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The programming environment of GALILEO consists of a choice of compilers for the main scientific languages (Fortran, C and C++), debuggers to help users in finding bugs and errors in their codes, profilers to help with code optimization. In general, you must also "load" also the correct environment for using programming tools like compilers, since "native" compilers are not available.

If you use a given set of compilers and libraries to create your executable, you will likely have to define the same "environment" when you want to run it. This is because, since by default linking is dynamic on Linux systems, at runtime the application will need the compiler shared libraries as well as other proprietary libraries. This means that you have to specify "module load" for compilers and libraries, both at compile time and at run time. If you prefer to minimize the number of needed modules at runtime, use static linking to compile the applications.

Compilers

You can check the complete list of available compilers on GALILEO with the command:

> module available

and you can check checking the "compilers" section from there.

In general, the available compilers are:

  • INTEL (ifort, icc, icpc) : ► module load intel
  • PGI - Portland Group (pgf77,pgf90,pgf95,pghpf, pgcc, pgCC): ► module load pgi (profile/advanced)
  • GNU (gcc, g77, g95): ► module load gnu

After loading the appropriate module, use the "man" command to get the complete list of the flags supported by the compiler, for example:

> module load intel
> man ifort

There are some flags that are common for all these compilers. Others are more specific. The most common are reported later for each compiler.

  1. If you want to use a specific library or a particular include file, you have to give their paths, using the following options
-I/path_include_files        specify the path of the include files
-L/path_lib_files -l<xxx>    specify a library lib<xxx>.a in /path_lib_files
  1. If you want to debug your code you have to turn off optimisation and turn on run time checkings: these flags are described in the following section.
  2. If you want to compile your code for normal production you have to turn on optimization by choosing a higher optimization level
-O2 or -O3      Higher optimisation levels

Other flags are available for specific compilers and are reported later.

INTEL Compiler

Intel family compiler suite is recommended on GALILEO, since the architecture is based on Intel processors and therefore using the Intel compilers may result in a significant improvement on in performance and stability of your code. Initialize the environment with the module command:

> module load intel

The names of the Intel compilers are:

  • ifort: Fortran77 and Fortran90 compiler
  • icc: C compiler
  • icpc: C++ compiler

The documentation can be obtained with the man command after loading the relevant module:

> man ifort
> man icc

Some miscellanous miscellaneous flags are described in the following:

-extend_source    Extend over the 77 column F77's limit
-free / -fixed    Free/Fixed form for Fortran
-ip               Enables interprocedural optimization for single-file compilation
-ipo              Enables interprocedural optimization between files - whole program optimisation


PORTLAND Group (PGI)

Initialize the environment with the module command:

> module load profile/advanced
> module load pgi

The name of the PGI compilers are:

  • pgf77: Fortran77 compiler
  • pgf90: Fortran90 compiler
  • pgf95: Fortran95 compiler
  • pghpf: High Performance Fortran compiler
  • pgcc: C compiler
  • pgCC: C++ compiler

The documentation can be obtained with the man command after loading the relevant module:

> man pgf95
> man pgcc

Some miscellanous miscellaneous flags are described in the following:

-Mextend            To extend over the 77 column F77's limit
-Mfree / -Mfixed    Free/Fixed form for Fortran
-fast               Chooses generally optimal flags for the target platform
-fastsse            Chooses generally optimal flags for a processor that supports SSE instructions


GNU compilers

The gnu compilers are always available but they are not the best optimizing compilers, expecially especially for an Intel-based cluster like GALILEO. The default version is 4.8.25, you do not need to load the module for using it.

For a more recent version of the compiler, initialize the environment with the module command:

> module load gnu

The name of the GNU compilers are:

  • g77: Fortran77 compiler
  • gfortran: Fortran95 compiler
  • gcc: C compiler
  • g++: C++ compiler

The documentation can be obtained with the man command:

> man gfortan
> man gcc

Some miscellanous miscellaneous flags are described in the following:

-ffixed-line-length-132       To extend over the 77 column F77's limit
-ffree-form / -ffixed-form    Free/Fixed form for Fortran


Debuggers and Profilers

If your code aborts at runtime, there may be a problem with it. In order to solve it, you can decide to analyze the core file (feature not available if the code is compiled with PGI) or to run your code using a debugger.

Compiler flags

In both cases, you need to enable compiler runtime checks, by putting specific flags during the compilation phase. In the following we describe those flags for the different Fortran compilers: if you are using the C or C++ compiler, please keep in min mind that the flags may differ.

The following flags are generally available for all compilers and are mandatory for an easier debugging session:

-O0     Lower level of optimisation
-g      Produce debugging information

Other flags are compiler-specific and are described in the following.

INTEL Fortran compiler

The following flags are useful (in addition to "-O0 -g") for debugging your code:

-traceback        generate extra information to provide source file traceback at run time
-fp-stack-check   generate extra code to ensure that the floating-point stack is in the expected state
-check bounds     enables checking for array subscript expressions
-fpe0             allows some control over floating-point exception handling at run-time

PORTLAND Group (PGI) Compilers

The following flags are useful (in addition to "-O0 -g") for debugging your code:

-C                     Add array bounds checking
-Ktrap=ovf,divz,inv    Controls the behavior of the processor when exceptions occur: 
                       FP overflow, divide by zero, invalid operands

GNU Fortran compilers

The following flags are useful (in addition to "-O0 -g") for debugging your code:

-Wall             Enables warnings pertaining to usage that should be avoided
-fbounds-check    Checks for array subscripts.



In the following we report informations about some ways to debug your codes:

PGI: pgdbg (serial/parallel debugger)

pgdbg is the Portland Group Inc. symbolic source-level debugger for F77, F90, C, C++ and assembly language programs. It is capable of debugging applications that exhibit various levels of parallelism, including:

  • Single-thread, serial applications
  • Multi-threaded applications
  • Distributed MPI applications
  • Any combination of the above

There are two forms of the command used to invoke pgdbg. The first is used when debugging non-MPI applications, the second form, using mpirun, is used when debugging MPI applications:

> pgdbg [options] ./myexec [args]
> mpirun [options] -dbg=pgdbg ./myexec [args]

More details in the on line documentation, using the "man pgdbg" command after loading the module.

To use this debugger, you should compile your code with one of the pgi compilers and the debugging command-line options described above, then you run your executable inside the "pgdbg" environment:

> module load profile/advanced
> module load pgi > pgf90 -O0 -g -C -Ktrap=ovf,divz,inv -o myexec myprog.f90 > pgdbg ./myexec

By default, pgdbg presents a graphical user interface (GUI). A command-line interface is also provided though through the "-text" option.

GNU: gdb (serial debugger)

GDB is the GNU Project debugger and allows you to see what is going on 'inside' your program while it executes -- or what the program was doing at the moment it crashed.

GDB can do four main kinds of things (plus other things in support of these) to help you catch bugs in the act:

  • Start your program, specifying anything that might affect its behavior.
  • Make your program stop on specified conditions.
  • Examine what has happened, when your program has stopped.
  • Change things in your program, so you can experiment with correcting the effects of one bug and go on to learn about another.

More details in the on line online documentation, using the "man gdb" command.

To use this debugger, you should compile your code with one of the gnu compilers and the debugging command-line options described above, then you run your executable inside the "gdb" environment:

> module load gnu
> gfortran -O0 -g -Wall -fbounds-check -o myexec myprog.f90
> gdb ./myexec

VALGRIND

Valgrind is a framework for building dynamic analysis tools. There are Valgrind tools that can automatically detect many memory management and threading bugs, and profile your programs in detail. The Valgrind distribution currently includes six production-quality tools: a memory error detector, two thread error detectors, a cache and branch-prediction profiler, a call-graph generating cache profiler, and a heap profiler.

Valgrind is Open Source / Free Software, and is freely available under the GNU General Public License, version 2.

To analyse a serial application:

  1. Load Valgrind module --> module load valgrind
  2. Load module for the compiler and compile your code with the compiler you prefer (Use -O0 -g flags)
  3. Run the executable under Valgrind.  

    If you normally run your program like this:

      myprog arg1 arg2
    

    Use this command line:

      valgrind  (valgrind-options) myprog arg1 arg2 

    Memcheck is the default tool. You can add the --leak-ceck option that turns on the detailed memory leak detector. Your program will run much slower  than normal, and use a lot more memory. Memcheck will issue messages about memory errors and leaks that it detects.

To analyse a parallel application:
  1. Load Valgrind module --> module load valgrind
  1. Load modules for compiler and openmpi libraries (at present only available for intel and gnu)
  2. Compile your code with the "-O0 -g" flags both at compiling and linking time
  3. Run the executable under Valgrind (both in interactive than in bacth mode)
  mpirun -np 4 valgrind (valgrind-options) myprog arg1 arg2

Core file analysis

In order to understand what problem was affecting you code, you can also try a "Core file" analysis. Since core files are usually quite large, be sure to work in the /scratch area.

There are several steps to follow:

  1. Increase the limit for possible core dumping


Core file analysis

In order to understand what problem was affecting your code, you can also try a "Core file" analysis. Since core files are usually quite large, be sure to work in the /scratch area.

There are several steps to follow:

  1. Increase the limit for possible core dumping
> ulimit -c unlimited (bash)
> limit coredumpsize unlimited (csh/tcsh)
  1. If you are using Intel compilers, set to TRUE the decfort_dump_flag environment variable
> export decfort_dump_flag=TRUE  (bash)       
> setenv decfort_dump_flag TRUE  (csh/tcsh)
  1. Compile your code with the debug flags described above.
  2. Run your code and create the core file.
  3. Analyze the core file using different tools depending on the original compiler.

INTEL compilers

> module load intel
> ifort -O0 -g -traceback -fp-stack-check -check bounds -fpe0 -o myexec prog.f90
> ulimit -c unlimited
(bash)

> 
limit coredumpsize unlimited (csh/tcsh) If you are using Intel compilers, set to TRUE the 
export decfort_dump_flag
 environment variable
=TRUE
> ./myexec
> ls -lrt
  -rwxr-xr-x 1 aer0 cineca-staff   9652 Apr  6 14:34 myexec
  -rw------- 1 aer0 cineca-staff 319488 Apr  6 14:35 core.25629
> idbc ./myexec core.25629

PGI

> export decfort_dump_flag=TRUE  (bash)       
> setenv decfort_dump_flag TRUE  (csh/tcsh)
  1. Compile your code with the debug flags described above.
  2. Run your code and create the core file.
  3. Analyze the core file using different tools depending on the original compiler.
for INTEL

compilers

> module load 
intel
profile/advenced
> module load pgi >
ifort
pgf90 -O0 -g -
traceback -fp-stack-check -check bounds -fpe0 -
C -Ktrap=ovf,divz,inv  -o myexec 
prog
myprog.f90
> ulimit -c unlimited
> 
export decfort_dump_flag=TRUE >
./myexec
> ls -lrt
  -rwxr-xr-x 1 aer0 cineca-staff   9652 Apr  6 14:34 myexec
  -rw------- 1 aer0 cineca-staff 319488 Apr  6 14:35 core.
25629
25666
>
idbc
 pgdbg -text -core core.25666 ./myexec 
core.25629

for PGI compilers

> module load profile/advenced

GNU Compilers

> module load 
pgi
gnu
>
pgf90
gfortran -O0 -g -
C
Wall 
-Ktrap=ovf,divz,inv
-fbounds-check -o myexec 
myprog
prog.f90
> ulimit -c unlimited
> ./myexec
> ls -lrt
  -rwxr-xr-x 1 aer0 cineca-staff   9652 Apr  6 14:34 myexec
  -rw------- 1 aer0 cineca-staff 319488 Apr  6 
14:35 core.25666 > pgdbg -text -core core.25666 ./myexec

for GNU Compilers

> module load gnu
> gfortran -O0 -g -Wall -fbounds-check -o myexec prog.f90 > ulimit -c unlimited > ./myexec > ls -lrt -rwxr-xr-x 1 aer0 cineca-staff 9652 Apr 6 14:34 myexec -rw------- 1 aer0 cineca-staff 319488 Apr 6 14:35 core.25555
14:35 core.25555
> gdb ./myexec core.2555


VALGRIND

Valgrind is a framework for building dynamic analysis tools. There are Valgrind tools that can automatically detect many memory management and threading bugs, and profile your programs in detail. The Valgrind distribution currently includes six production-quality tools: a memory error detector, two thread error detectors, a cache and branch-prediction profiler, a call-graph generating cache profiler, and a heap profiler.

Valgrind is Open Source / Free Software, and is freely available under the GNU General Public License, version 2.

To analyse a serial application:

  1. Load Valgrind module --> module load valgrind
  2. Load module for the compiler and compile your code with the compiler you prefer (Use -O0 -g flags)
  3. Run the executable under Valgrind.  

    If you normally run your program like this:

      myprog arg1 arg2
    

    Use this command line:

      valgrind  (valgrind-options) myprog arg1 arg2 

    Memcheck is the default tool. You can add the --leak-ceck option that turns on the detailed memory leak detector. Your program will run much slower  than normal, and use a lot more memory. Memcheck will issue messages about memory errors and leaks that it detects.

To analyse a parallel application:
  1. Load Valgrind module --> module load valgrind
  2. Load modules for compiler and openmpi libraries (at present only available for intel and gnu)
  3. Compile your code with the "-O0 -g" flags both at compiling and linking time
  4. Run the executable under Valgrind (both in interactive than in batch mode)
  mpirun -np 4 valgrind (valgrind-options) myprog arg1 arg2
> gdb ./myexec core.2555

Totalview
Totalview is a parallel debugger with a practical GUI that assist users to debug their parallel code. It has functionalities like stopping and reprising a code mid-run, setting breakpoints, checking the value of variables anytime, browse between the different tasks and threads to see the different behaviours, memory check functions and so on. For informations about how to run the debugger (by connecting the compute nodes to your display via RCM), type the command:

> module help totalview

Profilers (gprof)

In software engineering, profiling is the investigation of a program's behaviour using information gathered as the program executes. The usual purpose of this analysis is to determine which sections of a program to optimize - to increase its overall speed, decrease its memory requirement or sometimes both.

A (code) profiler is a performance analysis tool that, most commonly, measures only the frequency and duration of function calls, but there are other specific types of profilers (e.g. memory profilers) in addition to more comprehensive profilers, capable of gathering extensive performance data.

gprof

The GNU profiler gprof is a useful tool for measuring the performance of a program. It records the number of calls to each function and the amount of time spent there, on a per-function basis. Functions which consume a large fraction of the run-time can be identified easily from the output of gprof. Efforts to speed up a program should concentrate first on those functions which dominate the total run-time.

gprof uses data collected by the -pg compiler flag to construct a text display of the functions within your application (call tree and CPU time spent in every subroutine). It also provides quick access to the profiled data, which let you identify the functions that are the most CPU-intensive. The text display also lets you manipulate the display in order to focus on the application's critical areas.

Usage:

>  gfortran -pg -O3 -o myexec myprog.f90
> ./myexec
> ls -ltr
   .......
   -rw-r--r-- 1 aer0 cineca-staff    506 Apr  6 15:33 gmon.out
> gprof myexec gmon.out

It is also possible to profile at code line-level (see "man gprof" for other options). In this case you must use also the “-g” flag at compilation time:

>  gfortran -pg -g -O3 -o myexec myprog.f90
> ./myexec
> ls -ltr
   .......
   -rw-r--r-- 1 aer0 cineca-staff    506 Apr  6 15:33 gmon.out
> gprof -annotated-source myexec gmon.out


It is possible to profile MPI programs. In this case, the environment variable GMON_OUT_PREFIX must be defined in order to allow to each task to write a different statistical file. Setting

export GMON_OUT_PREFIX=<name>

 once the run is finished each task will create a file with its process ID (PID) extension

<name>.$PID

 If the environmental variable is not set every task will write the same gmon.out file.

Scientific libraries (MKL)

MKL

The Intel Math Kernel Library (Intel MKL) enables improving performance of scientific, engineering, and financial software that solves large computational problems. Intel MKL provides a set of linear algebra routines, fast Fourier transforms, as well as vectorized math and random number generation functions, all optimized for the latest Intel processors, including processors with multiple cores.

Intel MKL is thread-safe and extensively threaded using the OpenMP technology.

documentation can be found by loading the mkl module and searching in the directory:

${MKLROOT}/../Documentation/en_US/mkl

To use the MKL in your code you to load the module, then to define includes and libraries at compile and linking time:

> module load mkl
> icc -I$MKL_INC -L$MKL_LIB  -lmkl_intel_lp64 -lmkl_core -lmkl_sequential

For more informations please refer to the documentation.

...

IntelMPI in GALILEO is recommended , , since the architecture is based on Intel processors.
To load IntelMPI on GALILEO, check the module versions available with the "module avail" command, then load the relevant module:. After you have loaded the Intelmpi module
> mpiifort > module avail intelmpi
intelmpi/2018--binary

> module load autoload intelmpi/2018--binary
> man mpiifort
> mpiifort -o myexec myprof.f90 (uses the ifort compiler)

For more option of the compiler, please see

> man mpiifort

The three main parallel-MPI commands for compilation with OpenMPI are:

...

On GALILEO, "gnu" versions of OpenMPI are available. To load it, After  you have load the openmpi module (check the names available version with the "module avail" command, then load the relevant module):
> module avail openmpi
openmpi/2.1.1--gnu--6.1.0

> module load autoload openmpi/2.1.1--gnu--6.1.0
> man mpif90
> mpif90 -o myexec myprof.f90 (uses the gfortran compiler)

...

In all cases the parallel applications have to be executed with the command:

> mpirun ./myexec

or (recommended)recommended command:

> srun ./myexec 

There are limitations on running parallel programs in the login shell. You should use the "Interactive SLURM" mode, as described in the "Interactive" section, previously in this page.

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