Showing posts with label info. Show all posts
Showing posts with label info. Show all posts

Friday, 24 June 2011

Meeting 7 , 8 and 9 [01/06, 13/06 and 20/06]

Meeting 7 [01/06]


During this meeting the project was registered on Sourceforge:


The meeting was very short and the goal of the next coming week was to develop the user-synchronised communication: literally waiting for the user to click on a continue button to continue the MPI operation.


Meeting 8 [13/06]


During the 8th meeting the result of the synchronised communication with the user was presented. Some improvement were nonetheless needed. Each message between the interface and the profiler are done though formatted string, chosen for the simplicity of adding new elements in it. It also gives the advantage of variable length, as MPI_Probe could be use on the receiver side to determine the size of the message and avoid sending big messages when not required (messages for registering a communicator and giving information about a Ssend are not the same length for instance, as they do not have the same information to transmit).


Meeting 9 [20/06]


During the week the code was cleaned, reorganising the Interface mostly in order to cope with user-waiting communications. Registering a communicator was also completed, so the profiler can cope with adding and removing communicators easily. Nonetheless the attribute to find if the communicator was previously registered wasn't introduced yet.

Some improvements were proposed by David on the way of displaying the communications. Currently a ball is moving from the waiting processor to the waited one (A does a Ssend to B, the ball moves from A to B). But displaying a fix image seams to be a better idea, as a moving ball implies message transit, when there is none.

An error was also found when using the Compute Pi example, as the tag MPI_ANY_SOURCE was used and the Interface couldn't understand it.

The next step is to develop the basis of the array registration. With that done, each main requirement will be completed, forming a backbone to develop further one or the other by taking a specific example. In order to register memory nonetheless some development has to be made on both the profiler and interface, as currently there is no way of correctly finding if a peace of memory was registered and to display it on the interface.

Tuesday, 7 June 2011

Handling the MPI_Wait calls

Asynchronous communication


What is it?


Asynchronous communication is used in MPI programmes to have non-blocking operations. Usually theses routines are used to avoid deadlocks, and insure the good working of the communications. Each asynchronous MPI action returns a MPI_Request object that will be used to insure that the communication completed.

It is composed of 2 steps:

  • doing the asynchronous communication
  • waiting for the request

Taking a simple message in a ring example, the code could be:


#include <mpi.h>
#include <stdio.h>

#define TURNS 10

int main(int argc, char** argv)
{
  int i;
  int rank, size, left, right;
  int mess1, mess2;
  MPI_Request leftReq;

  MPI_Init(&argc, &argv);

  MPI_Comm_rank(MPI_COMM_WORLD, &rank);
  MPI_Comm_size(MPI_COMM_WORLD, &size);

  left = (rank+1)%size;
  right = (rank-1+size)%size;
  mess1 = rank;

  for ( i = 0 ; i < TURNS ; i++ )
    {
      // non blocking send to left
      MPI_Issend(&mess1, 1, MPI_INT, left, 0, MPI_COMM_WORLD, &leftReq);
      fprintf(stderr, "%d: sending %d to %d\n", rank, mess1, left);

      // blocking receive from right
      MPI_Recv(&mess2, 1, MPI_INT, right, 0, MPI_COMM_WORLD, MPI_STATUS_IGNORE);
      fprintf(stderr, "%d: receives %d from %d\n", rank, mess2, right);

      // wait for unfinished request
      MPI_Wait(&leftReq, MPI_STATUS_IGNORE);
    }

  MPI_Finalize();

  return 0;
}

On the profiler side the problems comes from knowing on the MPI_Wait calls if the current request is part of the registered communicators (see previous note). From the normal MPI call there is no way of guessing what the original call was, to which processor and what data was actually sent.


Finding what is waited for


An easy way to find about any MPI_Wait information is to save the asynchronous information, and when a wait is issued to look in them in order to find the information about it.
Using the MPI_Request as an identifier, as it has to be unique for the MPI implementation to also find out about what is waited for, the data is stored in a linked list that is part of the Register_Comm structure. The code will therefore look like that:


int MPI_Issend(void *buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm, MPI_Request *request)
{
  int ret;
  Register_Comm* commInfo = NULL;
 
  commInfo = Comm_register_search(comm);

  ret = PMPI_Issend(buf, count, datatype, dest, tag, comm, request);

  if ( commInfo )
    {
      /* send information to the Interface */

      addRequest(commInfo, request, dest, MESSAGE_Issend);
    }

  return ret;
}

int MPI_Wait(MPI_Request *request, MPI_Status *status)
{
  int ret;
  Request_Info* info = NULL;

  // search in all registered communicators...
  info = General_searchRequest(request);
    
  ret = PMPI_Wait(request, status);

  if ( info != NULL )
    {
      /* send information to the Interface */

      freeRequest(info);
    }

  return ret;
}

Internals improvements


The data are stored as double linked list cells, in order to have easy removal of elements (requests may not be waited in the same order that they are generated). Therefore the current implementation is obviously not very fast, as the time to find a request is proportional to the number of requests per registered communicators (each communicator is searched).

An easy improvement for that could be to add an attribute the the MPI_Request object (using MPI_set_attribute) that will point out what communicator is this request allocated to, reducing the searching time when several communicators or asynchronous alls are registered.

So far no information is given to the interface if a request isn't waited for, but a registered communicator cannot be deleted when there is still pending requests. The only way to notice is to see that the number of asynchronous calls is different of the numbers of wait ones. This may change in the future. A message should be sent to the Interface when a registered communicator is destroyed (an hence all its pending requests as well) or when MPI_Finalize is called and there is still some requests on the list.

The MPI_Waitall, MPI_Waitany and MPI_Waitsome aren't supported yet, and tests have to be performed to see if they individually call MPI_Wait, but it is more likely that they directly call some common internal function.

Friday, 3 June 2011

Register a communicator

Why registering a communicator?


Registering a communicator was, originally, an idea developed to allow the user to filter communication occurring on a specific MPI communicator rather than on all of the used ones. But quickly during the tests it appears that the MPI profiling interface was used for every call of the library, meaning that when MPI_Ssend is redefined for example, even for a simple program (like the message in ring, 40 sends, 40 receives, 40 waits) the count of messages was enormous (certainly internal messages).

It became therefore important to filter the messages to register in the Interface, and in order to avoid network congestion, to do so on the Profiler side. The first way to reduce this number of messages is very simple: check for MPI_COMM_WORLD, that is the basic communicator used. But it doesn't provide the user any choice on monitoring a communicator or not.


int MPI_Ssend(void *buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm)
{
  int ret;

  ret = PMPI_Ssend(buf, count, datatype, dest, tag, comm);

  if ( comm == MPI_COMM_WORLD )
    {
      /* send information to the Interface */
    }

  return ret;
}

Registering Communicators


Registering from the user side


A mechanism has to be create to allow the user to register and unregister communicators at will. Few functionalities are visible from the user side:

  • is a communicator registered?
  • register a communicator
  • unregister a communicator

Resulting in the following functions:

int Comm_is_registered(MPI_Comm comm);
int Comm_register(MPI_Comm comm, char* name);
int Comm_unregister(MPI_Comm comm);

When a user registers a communicator, a name is given, and this name is displayed in the Interface as the communicator name. By default MPI_COMM_WORLD is registered when the application starts, but further options may add the possibilities to avoid doing so.

Each communicator will have a unique identifier (an unsigned integer) that will be sent to the Interface. For each communicator sent to the interface this identifier will be given, allowing the GUI to sort information by communicator when needed.


Registering: use in the profiling interface


The actual registration is done via a linked list. When the user registers a communicator, the list is searched for it, and if it is not present, added. When a MPI call is processed, the list is searched as well, and if the communicator isn't present, no information is sent to the Interface. The MPI profiling function now looks like following.


int MPI_Ssend(void *buf, int count, MPI_Datatype datatype, int dest, int tag, MPI_Comm comm)
{
  int ret;
  Register_Comm* commInfo = NULL;

  commInfo =  Comm_register_search(comm);

  ret = PMPI_Ssend(buf, count, datatype, dest, tag, comm);

  if ( commInfo )
    {
        /* send information to the Interface */
    }

  return ret;
}

Registering a communicator: internals



Communicator cells struct diagram

Registering a communicator looks relatively easy. The class diagram is relatively simple, though it is a double linked list (linking previous and next cells).


The MPI_Comm datatype could be considered as a simple int or long int as it represents the address of a communicator internally. In OpenMPI it is a structure. In MPICH2 it is defined as an int. Therefore a comparison like follows works.

int compare(MPI_Comm a, MPI_Comm b)
{
   return a == b;
}


Using MPI_Comm_compare


But comparing the datatype itself isn't very portable. The goal of that tool is to work with the MPI standard, not really using tricks from implementations to implementations. A function exists to compare two communicators: MPI_Comm_compare. According to the standard it returns:

  • MPI_IDENT results if and only if comm1 and comm2 are handles for the same object (identical groups and same contexts).
  • MPI_CONGRUENT results if the underlying groups are identical in constituents and rank order; these communicators differ only by context.
  • MPI_SIMILAR results of the group members of both communicators are the same but the rank order differs.
  • MPI_UNEQUAL results otherwise.


while ( curr != NULL )
    {
      MPI_Comm_compare(curr->comm, comm, &res);

        switch(res)
        {
        case MPI_IDENT:
            fprintf(stderr, "got MPI_IDENT\n");
            break;
        case MPI_CONGRUENT:
            fprintf(stderr, "got MPI_CONGRUENT\n");
            break;
        case MPI_SIMILAR:
            fprintf(stderr, "got MPI_SIMILAR\n");
            break;
        case MPI_UNEQUAL:
            fprintf(stderr, "got MPI_UNEQUAL\n");
            break;
        }

   curr = curr->next;
}


Using Communicators attributes


In order to go further, the user should be able to register a communicator for some time, and then unregister it. But just maintaining a list of currently registered communicator, if an unregistered communicator is registered again, it will become a new communicator.



This behaviour could be avoided. Firstly a list "communicator registered in the past" could be created, and each time a communicator is created, a search is performed. This isn't a bad option as usually few communicators are used, but isn't very interesting in term of performance. The MPI standard defines attributes that can be attached to an object. In that case an attribute could be created when registering the communicator (storing its unique ID for instance). This attribute could be looked for just before the insertion in the list, and if it exists, retrieve the unique ID from it.


Conclusion and limitations


The simple mechanism (comparing as int) is used effectively to search through registered communicators, and be able to add/remove communicators. But a more portable way will be used in the future, in order to complain with the standard rather than adapting to implementors versions. The actual "retrieving" of information from a deleted communicator isn't implemented yet, and will certainly be useful for watching a particular moment of a code rather than the whole MPI program without creating a lot of communicators in the Interface.

Monday, 30 May 2011

Meeting 6 [25/05] and how to use the tool

The meeting


Even thought a month came by, few new functionalities appeared into the project. Firstly because it was revision and examination period. During that period effort was made to insure the continuation of the project as design and researches. Some ideas on how to implement the synchronisation and possible functionalities were discuss (like the communicator registration).

The next step is to generate documentation for the project, as a proper webpage (and because some part of the code isn't much commented - as it was evolving quickly). Effort has to be make to make the project's folder organised. And some implementation will be carried on:

  • communicator registration, to organise the MPI_Request saving
  • syncrhonous communication (wait for the user to click continue before actually performing the MPI function


Was already in place the basis to do both implementation (MPI_Request are saved into a linked list and the backbone of the synchronisation is implemented - but not functional).

Using the tool


This tool aims to help people learning MPI behaviour. The sources have therefore been open to the "public". The first attempt was on an internal machine - Ness - that didn't work correctly. Therefore the project will be registered on source-forge, as it was planned, in advance.


This part is to explain how to use the current version of the code, and shouldn't change much in the future releases.

The project is composed of a library - the profiler - and an executable - the interface. The project should be organised into folders, one per deliverable. And should include tests. A general Makefile should be available to compile each of the deliverable, and a configure script may be available to automatise the variable generation (installation path, MPI flags to compile from the MPI compilers, Qt path, ...).

Compiling the profiler


Compiling the profiler requires:

  • a C MPI implementation
  • a C compiler
The profiler is available in both static or dynamic linking format, as only the linking stage changes. It is important for the user to be able to choose one or the other, as it appeared some MPI installation do not accept another type of library to use the MPI profiling interface.


Either mode could be compiled and installed, but note that if both are installed, it appears that dynamic linking is used by default.


Running make static or make dynamic should compile and install the library, by default in a local install folder composed of the classical lib and includes folders.


Compiling the interface


Compiling the interface requires:

  • Qt 4.6 or later (note that Qt 4.7 was used but none of the used functionalities where introduced on that release).
  • an C++ MPI implementation that supports multi-threading (see a previous note).
  • a C++ compiler
  • the headers from the profiler
The interface should be compilable from the main Makefile. A typical Qt project needs a project file to be generated that will generate the Makefile to compile it. Normally this process should be automatic, as the main Makefile should do so. If a configure script is available it should handles the variable generation, otherwise some variable needs to be set up:

  • INSTALL_ROOT should contains the path to the installation folder (default: ../install as it is relative to the interface folder where it is built).
  • MPI_INCLUDE should contain the path to the MPI headers. It can be retrieved by using mpicc -showme and is generally like -I/usr/local/include. However the -I should be REMOVED from the project option as QMake will generate it automatically.
  • MPI_LINK should contain the linking options given by mpicc -showme and is generally like -pthread -L/usr/local/lib -lmpi_cxx -lmpi -lopen-rte -lopen-pal -ldl -Wl,--export-dynamic -lnsl -lutil -lm -ldl.
  • MPI_EXTRA_FLAGS should be set up to -DMPICH_IGNORE_CXX_SEEK when using MPICH2 to avoid conflict with standard C++ file handling.

When the project file is done, and named as mpidisplay.pro, running make display should take care of the 2 compilation steps and of the installation. Nonetheless the steps are:
  • The generation of the Makefile qmake mpidisplay.pro. You can specify the previously stated variables in the command line or in the file itself (example: qmake mpidisplay.pro INSTAL_ROOT=../install).
  • Compiling the executable with the generated Makefile: make -f Makefile.qt
  • Installing the executable is done by calling make -f Makefile.qt install


Using a MPI program with the library


Compiling


In order to compile the library with the profiler options, you need to know where the profiler library is installed. Let's assume ~/local/, meaning that the library is in ~/local/lib and the headers in ~/local/includes. The location of the mpidisplay interface isn't important yet, but it certainly in ~/local/bin.


Note that to compile - even as a dynamic library - you do not need the LD_LIBRARY_PATH to be updated, but you will need it to run the software later. You don't need to update the variable if you use static linking as the library is completely added to your executable. To set the path simple execute export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:~/local/lib in your shell - or add it to your bashrc file.


Compiling your program is done exactly the same way than any other MPI program with additional library. You need to add the headers path to the compiler flags and the library location and name to the linking flags. In a generic Makefile this is done by adding CFLAGS+=-I~/local/includes and LDFLAGS+=-L~/local/lib -lmpi_wrap.


The only source modification is then to add to your code files:

#include <mpi_wrap.h>
In theory you can even remove the flags if you don't want to use the library, but be aware that the compiler might complain about not finding "mpi_wrap.h". Therefore you can define a precompiler macro WITH_MPIWRAP by adding CFLAGS+=-I~/local/includes -DWITH_MPIWRAP and doing your include as
#ifdef WITH_MPIWRAP
#include <mpi_wrap.h>
#endif


Running


As stated before your LD_LIBRARY_PATH should be updated if you are using a dynamic linking. Otherwise simply run your MPI program as usual. Assuming your program executable is called ring you usually ran mpiexec -n 4 ring to run with 4 MPI processes. With the library it is the same!

The profiler library will write the port on the standard output by default. But you can add command line arguments to define another way:

  • Standard output with --port-in-stdout
  • Standard error output with --port-in-stderr
  • A text file with --port-in-file file


Start the interface



Starting message box of the interface (GNU/Linux Gnome 3)

In order to start the mpidisplay interface you need to add its location to the PATH with the same technique than the LD_LIBRARY_PATH: export PATH=$PATH:~/local/bin. Then simply run mpidisplay to see the connection window. If you exported the port on the standard output move to the "manual" tab and write the ports in the fields. You can change the number of processors in the list - and the order of the port does not matter. If you used a text file, click the button and select it; the ports information will be loaded on the text edit area underneath if you need edition (and the number of processors should be updated).

Then simply click OK to start the interface.


You can find for the moment 2 main information in the interface: the number of calls to a sample of MPI routines and the time spent in them.



Wednesday, 30 March 2011

The tests programs

During the 1st semester, in the Message Parsing Programming lectures, EPPC staff taught us how to use the basic features of MPI, and how to avoid some mistakes. For this project some example will be reused to insure that both the profiler and display work correctly

The Message in a Ring



The message in a ring is a simple MPI program where each process sends data to the next one and receive therefore from the previous one. This program was developed to investigate the difference between the several send and receive possibilities proposed by the MPI standard:


  • Asynchronous send ; receive ; wait for the send
  • Asyncrhonous receive ; send ; wait for receive
  • Use of the special send and receive function

This code can be used as an example of real time communication, and checking on waiting for communications.

Calculating PI


The calculating PI was an exercise where each processor was computing a part of PI and then a reduction is done to add the results together. The goal was to illustrate the possible rounding errors when the sum wasn't done in the same order. In order to avoid it, an array was made on the master processor to store each result and do the sum in the end.

This code can be used to show a very simple data registering (float).

The traffic model


The traffic model simulation was a simple domain decomposition model, where a process can have several cells of road. Each cell can be either occupied or empty. A car moves to an empty cell forward to it. Therefore some communication has to be made to send cars across the neighbour processors: check if the next cell is empty (a very simple 1D hallow swapping).

The casestudy and coursework


The idea was to introduce a very simple reverse edge detection algorithm. The solution is quite computing intensive as a smooth operation has to be made several time in order to obtain the original picture. Therefore a simple domain decomposition was done on 1 of the dimension to share the work among processors.

This code involves typical hallo swapping and the use of MPI datatypes.

The coursework introduces a 2D domain decomposition. Making it more complex to share data with the neighbours processes.

Saturday, 26 March 2011

Meeting 3 and 4 [21/02 and 14/03]

During the month of March the deadline for the Project Preparation report and presentation. The goal of this module was to justify the research done and to prove the feasibility of the project.


During the 3rd meeting the MPI socket organisation was presented to David, showing a new orientation of the communication. Mainly the discussion was about the report, and what to write in it.

But also a set of tests, from the earlier MPI course, was discussed, including 3 simple codes and 1 more complex one:

  • calculating PI
  • A message in a ring
  • The traffic model
With the willing to be able to use the MPI casestudy and its evolution: the coursework. This last was about an image computing. All tests will be discuss later in this blog.

The main features for the software are the communication information (general statistics to find missing calls to MPI_Wait for example), the data display to show what data are sent and where they are stored to. Finally the last feature is a synchronised view of the communication, equivalent to a step by step action in a debugger, but at a MPI call level rather than a C or assembly one.


Few innovations were made for the 4th meeting. The report was due few days after. Nonetheless some goals were discuss. The project will provide a framework composed of a library (the profiler part) and an executable (the interface). The goal is to provide a real time global view of the program and it aims modest MPI programs with few processes. As it is only an information tool no performance is needed, but effort will be made to insure at least memory management.

Tuesday, 15 February 2011

A bit of software engineering

This article will only details some changes on the code done in order to have a more adaptable test software. It will also explain how to use the library with an MPI program in C.


The Project


The project is so far organised around 2 things: the profiler and the display. The profiler is produced as a library, that patches some of the MPI calls. The display is an executable that only displays information from the profiler.

The current directory architecture reflects that organisation, where the display is actually in a subdirectory of the profiler (the interface one).

When build 3 folders are created;

  • dynamic containing the library as a .so - or static with the .a
  • includes which contains the header to add to the MPI executable you want to use with the profiler (the mpi_wrap.h file is the one, the intra_comm.h just defines some of the way for the display and profiler to communicate and can be used later on to develop another display)
  • display that obviously is the folder where the display executable is stored.

The actual profiler is done in C, and therefore uses MPICC (on my machine GCC - No build was really done on Ness, as for the moment Qt isn't installed on it).

The display is implemented in C++ using both Qt and MPI and uses the powerful .pro files to handle compilation.


The profiler


The profiler is organised so far around:

  • mpi_basic.c and mpi_communication.c that implements the MPI functions defined in mpi_wrap.h.
  • child_comm.c, child_comm.h and intra_comm.h that implements the profiler/display communication.

MPI overloading


Only the defined function in mpi_wrap.h are overloaded, and this is so far the only file that has to be included from the original MPI program. Each of the function will call some of the child_comm module to communicate with the child, and the user doesn't have to bother with them.


The child_comm module


Actually very few type of communication is required with the display. The header is rather small:


child_comm.h

#ifndef CHILDCOMM
#define CHILDCOMM

int start_child(char* command, char* argv[]);
int alive_child();
int sendto_child(char* mess);
int wait_child(char* mess);

#endif // CHILDCOMM

  • start_child starts the child, and therefore is called in MPI_Init()
  • sendto_child sends information to the child, the message is of a defined size in intra_comm.h
  • wait_child is to wait for the child death (i.e. be sure he received every information before closing communication) and is thus called in MPI_Finalize()
  • aline_child() return either SUCCESS or FAILURE (defined in intra_comm.h) to inform that the child is still running or not.

Such approach allows different way of communication with the child without affecting directly the MPI overloaded functions and vice versa.


The display


The display is developed using the Qt library, and uses a classical directory organisation. Qt provides a excellent tool, qmake, to generate Makefiles from a project file (here mpidisplay.pro) and will adapt to it. From a platform to another just minor modification have to be made on the file, such as the 2 first lines that defines MPICC flags. Note that Qt uses GCC as a compiler.


Extract of the mpidisplay.pro

# using 'mpicxx -showme:compile' and 'mpicxx -showme:link'
MPICXX_COMPILE = -I/usr/local/include -pthread
MPICXX_LINK = -pthread -L/usr/local/lib -lmpi_cxx -lmpi -ldl -Wl,--export-dynamic -lnsl -lutil -lm -ldl

Qt provides also a good interface designer, that will be used to generate the GUI, and the forms generated are stored in the forms folder. The src folder contains the sources.


The code organisation


The display code is organised around 2 classes so far:

  • MPIWatch that is implemented as a singleton and is the only one to deals with MPI communication (i.e. communicates with the profiler). It therefore uses some information from intra_comm.h.

    It is inheriting from the QThread class, that is a portable thread for Qt (using pthreads on Unix certainly) and allows communication and display actualisation to be separated.

    The communication with the other class is done through Qt internals signals, that are kind of remote calls. When a message is received from the profiler, it is stored on a message stack, and the signal newMessage() is emitted.
  • CommStat that is a classical QWidget displaying basic information on the number of sends and receives. It pops information from the MPIWatch object each time this one signals a new message.

How to use the mpi_wrap library?


Using the library is a very easy, and standard.

  • Add the #include line to the code that uses MPI.
  • Compile the files with the path of the include files (usually -I)
  • Link the executable with the path of the library, and the library name (usually -L and -libmpi_wrap).


Example in a Makefile

# path where the library is installed
MPI_WRAPPER = /home/workspace/project/current
# linking is either static or dynamic, will look in $MPI_WRAPPER/$linking
linking = dynamic

DEFINES+=
CC= mpicc
CFLAGS= -g $(DEFINES) -I${MPI_WRAPPER}/includes


LFLAGS= -lm -L${MPI_WRAPPER}/$(linking) -lmpi_wrap

EXE= ring

SRC= ring.c

OBJ= $(SRC:.c=.o)

.c.o:
$(CC) $(CFLAGS) -c $<

all: $(EXE)

$(EXE): $(OBJ)
$(CC) $(CFLAGS) -o $@ $(OBJ) $(LFLAGS)
@echo "don't forget export LD_LIBRARY_PATH='$(MPI_WRAPPER)/$(linking)'"
@echo "don't forget to add $(MPI_WRAPPER)/display to the PATH!"

clean:
rm -f $(OBJ) $(EXE)

The sources


The sources are available on http://www.megaupload.com/?d=DDUQP5QH.

Saturday, 12 February 2011

Tackling C++ from C

Why using both C and C++ in a single program when MPI provides C++ wrapper? Well first of all, most of the scientific program are either written in C or Fortran. Thus providing a C++ limited library is somewhat not in the score of the project. Then finding a solution that could provide a liberty of using C or Fortran for the MPI profiling interface (called the profiler) and any other language or library for the interface (called display) is, to my point of view, a good approach.


At the current state of the project, the profiler is written in C - and it will certainly be written only in C for the whole project - and the interface has to written using the Qt C++ library. The problem is therefore to call the corresponding C++ method when a MPI called is handled - hence calling C++ from C.


The first approach was to try to bind C++ in C, and was a big failure. The code was a simple function call (not even a method from an object) and it didn't link properly. Therefore a more modular solution had to be found.


Having a separate software for the profiler and the display is certainly the key to the problem. Hence it therefore requires another way of communication than simple function calls. MPI provides functions to spawn another process. It also provides socket handling.

During next week I will try to use both of the solution and try to choose between them.


A client and a server


The typical communication with sockets can be achieved with a client-server communication. The display will be a server, and the profiling interface will connect on it, and send information.

In order to provide a display per profiler, several interface will be started, each of them on a port. The obvious idea is to use a "base" port (say 4242) and to add the MPI process rank to find which port to use for communication. Thus on a 4 process job, 4 display will start, each of them listening on either 4242, 4243, 4244, 4245. Then the profilers will try to connect to one of them, according to their rank.

Using socket should be easy enough from MPI and Qt, as both libraries provide a "high" level interface.


The obvious advantage of such approach is the total independence of both software. One can communicate with another through a defined protocol without any trouble. It also allows the profiler to be in any language, and the display to be rewritten at wish - to display more specific information or using another library/language.

The obvious disadvantage is the opening of several ports, that might be troublesome on some restricted networks. A communication protocol has to be written as well, but it is also part of the other approach.


Spawning the display


Spawning the display is basically starting another process from the profiler. The display will hence be a totally different program, but it will be possible to communicate through a special MPI communicator given during the spawning process.

The difficulty of that approach lies in the spawning idea. As the 2 processes are tight together, if one of them dies (from an error, or simply because the display is closed) the ORTE (the deamon that manages MPI communication with OpenMPI - and MPICH2 must have something similar) will kill the other process. Therefore there is no real clean way of exiting both of the program.

Moreover the display program should be either accessible from the PATH or the profiler has to have a way to find where it is stored.


Hence the advantages are on the communication point of view. Both use MPI to communicate, that is rather simple and tackle the port problem.