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All ThaiSC modules are located at the same module path, so there is no module hierarchy. Executing module avail on LANTA will display all available ThaiSC modules. For a more concise list, you can use module overview, then, use module whatis spider <name> or module help <name> to learn more about a each specific module.
Users can readily use ThaiSC modules and CPE toolchains to build their applications. Some popular application software are pre-installed as well, for more information, refer to Applications usage.
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username@lanta-xname:~> module overview ------------------------------------- /lustrefs/disk/modules/easybuild/modules/all -------------------------------------- ADIOS2 (2) FriBidiGATK (21) MrBayesNASM (1) Trimmomatic (1) Tcl hwloc (12) ATK groff (2) ATK GATK (2) GDAL (1) NASM (2) NLopt (12) UDUNITS2Tk (12) hwloc intltool (1) Amber (1) GDALGEOS (2) NLopt Nextflow (2) VASP Trimmomatic (3(1) jbigkit intltool (21) Apptainer (1) GEOSGLM (2) NextflowNinja (21) VCFtoolsUDUNITS2 (1) libGLUjbigkit (2) Armadillo (2) GLMGLib (2) Ninja OSPRay (12) WPS VASP (23) libaeclibGLU (2) AutoDock-vina (1) GLibGMP (23) OpenCASCADE OSPRay (2) VCFtools (21) WRFlibaec (12) Autoconf libdeflate (21) Autoconf GObject-Introspection (2) (1)OpenEXR GMP (2) WPS (32) OpenCASCADE libdeflate (2) Automake WRFchem (1) libdrmGROMACS (2) Automake (12) GObject-Introspection (2)OpenFOAM OpenEXR (2) WRF (2) Wayland (21) libepoxylibdrm (2) Autotools (1) GSL GROMACS (23) OpenFOAMOpenJPEG (2) X11 WRFchem (2) libffilibepoxy (12) BCFtools (1) GSL Gaussian (31) OpenJPEGOpenMPI (21) XZWayland (2) libffi (3) libgeotiff (21) BEDTools (1) GaussianGenericIO (12) OpenSSL (1) Xerces-C++X11 (12) libglvndlibgeotiff (2) BLAST+ (1) Gmsh GenericIO (21) OpenTURNS (2) XZ Yasm (13) libiconvlibglvnd (2) BLASTDB (1) Go (1) PCRE (1) arpackXerces-ngC++ (21) libjpeg-turbolibiconv (32) BWA (1) HDF-EOS (2) PCRE2 (1) Yasm (1) libjpeg-turbo (3) BamTools (1) HDF (2) PDAL assimp (1) arpack-ng (12) libpciaccess (2) Beast BamTools (1) HDFHTSlib (1) (2)PETSc PDAL (2) assimp (1) at-spi2-atk (2) libpng (3) BeastBison (1) HYPRE HTSlib (12) PETScPROJ (2) at-spi2-coreatk (2) libreadline (2) BisonBlosc (12) HYPREHarfBuzz (2) PROJPango (2) awsat-ofispi2-ncclcore (12) libtirpc (2) BloscBoost (2)4) ICU HarfBuzz (23) PangoParFlow (21) beagleaws-ofi-libnccl (1) libtool (1) BoostBowtie (4) (1) ICU Imath (32) ParMETIS (2) binutils beagle-lib (1) libunwind (2) Bowtie Bowtie2 (1) ImathJasPer (23) ParaView ParallelIO (1) bzip2 binutils (31) libxml2 (3) Bowtie2Brotli (12) Java JasPer (2) PerlParallelIO (2(1) cURL bzip2 (13) lz4 (3) Brotli C-Blosc2 (2) Java KaHIP (2) Perl PostgreSQL (2) cURL cairo (21) minimap2 (1) CFITSIO C-Blosc2 (2) KaHIPLAME (2)1) PostgreSQL QuantumESPRESSO (2) canucairo (12) nccl (1)) CGAL CFITSIO (2) LAMELLVM (1) RAxML-NG QuantumESPRESSO (2) canu (1) cpeCray (1) ncurses (2) CGAL CMake (2) LLVMLMDB (1) SAMtoolsRAxML-NG (1) cpeGNUcpeCray (1) nlohmann_json (1) CMake CrayNVHPC (1) LibTIFF (2) LMDB (2) SAMtools (1) SCOTCHcpeGNU (1) (2)numactl cpeIntel (1) DB numactl (12) CrayNVHPC M4 (1) LibTIFF (21) SDL2 SCOTCH (2) ecCodescpeIntel (21) pixman (1) DB DBus (21) M4MAFFT (1) SLEPcSDL2 (2) expat ecCodes (2) pkgconf (1) DBusESMF (12) MAFFTMETIS (12) SLEPc SPAdes (12) flexexpat (12) tbb (1) ESMFEasyBuild (1) MPC (2) METIS (2) SQLiteSPAdes (2)1) flex fontconfig (21) termcap (1) EasyBuildEigen (1) MPC MPFR (2) SWIGSQLite (32) freetype fontconfig (2) x264 (1) FDS Eigen (1) MPFRMUMPS (23) SZ SWIG (23) gettextfreetype (12) x265 (1) FDS FFmpeg (12) Mako MUMPS (2) SpectrASYCL (1) git-lfsgettext (1) xorg-macros (2) FFmpegFastQC (21) MakoMamba (2)1) SZ SuiteSparse (2) git-lfs googletest (1) xprop (2) FastQCFortranGIS (12) Mesa Mamba (12) SuperLU_DISTSpectrA (2) gperf (1) googletest (1) zfp (2) FreeXL FortranGIS (2) MesaMeson (2) TclSuiteSparse (2) gperf (2) gperftools (21) zlib (2) FreeXL FriBidi (2) MesonMrBayes (21) Tk SuperLU_DIST (2) groff gperftools (2) zstd (3) |
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1. Slurm sbatch header
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The
#SBATCH macro directives can be used to specify sbatch options that mostly unchanged, such as partition, time limit, billing account, and so on. For optional options like job name, users can specify them when submitting the script (see Submitting a job). For more details regarding sbatch options, please visit Slurm sbatch. Mostly, Slurm sbatch options only define and request computing resources that can be used inside a job script. The actual resources used by a software/executable can be different depending on how it will be invoked/issued (see Stage 5), although these sbatch options are passed and become the default options for it. For GPU jobs, we recommend using either --gpus or --gpus-per-node to request GPUs at this stage; additionally, please see GPU bindingstage will provide the most flexibility for the next stage, GPU binding.
If your application software only supports parallelization by multi-threading, then your software cannot utilize resources across nodes; in this case, therefore, -N, -n, --ntasks and --ntasks-per-node should be set to 1.
2. Loading modules
It is advised to load every module used when installing the software in the job script, although build dependencies such as CMake, Autotools, and binutils can be omitted. Additionally, those modules should be of the same version as when they were used to compile the program.
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When executing your program, if you encounter
Preliminary check could be performed on frontend node by doing something like
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4. Setting environment variables
Some software requires additional environment variables to be set at runtime; for example, the path to the temporary directory. Parameters Output environment variables set by Slurm sbatch (see Slurm sbatch - output environment variables) could be utilized in setting up used to set software-specific environment variablesparameters.
For application with OpenMP threading, OMP_NUM_THREADS, OMP_STACKSIZE, ulimit -s unlimited are commonly set in a job script. An example is shown below.
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Usually, either srun, mpirun, mpiexec or aprun is required to run MPI programs. On LANTA, srun command MUST be used insteadto launch MPI processes. The table below compares a few options of those commands.
Command | Total MPI processes | CPU per MPI process | MPI processes per node |
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srun | -n, --ntasks | -c, --cpus-per-task | --ntasks-per-node |
mpirun/mpiexec | -n, -np | --map-by socket:PE=N | --map-by ppr:N:node |
aprun | -n, --pes | -d, --cpus-per-pe | -N, --pes-per-node |
There is usually no need to explicitly add options option to srun since, by default, Slurm will automatically derive them from sbatch, with the exception of --cpus-per-task.
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For multi-threaded hybrid (MPI+Multi-threading) applications, it is essential to specify |
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You can test your initial script on compute-devel or gpu-devel partitions, using |
Your entire job script will only run on the first requested node (${SLURMD_NODENAME}). Only the lines starting with srun could initiate process and run on the other nodes.
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Example
Installation guide
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