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Open MPI Java Bindings

Important node

JAVA BINDINGS ARE PROVIDED ON A "PROVISIONAL" BASIS - I.E., THEY ARE NOT PART OF THE CURRENT OR PROPOSED MPI STANDARDS. THUS, INCLUSION OF JAVA SUPPORT IS NOT REQUIRED BY THE STANDARD. CONTINUED INCLUSION OF THE JAVA BINDINGS IS CONTINGENT UPON ACTIVE USER INTEREST AND CONTINUED DEVELOPER SUPPORT.

Overview

This version of Open MPI provides support for Java-based MPI applications.

The rest of this document provides step-by-step instructions on building OMPI with Java bindings, and compiling and running Java-based MPI applications. Also, part of the functionality is explained with examples. Further details about the design, implementation and usage of Java bindings in Open MPI can be found in [1]. The bindings follow a JNI approach, that is, we do not provide a pure Java implementation of MPI primitives, but a thin layer on top of the C implementation. This is the same approach as in mpiJava [2]; in fact, mpiJava was taken as a starting point for Open MPI Java bindings, but they were later totally rewritten.

  1. O. Vega-Gisbert, J. E. Roman, and J. M. Squyres. "Design and implementation of Java bindings in Open MPI". Parallel Comput. 59: 1-20 (2016).
  2. M. Baker et al. "mpiJava: An object-oriented Java interface to MPI". In Parallel and Distributed Processing, LNCS vol. 1586, pp. 748-762, Springer (1999).

Building Java Bindings

If this software was obtained as a developer-level checkout as opposed to a tarball, you will need to start your build by running ./autogen.pl. This will also require that you have a fairly recent version of GNU Autotools on your system - see the HACKING.md file for details.

Java support requires that Open MPI be built at least with shared libraries (i.e., --enable-shared) - any additional options are fine and will not conflict. Note that this is the default for Open MPI, so you don't have to explicitly add the option. The Java bindings will build only if --enable-mpi-java is specified, and a JDK is found in a typical system default location.

If the JDK is not in a place where we automatically find it, you can specify the location. For example, this is required on the Mac platform as the JDK headers are located in a non-typical location. Two options are available for this purpose:

  1. --with-jdk-bindir=<foo>: the location of javac and javah
  2. --with-jdk-headers=<bar>: the directory containing jni.h

For simplicity, typical configurations are provided in platform files under contrib/platform/hadoop. These will meet the needs of most users, or at least provide a starting point for your own custom configuration.

In summary, therefore, you can configure the system using the following Java-related options:

$ ./configure --with-platform=contrib/platform/hadoop/<your-platform> ...

or

$ ./configure --enable-mpi-java --with-jdk-bindir=<foo> --with-jdk-headers=<bar> ...

or simply

$ ./configure --enable-mpi-java ...

if JDK is in a "standard" place that we automatically find.

Running Java Applications

For convenience, the mpijavac wrapper compiler has been provided for compiling Java-based MPI applications. It ensures that all required MPI libraries and class paths are defined. You can see the actual command line using the --showme option, if you are interested.

Once your application has been compiled, you can run it with the standard mpirun command line:

$ mpirun <options> java <your-java-options> <my-app>

For convenience, mpirun has been updated to detect the java command and ensure that the required MPI libraries and class paths are defined to support execution. You therefore do NOT need to specify the Java library path to the MPI installation, nor the MPI classpath. Any class path definitions required for your application should be specified either on the command line or via the CLASSPATH environment variable. Note that the local directory will be added to the class path if nothing is specified.

As always, the java executable, all required libraries, and your application classes must be available on all nodes.

Basic usage of Java bindings

There is an MPI package that contains all classes of the MPI Java bindings: Comm, Datatype, Request, etc. These classes have a direct correspondence with classes defined by the MPI standard. MPI primitives are just methods included in these classes. The convention used for naming Java methods and classes is the usual camel-case convention, e.g., the equivalent of MPI_File_set_info(fh,info) is fh.setInfo(info), where fh is an object of the class File.

Apart from classes, the MPI package contains predefined public attributes under a convenience class MPI. Examples are the predefined communicator MPI.COMM_WORLD or predefined datatypes such as MPI.DOUBLE. Also, MPI initialization and finalization are methods of the MPI class and must be invoked by all MPI Java applications. The following example illustrates these concepts:

import mpi.*;

class ComputePi {

    public static void main(String args[]) throws MPIException {

        MPI.Init(args);

        int rank = MPI.COMM_WORLD.getRank(),
            size = MPI.COMM_WORLD.getSize(),
            nint = 100; // Intervals.
        double h = 1.0/(double)nint, sum = 0.0;

        for(int i=rank+1; i<=nint; i+=size) {
            double x = h * ((double)i - 0.5);
            sum += (4.0 / (1.0 + x * x));
        }

        double sBuf[] = { h * sum },
               rBuf[] = new double[1];

        MPI.COMM_WORLD.reduce(sBuf, rBuf, 1, MPI.DOUBLE, MPI.SUM, 0);

        if(rank == 0) System.out.println("PI: " + rBuf[0]);
        MPI.Finalize();
    }
}

Exception handling

Java bindings in Open MPI support exception handling. By default, errors are fatal, but this behavior can be changed. The Java API will throw exceptions if the MPI.ERRORS_RETURN error handler is set:

MPI.COMM_WORLD.setErrhandler(MPI.ERRORS_RETURN);

If you add this statement to your program, it will show the line where it breaks, instead of just crashing in case of an error. Error-handling code can be separated from main application code by means of try-catch blocks, for instance:

try
{
    File file = new File(MPI.COMM_SELF, "filename", MPI.MODE_RDONLY);
}
catch(MPIException ex)
{
    System.err.println("Error Message: "+ ex.getMessage());
    System.err.println("  Error Class: "+ ex.getErrorClass());
    ex.printStackTrace();
    System.exit(-1);
}

How to specify buffers

In MPI primitives that require a buffer (either send or receive) the Java API admits a Java array. Since Java arrays can be relocated by the Java runtime environment, the MPI Java bindings need to make a copy of the contents of the array to a temporary buffer, then pass the pointer to this buffer to the underlying C implementation. From the practical point of view, this implies an overhead associated to all buffers that are represented by Java arrays. The overhead is small for small buffers but increases for large arrays.

There is a pool of temporary buffers with a default capacity of 64K. If a temporary buffer of 64K or less is needed, then the buffer will be obtained from the pool. But if the buffer is larger, then it will be necessary to allocate the buffer and free it later.

The default capacity of pool buffers can be modified with an Open MPI MCA parameter:

shell$ mpirun --mca mpi_java_eager size ...

Where size is the number of bytes, or kilobytes if it ends with 'k', or megabytes if it ends with 'm'.

An alternative is to use "direct buffers" provided by standard classes available in the Java SDK such as ByteBuffer. For convenience we provide a few static methods new[Type]Buffer in the MPI class to create direct buffers for a number of basic datatypes. Elements of the direct buffer can be accessed with methods put() and get(), and the number of elements in the buffer can be obtained with the method capacity(). This example illustrates its use:

int myself = MPI.COMM_WORLD.getRank();
int tasks  = MPI.COMM_WORLD.getSize();

IntBuffer in  = MPI.newIntBuffer(MAXLEN * tasks),
          out = MPI.newIntBuffer(MAXLEN);

for(int i = 0; i < MAXLEN; i++)
    out.put(i, myself);      // fill the buffer with the rank

Request request = MPI.COMM_WORLD.iAllGather(
                  out, MAXLEN, MPI.INT, in, MAXLEN, MPI.INT);
request.waitFor();
request.free();

for(int i = 0; i < tasks; i++)
{
    for(int k = 0; k < MAXLEN; k++)
    {
        if(in.get(k + i * MAXLEN) != i)
            throw new AssertionError("Unexpected value");
    }
}

Direct buffers are available for: BYTE, CHAR, SHORT, INT, LONG, FLOAT, and DOUBLE. There is no direct buffer for booleans.

Direct buffers are not a replacement for arrays, because they have higher allocation and deallocation costs than arrays. In some cases arrays will be a better choice. You can easily convert a buffer into an array and vice versa.

All non-blocking methods must use direct buffers and only blocking methods can choose between arrays and direct buffers.

The above example also illustrates that it is necessary to call the free() method on objects whose class implements the Freeable interface. Otherwise a memory leak is produced.

Specifying offsets in buffers

In a C program, it is common to specify an offset in a array with &array[i] or array+i, for instance to send data starting from a given position in the array. The equivalent form in the Java bindings is to slice() the buffer to start at an offset. Making a slice() on a buffer is only necessary, when the offset is not zero. Slices work for both arrays and direct buffers.

import static mpi.MPI.slice;
// ...
int numbers[] = new int[SIZE];
// ...
MPI.COMM_WORLD.send(slice(numbers, offset), count, MPI.INT, 1, 0);

Questions? Problems?

If you have any problems, or find any bugs, please feel free to report them to Open MPI user's mailing list.