For developing code on ada we recommend using the intel software stack, which includes the Intel compilers (icc/icpc/ifort), the Intel Math Kernel Library (MKL), and the Intel MPI. Additionally, the Intel compilers are the only compilers able to compile programs for the Phi co-processors. To load the latest (and possibly untested) Intel software stack, enter:
module load intel
However we highly recommend users select a particular toolchain and stick with modules that use it.
At present, we support the following toolchains:
- intel - described above
- iomkl - which substitutes OpenMPI for Intel's MPI
- foss - which is entirely Free and Open-Source Software (GCC/OpenMPI/BLAS/LAPACK/etc)
At present, we support the following toolchain releases:
- intel/2015B - This has evolved over the lifetime of Ada and has the most libraries presently available. Given its evolution it isn't the crispest in terms of versioning but is well tested.
- intel/2016a -This is the current development environment for new projects. It isn't as rich in terms of libraries but is better versioned.
- intel/2016b - This will likely play a role in the future but isn't being supported yet.
- iomkl/2015B - Primarily created for R but has other uses.
- iomkl/2016a - Similar to 2015B
- foss/2015B - Supported to some extent.
- foss/2016a - For testing future
- foss/2016b - Available, but not supported yet
Each of those has their own distinct combination of compiler/MPI/math. The newer ones will have more appeal to those using newer C++ codes. The older ones are probably more of interest to those with legacy code.
After you decide upon a toolchain, you can do something like:
module load intel/2016a # or ml intel/2016a # ml == module load in this case
module list # or ml # ml == module list in this case
to see what components are in the toolchain.
DO NOT MIX MODULES FROM DIFFERENT TOOLCHAINS... it only causes grief.
For more information about the module system on ada, please visit the modules page.
Using the intel toolchain
After initializing the compiler environment, you can use the "man" command to obtain a complete list of the available compilation options for the language you plan to use. For example:
man icc man icpc man ifort
will provide information on the C, the C++ and the Fortran compilers, respectively.
Each compiler requires appropriate file name extensions. These extensions are meant to identify files with different programming language contents, thereby enabling the compiler script to hand these files to the appropriate compiling subsystem: preprocessor, compiler, linker, etc. See table below for valid extensions for each language.
|.c||icc||C source code passed to the compiler.|
|.C, .CC, .cc, .cpp, .cxx||icpc||C++ source code passed to the compiler.|
|.f, .for, .ftn||ifort||fixed form Fortran source code passd to the compiler.|
|.fpp||ifort||Fortran fixed form source code that can be preprocessed by the Intel Fortran preprocessor fpp.|
|.f90||ifort||free form Fortran 90/95 source code passed to the compiler.|
|.F||ifort||Fortran fixed form source code, will be passed to preprocessor (fpp) and then passed to the Fortran compiler.|
|.o||icc/icpc/ifort||compiled object file--generated with the -c option--passed to the linker.|
NOTE: The icpc command ("C++" compiler) uses the same compiler options as the icc ("C" compiler) command. Invoking the compiler using icpc compiles '.c', and '.i' files as C++. Invoking the compiler using icc compiles '.c' and '.i' files as C. Using icpc always links in C++ libraries. Using icc only links in C++ libraries if C++ source is provided on the command line.