Let's rokk! [Tudor Cret's blog]

October 24, 2008

Time for life coding…

Filed under: Others — Tudor Cret @ 10:58 pm

What happens when you realize that you have to go to the dentist ? First of all you are scared a little bit, or you have a panic attack or you simply say…NO…or you do not even want to think about it. But it comes a day when it happens to say YES. (And is not that day when you get married…). And you go the dentist, scared because of the chair and its tiny machines, the peoples in white near you…or just because of “phobic problems” . But what may happens so badly ? Watch this:

This happens, if you are Bean.

It was no surprise for me when it happened to have to go to dentist. Beware of Mr.Bean’s experience I have just imagined that I sit in F1 car, of course not an usual one…a red one… I was scared a little bit, I have to admit. But I met a wonderful and cool doctor – Dr.Razvan. He “killers” you with jokes, fun and he fills you with positive energy. Before all these he gave you a dental anesthesia in order not to be able to feel something when you laugh. It’s so cool… And in the end you will see that all your medical problems are fixed in the best professional manner, all your dental bugs are fixed, and you are  filled with a positive energy for the rest of the day. You enter at Dr.Razvan’s clinics worried about your “medical bugs” and you get out not worring anymore, just filled with positive energy and having a “bestial” job done by this cool doctor. I recommend him, it’s a great professional and a wonderful person.

Open GL

Filed under: Others — Tudor Cret @ 10:25 pm

Some days ago when I took a coffee break after a hard work at a site that will launch soon, I had the pleasure to be asked for a good tutorial for OpenGL. Of course that i did not resist and I start googling for a good tutrial. Ans look what I have found:
Have you noticed how most OpenGL Tutorial sites only talk about drawing and playing with triangles, quads and simple 3d objects (certainly not anything more complicated then cube) they draw using hard coded coordinates? That’s not exactly they way to go to create an impressive 3d scene that actually looks like a cool 3D game. If spinning a colored triangle is not good enough for you then you’ve come to the right place.”  And it’s right. All other tutorials talk about drawing and playing with triangles etc using hard coded coordinates. I really liked 3d coding tutorial and i recommend it, it is a first hand 3d tutorial.

 

http://www.3dcodingtutorial.com/

October 6, 2008

CCS 2003 & MS-MPI (part2)

Filed under: Parallel programming — Tudor Cret @ 11:27 pm

Now that we saw how to install and configure a Windows cluster (see part1 for instaling and configuring CCS) let’s find out more about MS-MPI and see how to run a parallel application.

Installing MS-MPI

MS-MPI is the implementation of the MPI standard, helping the users to create high performance parallel applications for Microsoft Windows Compute Cluster Server 2003. Microsoft provides a SDK, available here, that is used to create parallel applications. The Microsoft Compute Cluster Pack SDK contains executable binaries for Microsoft MPI and also headers and libraries for developing parallel applications. Also it includes API for integration with Microsoft Job Scheduler.

Download the SDK from the link provided above, 32-bit or 64-bit version and install it using the installation wizard either on a cluster or a simple machine on which a cluster behavior is simulated.

More about using CCP SDK can be found on MSDN – Using CCP.

More about MS-MPI can be found here. Also there are some MPI implementations for Microsoft .NET environment: MPI.NET and Pure MPI.NET.

Installing and enabling MPI Cluster Debugger

Visual Studio 2008 Professional Edition and Visual Studio 2008 Team System support remote debugging of applications, including parallel applications. The Visual Studio remote debugging process for a Message Passing Interface (MPI) application uses the following:

  • Msvsmon -the remote debugging monitor application of Visual Studio.
  • Smpd -the MPI daemon process. Starts mpishim.exe.
  • Mpishim -the application that connects to msvsmon.exe and that starts mpiexec.
  • Mpiexec -the MPI job launcher that starts the user’s application.

To use remote MPI debugging on a CCS cluster, you will need to perform the following tasks: 

  • MPI must be installed and configured on each node of the cluster.
  • The MPIShim.exe file must be installed on each node in the cluster, and in the same location on each node.
  • The Visual Studio Remote Debugging Monitor (msvsmon.exe) must be installed on each node in the cluster.
  • The Visual Studio host computer (the one from which you are debugging) must be set up with an account that has sufficient privileges to execute jobs on the cluster, and must be on a network segment and subnet that gives it access to the compute nodes of the cluster.

The Remote Debugging Monitor is specific to each processor architecture. It’s important that you install the x64 version. To install all the required remote debugging components, do the following at each compute node:

  • Insert the last disk of the Visual Studio 2005 installation set.
  • Navigate to the Remote Debugger\x64 folder using Windows Explorer.
  • Double-click rdbgsetup.exe to install the remote debugging components.

Debugging cluster applications

  1.Prerequisites
  • Install and configure Windows Compute Cluster 2003 as described in previous section. All services will be configured on public network, because each machine has only one network card. Let the cluster to have the following configuration:
    • Machine 1: HEADCLUSTER210 – the head node of the cluster, it is not a computational node.
    • Machine 2: CLUSTERNODE2101 – first computational node in the cluster.
    • Machine 3: CLUSTERNODE2102 – the second computational node in the cluster.
  • Check that the cluster is configured and running correctly, using Compute Cluster Administrator interface.
  • Install Microsoft Compute Cluster Pack SDK x64 version on each node, in the same location. Because CCS 2003 runs on a x64 architecture all application and processes that runs on the cluster will be x64 platform based.
  • Check that MPI services are up and running on all nodes.
  • Install Visual Studio 2008 Professional Edition or Visual Studio 2008 Team Edition on the computational nodes – CLUSTERNODE2101 and CLUSTERNODE2102 in the same location on EACH  node. Be sure that you install the extensions necessary for building x64 platform based applications. 

                           Check x64 extenstions 

  • Check that Visual Studio Remote Debugger (mpishim.exe) is installed on all nodes in the same location.
  • Modify the registry:

Cmd.exe has an issue with UNC paths.  MPI Debugging relies on these paths so just to be safe and make sure nothing breaks, carry out the following modification on each of the clusters.  Access the following registry key:

HKEY_CURRENT_USER\Software\Microsoft\Command Processor

Add a DWORD entry entitled “DisableUNCCheck” and set the value to 1:

Modify the registry

2.Running the application
  2.1.Configure a job with the Job Scheduler

If you want to have something done at the cluster for you, then you need to use the job scheduler. Be sure that you are logged in on the workstations using a domain account with administrative rights. All jobs and will have to be submitted using this account.  Debugging is no exception, as you need to create an empty job that will host the debugging application.To get started, open the Job Scheduler->File menu->Submit Job:                                                                     

Create a job on the cluster

Name the job “Debug Job” and move over to the Processors tab.  Select the number of processors you would like to use for this job and then, check the box that says “Run Job until end of run time or until cancelled”.   Failure to check this box will cause the empty job to run and finish. The job must to continually run, so that Visual Studio will then attach the running processes to this specific job.

  Select job’s running time

Move to the Tasks and add to the tasks list msvsmon.exe in order for the Visual Studio to communicate with the Visual Studio Debugger when running the parallel application.

 Add msvsmon.exe to the tasks list

Move to the Advanced tab and select which nodes will be part of your debugging scheme. In our case we will use only the twos nodes we have, but other computational nodes may be added.

 Allocate nodes for the job

Click on submit job, and the  job has to run. Write down the ID of the job (in this case, it is 16) as it will be used further.

 Running created job

   2.2.Configure Visual Studio
On CLUSTERNODE2101:
  • Open Visual Studio 2008 and create new application. See previous section “Debugging parallel applications with Visual Studio 2008″ for more detail about creating a new application.
  • Let for example the parallel value calculation of PI:

#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include “mpi.h”
int main(int argc, char *argv[])
{
      int         NumIntervals      = 0;  //num intervals in the domain [0,1] of F(x)= 4 / (1 + x*x)
      double      IntervalWidth     = 0.0;      //width of intervals
      double  IntervalLength  = 0.0;      //length of intervals
      double      IntrvlMidPoint    = 0.0;      //x mid point of interval
      int         Interval          = 0;  //loop counter
      int         done              = 0;  //flag
      double      MyPI              = 0.0;      //storage for PI approximation results
      double      ReferencePI       = 3.141592653589793238462643; //ref value of PI for comparison
      double  PI;
      char  processor_name[MPI_MAX_PROCESSOR_NAME];
      char  (*all_proc_names)[MPI_MAX_PROCESSOR_NAME];
      int         numprocs;
      int         MyID;
      int         namelen;
      int         proc = 0;
      MPI_Init(&argc,&argv);
      MPI_Comm_size(MPI_COMM_WORLD,&numprocs);
      MPI_Comm_rank(MPI_COMM_WORLD,&MyID);
      MPI_Get_processor_name(processor_name,&namelen);

      all_proc_names = malloc(numprocs * MPI_MAX_PROCESSOR_NAME);

      MPI_Gather(processor_name, MPI_MAX_PROCESSOR_NAME, MPI_CHAR, all_proc_names, MPI_MAX_PROCESSOR_NAME, MPI_CHAR, 0, MPI_COMM_WORLD);

      for (proc=0; proc < numprocs; ++proc)
            printf(“Process %d on %s\n”, proc, all_proc_names[proc]);

      while (!done) //loops until done == 0
      {
            IntervalLength = 0.0;
            if (MyID == 0){
                  printf(“\nEnter the number of intervals: (0 quits) “);
                  fflush(stdout);
                  scanf_s(“%d”,&NumIntervals);
                  //NumIntervals = 10;
            }
            MPI_Bcast(&NumIntervals, 1, MPI_INT, 0, MPI_COMM_WORLD);   /* send number of intervals to all procs */
            if (NumIntervals == 0)
                  done = 1;   //exit if number of intervals = 0 
            else
            {
                 //approximate the value of PI
                  IntervalWidth   = 1.0 / (double) NumIntervals;          
                  for (Interval = MyID + 1; Interval <= NumIntervals; Interval += numprocs){
                        IntrvlMidPoint = IntervalWidth * ((double)Interval – 0.5);
                        IntervalLength += (4.0 / (1.0 + IntrvlMidPoint*IntrvlMidPoint));
                  }
                  MyPI = IntervalWidth * IntervalLength;
                  MPI_Reduce(&MyPI, &PI, 1, MPI_DOUBLE, MPI_SUM, 0, MPI_COMM_WORLD);

                  //report approximation
                  if (MyID == 0){
                  printf(“PI is approximately %.16f, Error is %.16f\n”,
                              PI, fabs(PI – ReferencePI));
                  //done=1;
                  }
            }
      }
      MPI_Finalize();
      //printf(“Hello world”);
}

  • Go to Project->Properties (or Alt + F7).
  • In Configuration Properties tab, select Debugging under the General tab.
  • Set Debugger to Launch to property value to MPI Cluster Debugger. The next screen shot show the values of the debugger properties:

Project settings 

MPI Run Command:  mpiexec. This is required for MPI application.
MPIRun Arguments:  The first argument “-job 3.0″ is to specify which is the job in the scheduler to use.  In my case, it was 3 when I created the job, and the 0 is to specify the task, which every job has by default.   We then have “-np 2″ which is used to specify that we will be using 2 nodes for this job.  Finally you see there is “-machinefile \\kim03a\bin\machines.txt“.  The “-machinefile” is used to specfify the UNV location of a text file that contains the names of the machines that will be part of this job.  The text file should have the names of the nodes on each line. The first line should contain the machine on which is made the application debugging in order not to redirect standard console input/output. So on CLUSTERNODE2101 machines.txt will look like this:

Machine file 

The name of the machines were duplicated because the physical machines on which the cluster is deployed are dual core, and the job that runs on the cluster needs to know a name for each core.

Application Command: This is the UNV path to the MPI application that you would like to debug.  This application HAS to be compiled to 64-bit and debugging symbols should be in that same directory as well.
MPIShim Location: In this location, it is specified the path to the x64 mpishim.exe binary. Mpishim should exist on each and every one of the machines at the specified local path.
MPI network security mode: Accept connections from any address to avoid problems.

  • In order to run C code and not C++ code you have to set up the compiler to compile the code as C code and not as C++ code. For this go to C/C++ -> Advanced tab and set the value of Compile as property to Compile as C++ or Compile as C depending on the written code. For the examples presented on the MPI’s API site you need to compile the project using Compile as C.

 Set compilator for C code

  • Select Linker->General tab and set the value for Additional Library Directories to “C:\Program Files\Microsoft Compute Cluster Pack\Lib\amd64” .The path depends on the place where CCP SDK was installed on the local machine.

Add additional library directories

  • Go to Linker->Input tab and add msmpi.lib to Additional Dependencies.

Add additional msmpi.lib

  • Go to C/C++->General tab and set the value for Additional Include Directories to “C:\Program Files\Microsoft Compute Cluster Pack\Include”.

 Include additional directories

  • Select Configuration Manager in order to selectx64 platform. Choose New and select x64 platform.

 Modify application platform

  • Set the Post Build Action. The executable should be copied in the shared location on the cluster in order to be accessible to all nodes in the cluster. In this case the shared location is headcluster210\PDC

Set post build action

  • Go to Tools->Options->Debugging tab and uncheck Break all processes when one process break.
  • Build the application and resolve any kind of errors.
  • Start debugging the application. From Debug->Windows->Processes you can see the processes that currently are running.
  • The result looks like this:

 Running parallel application 

The MPI application is running parallel on the cluster. In this case there are 4 processes that are running parallel, two of them on a compute node (node 1) and the other two on the other compute node (node 2).

On CLUSTERNODE2102:
  • Copy the application created recently on the second node and the settings too
  • Modify machines.txt (or create another file). Now it looks like this:

 Machine file 

  • Build the application and resolve any kind of errors.
  • Start debugging the application. From Debug->Windows->Processes you can see the processes that currently are running.
  • The result looks like this:

 Running parallel application 

The MPI application is running parallel on the cluster. In this case there are only 3 processes that are running parallel (-np 4 was modified to -np 3), two of them on a compute node (node 2) and the other one on the other compute node (node 1).

Some common problems when debugging MPI application on a cluster and their solutions can be found here.

CCS 2003 & MS-MPI (part 1)

Filed under: Parallel programming — Tudor Cret @ 6:11 pm

Around the world the computation power increseas every day. More power is needed because the amount of data increseas exponentially. Sometimes a single computer is not enough to complete a task or a job in a decent amount of time. In the fight with the execution time we created so called super-computers and we started to write parallel applications.

Microsoft has a solution for creating a super-computer: Windows Compute Cluster Server 2003, a high performance computing cluster consisting of a head node and one or more compute nodes. CCS uses MPI standard ( MS-MPI is a version of MPI implemented by Microsoft) to run parallel applications on the cluster. It may be tricky sometimes to create parallel applications and to run them on a cluster. In the next sections I will show how to create and to run such an application on a CCS 2003 cluster. First of all let’s install and configure Windows Compute Cluster 2003.

Software requirements

Supported operating systems for head node and compute nodes:

  • Microsoft Windows Server 2003, Compute Cluster Edition
  • Microsoft Windows Server 2003, Standard x64 Edition
  • Microsoft Windows Server 2003, Enterprise x64 Edition
  • Microsoft Windows Server 2003 R2, Standard x64 Edition
  • Microsoft Windows Server 2003 R2, Enterprise x64 Edition

An overview of Windows Server 2003 x64 Editions is available here.

In addition, Windows Compute Cluster Server 2003 also requires the following:

  • Microsoft .NET Framework 2.0
  • Microsoft Management Console(MMC) 3.0 Pre-Release
  • Microsoft SQL Server 2000 Desktop Engine (MSDE) to store all job information

Network requirements

CCS 2003 supports five different cluster topologies. Each topology has implications for performance and accessibility. The topologies involve at least one and possibly three different networks: public, private, and Message Passing Interface (MPI).

  • 1. Two network adapters on the head node, one network adapter on compute node
  • 2. Two network adapters on each node
  • 3. Three network adapters on the head node, two on compute nodes
  • 4. Three network adapters on each node
  • 5. One Network Adapter Per Node

More details about system requirements and network topologies can be found here.

Install and configure CCS

Checklist used to install and configure CCS 2003:

  1. Review prerequisites and assure that the computers used to configure as cluster nodes meet the all preconditions.
  2. Create a cluster head node.
    1. Install a supported x64 edition of Windows Server.
    2. [optional]Create a second partition in order to use RIS and compute nodes automated adding.
    3. Join the head node to an Active Directory domain or use Dcpromo.exe to create one and to make the node a domain controller.
    4. Configure DNS, DHCP and other required network services for the cluster’s network.
  3. Configure the cluster head node.
    1. Start the Compute Cluster Pack Installation Wizard from the Computer Cluster Pack CD.
    2. Select “Create a new compute cluster with this server as the head node” and click next.
    3. Define the network topology. Use To Do List that is displayed in the Compute Cluster Administrator.
    4. Disable or enable firewall on the public network. Use To Do List that is displayed in the Compute Cluster Administrator.
    5. [optional] Configure RIS and RIS installation images for compute nodes.
  4. Add compute nodes to the cluster.
    1. Verify prerequisites for the machine that is going to become a compute node.
    2. Install a supported x64 edition of Windows Server.
    3. Add the compute node to the same Active Directory domain with the head node.
    4. Add the compute node to the cluster. Use the Compute Cluster Pack CD and select join this server to an existing compute cluster as node for manual addition.

More information about deploying CCS 2003 can be found here.

  Now that we have installed and configured the cluster we will see more about MPI and parallel application in part2 of this post.

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