Version: 18.04
Included Packages:
Example GCLI startContainers call:
$ gcli startContainers Lancium/ubuntu18.04.simg MyUbuntuJob 1 \
"echo hello world" \
-o ubuntuoutput.txt stdout.txt
Version: Ubuntu 18.04, CUDA 9.2
Included Packages:
Environment:
CUDA_HOME=/usr/local/cuda
Example GCLI startContainers call:
$ gcli startContainers Lancium/ubuntu18.04_cuda9.2.simg MyUbuntuJob 1 \
"echo hello world" \
-o ubuntu_cuda_output.txt stdout.txt
Author: KTH Royal Institute Access here
Version:
$ gmx --version
GROMACS: gmx, version 2018.8
Executable: /usr/local/gromacs/bin/gmx
Data prefix: /usr/local/gromacs
Working dir: /tmp
Command line:
gmx --version
GROMACS version: 2018.8
Precision: single
Memory model: 64 bit
MPI library: thread_mpi
OpenMP support: enabled (GMX_OPENMP_MAX_THREADS = 64)
GPU support: CUDA
SIMD instructions: AVX_256
FFT library: fftw-3.3.8-sse2-avx-avx2-avx2_128-avx512
RDTSCP usage: enabled
TNG support: enabled
Hwloc support: disabled
Tracing support: disabled
Built on: 2019-12-02 16:33:44
Built by: root@lmf03ab2300 [CMAKE]
Build OS/arch: Linux 4.15.0-62-generic x86_64
Build CPU vendor: Intel
Build CPU brand: Intel(R) Xeon(R) CPU E5-2680 0 @ 2.70GHz
Build CPU family: 6 Model: 45 Stepping: 7
Build CPU features: aes apic avx clfsh cmov cx8 cx16 htt intel lahf mmx msr nonstop_tsc pcid pclmuldq pdcm pdpe1gb popcnt pse rdtscp sse2 sse3 sse4.1 sse4.2 ssse3 tdt x2apic
C compiler: /usr/bin/cc GNU 7.4.0
C compiler flags: -mavx -O3 -DNDEBUG -funroll-all-loops -fexcess-precision=fast
C++ compiler: /usr/bin/c++ GNU 7.4.0
C++ compiler flags: -mavx -std=c++11 -O3 -DNDEBUG -funroll-all-loops -fexcess-precision=fast
CUDA compiler: /usr/local/cuda/bin/nvcc nvcc: NVIDIA (R) Cuda compiler driver;Copyright (c) 2005-2019 NVIDIA Corporation;Built on Sun_Jul_28_19:07:16_PDT_2019;Cuda compilation tools, release 10.1, V10.1.243
CUDA compiler flags:-gencode;arch=compute_30,code=sm_30;-gencode;arch=compute_35,code=sm_35;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=compute_75;-use_fast_math;-D_FORCE_INLINES;; ;-mavx;-std=c++11;-O3;-DNDEBUG;-funroll-all-loops;-fexcess-precision=fast;
CUDA driver: 10.20
CUDA runtime: 10.10
Environment:
There is nothing specific to GROMACS setup in the environment apart from /usr/local/gromacs/bin/ being added to the search path.
Example GCLI startContainers call:
$ gcli startContainers Lancium/gromacs.simg MyGromacsJob 1 \
"gmx --version" \
-o gmxoutput.txt stdout.txt
Version: 6.4.1
Environment:
QE_BIN_PATH=/q-e-qe-6.4.1/bin/ the install directory of Quantum Espresso
Included binaries:
$ ls $QE_BIN_PATH
alpha2f.x fermi_velocity.x ld1.x pp.x simple_bse.x
average.x fqha.x manycp.x ppacf.x simple_ip.x
bands.x fs.x manypw.x projwfc.x spectra_correction.x
bse_main.x generate_rVV10_kernel_table.x matdyn.x pw.x sumpdos.x
cell2ibrav.x generate_vdW_kernel_table.x molecularnexafs.x pw2bgw.x turbo_davidson.x
cp.x gww.x molecularpdos.x pw2critic.x turbo_eels.x
dist.x gww_fit.x neb.x pw2gw.x turbo_lanczos.x
dos.x head.x open_grid.x pw2wannier90.x turbo_spectrum.x
dynmat.x hp.x path_interpolation.x pw4gww.x wannier_ham.x
epa.x ibrav2cell.x ph.x pwcond.x wannier_plot.x
epsilon.x initial_state.x phcg.x pwi2xsf.x wfck2r.x
ev.x iotk plan_avg.x q2qstar.x wfdd.x
fd.x iotk.x plotband.x q2r.x xspectra.x
fd_ef.x iotk_print_kinds.x plotproj.x q2trans.x
fd_ifc.x kpoints.x plotrho.x q2trans_fd.x
fermi_proj.x lambda.x pmw.x simple.x
Example GCLI startContainers call:
$ gcli startContainers Lancium/QuantumEspresso.simg MyQEJob 1 \
"pw.x" \
-o QEoutput.txt stdout.txt
Version: Amber 18 CUDA Version: 9.2
Environment:
AMBERHOME=/opt/amber, the install directory of AMBER.
Included Binaries:
$ ls $AMBERHOME/bin
AddToBox atomtype lmanal nef_to_RST resp
CartHess2FC.py bondtype makeANG_RST new2oldparm respgen
ChBox car_to_files.py makeCHIR_RST new_crd_to_dyn rism1d
CheckMD ceinutil.py makeDIST_RST new_to_old_crd rism3d.orave
FEW.pl cestats make_crd_hg nf-config rism3d.snglpnt
IPMach.py charmmlipid2amber.py mdgx nfe-umbrella-slice rism3d.thermo
MCPB.py cpeinutil.py mdnab nmode sander
MMPBSA.py cphstats mdout2pymbar.pl packmol sander.LES
OptC4.py cpinutil.py mdout_analyzer.py packmol-memgen saxs_md
PdbSearcher.py cpptraj memembed paramfit saxs_rism
ProScrs.py cpptraj.cuda metatwist parmchk2 senergy
PropPDB dacdif minab parmed sgldinfo.sh
UnitCell elsize mm_pbsa.pl pbsa sgldwt.sh
addles espgen mm_pbsa_nabnmode pbsa.cuda softcore_setup.py
am1bcc espgen.py mm_pbsa_statistics.pl pdb4amber sqm
amb2chm_par.py fantasian mmpbsa_py_energy pmemd sviol
amb2chm_psf_crd.py ffgbsa mmpbsa_py_nabnmode pmemd.cuda sviol2
amber.conda fftw-wisdom mol2rtf.py pmemd.cuda_DPFP teLeap
amber.ipython fftw-wisdom-to-conf molsurf pmemd.cuda_SPFP tinker_to_amber
amber.jupyter finddgref.py nab prepgen tleap
amber.pip fitpkaeo.py nab2c process_mdout.perl to_be_dispatched
amber.python fix_new_inpcrd_vel nc-config process_minout.perl ucpp
ambmask fixremdcouts.py nccopy pymdpbsa volslice
ambpdb gbnsr6 ncdump pytleap xaLeap
ante-MMPBSA.py genremdinputs.py ncgen reduce xleap
antechamber hcp_getpdb ncgen3 residuegen xparmed
Example GCLI startContainers call:
$ gcli startContainers Lancium/L_amber18-cuda9.2.simg MyAmberJob 1 \
"/opt/amber/bin/pmemd.cuda --help" \
-o amberoutput.txt stdout.txt
Please also see the comprehensive AMBER demo.
Note: All of our ML containers (except for Theano, currently a work in progress) are built for both python3 and python2. If you wanted to use the PyCaffe python2 or python3 variant, indicate that by using Lancium/py3_pycaffe when you call startContainers.
Version:
$ caffe --version
caffe version 1.0.0
Debug build (NDEBUG not #defined)
Environment:
$PATH includes the directory containing the binaries for caffe.
/opt/conda/envs/caffe2/bin in Python2 Container
/opt/conda/envs/caffe/bin in Python3 Container
Example GCLI startContainers call:
$ gcli startContainers Lancium/py2_caffe.simg MyCaffeJob 1 \
"caffe --version" \
-o caffeoutput.txt stdout.txt
$ gcli startContainers Lancium/py3_caffe.simg MyCaffeJob 1 \
"caffe --version" \
-o caffeoutput.txt stdout.txt
Version:
1.14.0 in Python 2 Container 1.13.1 in Python 3 Container
Environment:
Tensorflow binary path included in search path.
/opt/conda/envs/tensorflow-gpu2/bin in Python 2 Container
/opt/conda/envs/tensorflow-gpu/bin in Python 3 Container
Example GCLI startContainers call:
$ gcli startContainers Lancium/py2_tensorflow.simg MyTensorflowJob 1 \
"ls /opt/conda/envs/tensorflow-gpu2/bin" \
-o tf_output.txt stdout.txt
$ gcli startContainers Lancium/py3_tensorflow.simg MyTensorflowJob 1 \
"ls /opt/conda/envs/tensorflow-gpu/bin" \
-o tf_output.txt stdout.txt
Version:
1.0.4 in Python 2 Container
Environment:
Theano binary path included in search path.
/opt/conda/envs/theano2/bin in Python 2 Container
Example GCLI startContainers call:
$ gcli startContainers Lancium/py2_theano.simg MyTheanoJob 1 \
"ls /opt/conda/envs/theano2/bin" \
-o theano_output.txt stdout.txt
Version:
1.1.0 in Python 2 Container 1.0.0 in Python 3 Container
Environment:
PyTorch binary path included in search path.
/opt/conda/envs/pytorch2/bin in Python 2 Container
/opt/conda/envs/pytorch/bin in Python 3 Container
Example GCLI startContainers call:
$ gcli startContainers Lancium/py2_pytorch.simg MyPyTorchJob 1 \
"ls /opt/conda/envs/pytorch2/bin" \
-o pytorch_output.txt stdout.txt
$ gcli startContainers Lancium/py3_pytorch.simg MyPyTorchJob 1 \
"ls /opt/conda/envs/pytorch/bin" \
-o pytorch_output.txt stdout.txt