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.
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.
- 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).
- 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).
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:
--with-jdk-bindir=<foo>: the location ofjavacandjavah--with-jdk-headers=<bar>: the directory containingjni.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.
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.
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();
}
}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);
}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.
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);If you have any problems, or find any bugs, please feel free to report them to Open MPI user's mailing list.