length; send[peer].sendOffset = offset; send[peer].send = data; CollectiveCommunications.await(send[peer].barrier); } /** * Receives data[offset:offset+length] from peer */ public void recv(Object data, int offset, int length, int peer) { checkArgs(data, offset, length, peer); recv[peer].recvOffset = offset; recv[peer].recv = data; CollectiveCommunications.await(recv[peer].barrier); } public Future isend(final Object data, final int offset, final int length, final int peer) { return executor.submit(new Runnable() { public void run() { synchronized (out[peer]) { send(data, offset, length, peer); } } }); } public Future irecv(final Object data, final int offset, final int length, final int peer) { return executor.submit(new Runnable() { public void run() { synchronized (in[peer]) { recv(data, offset, length, peer); } } }); } public void send(Object data, int peer) { send(data, 0, Array.getLength(data), peer); } public void recv(Object data, int peer) { recv(data, 0, Array.getLength(data), peer); } public Future isend(Object data, int peer) { return isend(data, 0, Array.getLength(data), peer); } public Future irecv(Object data, int peer) { return irecv(data, 0, Array.getLength(data), peer); } /** * Waits for the given asynchronous operations to finish */ public void await(Future[] future) { for (Future f : future) await(f); } /** * Waits for the given asynchronous operation to finish */ public void await(Future f) { if (f == null) return; try { f.get(); } catch (Exception e) { throw new RuntimeException(e); } } private void checkArgs(Object data, int offset, int length, int peer) { if (peer == rank) throw new IllegalArgumentException("peer == rank"); if (length + offset > Array.getLength(data)) throw new IllegalArgumentException("Buffer underflow"); if (peer < 0 || peer >= coll.size) throw new IllegalArgumentException("Invalid peer"); } }




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