Resource

High Performance Computers (DANEEL)



The research group is equipped with an independent Daneel cluster, with nearly 80+ CPU computing nodes, and independent nodes such as independent GPU and large memory. Most nodes are connected by InfiniBand (IB) high-speed network to support parallel computing across nodes. The system has built the Lustre high-performance cluster parallel file system, the SLURM job management system and the LMOD environment module management system. Moreover, the research group has long purchased computer machines from the Big Data Computing Center of Southeast University, National Supercomputing Center in Tianjin, and Jiangsu Zhonghe Cloud Computing to fully meet the computing needs of the research group.


 

  Partition

Count

Arch

Cores

RAM

Limitation

Nodes

  debug

2

E5 2680v4

28 Core

  64 Gb

12 Hours

node[09-10]

  GPU

1

RTX 2080Ti × 2

32 Core

192 Gb

100 Days

s05

  C2680

8

E5 2680v4

28 Core

  64 Gb

100 Days

node[01-08]

  C6132

10

Gold 6132

28 Core

192 Gb

100 Days

node[11-18]

s[01-02]

  C6240

10

Gold 6240

36 Core

192 Gb

100 Days

node[19-26]

s[03-04]

  C6240R

8

Gold 6240R

48 Core

192 Gb

100 Days

node[27-34]

  wang

6

Gold 6248R

48 Core

192 Gb

100 Days

s[06-11]

  C6326JU

11

Gold 6326

32 Core

256 Gb

100 Days

node[35-45]

  C6326LI

10

Gold 6326

32 Core

256 Gb

100 Days

node[46-55]

* Ethernet, Ethernet and InfiniBand.


 

Commonly Used Applications:

Density Functional Theory

Application

Versions

Default

berkeleygw

1.2, 2.1, 3.0.1

3.0.1

cp2k

6.1, 7.1, 8.2, 9.1

7.1

elk

6.8.4, 7.2.42, 8.4.6

8.4.6

gpaw

22.1.0

22.1.0

gromacs

2020.7, 2021.6, 2022.2

2022.2

jdftx

1.7.0

1.7.0

lammps

20.12.24, 21.09.29, 22.03.24

22.03.24

nwchem

6.8.1, 7.0.2

7.0.2

orca

3.0.3, 4.2.1, 5.0.3

5.0.3

qe

6.5, 6.8, 7.0, 7.1

7.1

siesta

3.2, 4.0.2, 4.1.5

4.0.2

vasp

5.4.1, 5.4.4, 5.4.4_mods, 6.1.2, 6.1.2_omp,

6.2.0, 6.2.0_omp, 6.3.0, 6.3.0_omp

6.3.0

yambo

4.5.3, 5.0.4, 5.1.0

5.1.0

 

Machine Learning Libraries

Application

Versions

Default

jax

0.1.56, 0.3.10

0.3.10

keras

2.8.0, 2.9.0

2.9.0

pytorch

1.5.0, 1.11.0

1.11.0

tensorflow

2.1.0, 2.8.0, 2.8.1, 2.9.0

2.9.0

xgboost

1.6.0, 1.6.1

1.6.1

 

Analysis Tools

Application

Versions

Default

gdb

9.2, 10.2, 11.2

11.2

gnuplot

5.4.3

5.4.3

lobster

4.0.0, 4.1.0

4.1.0

phonopy

2.14.0

2.14.0

sisso

2.4, 3.1

3.1

swig

3.0.12, 4.0.2

4.0.2

vaspkit

1.1.2, 1.2.5, 1.3.4

1.3.4

vtstscripts

978

978

wannier90

1.2, 2.1.0, 3.1.0

3.1.0

wanniertools

2.2.9, 2.5.1

2.5.1

 



Other Applications:

Program Environment

Application

Versions

Default

StdEnv

intelhpc-2022.2

intelhpc-2022.2

 

Utilities

Application

Versions

Default

autoconf

2.71

2.71

automake

1.16.5

1.16.5

gmake

4.3

4.3

binutils

2.38

2.38

cmake

3.16.9, 3.18.6, 3.20.6, 3.22.4

3.22.4

libtool

2.4.6

2.4.6

ninja

1.6.0, 1.8.2, 1.10.2

1.10.2

singularity

3.7.4, 3.9.9

3.9.9

texinfo

6.8

6.8

 

Languages

Application

Versions

Default

go

1.16.15, 1.17.9, 1.18.1

1.18.1

java

14.0.2, 15.0.2, 16.0.2, 17.0.2

17.0.2

julia

1.5.4, 1.6.6, 1.7.2

1.7.2

python

py27-2019.10, py37-2019.10, py38-2020.11,

py39-2021.11

py39-2021.11

rust

1.38.0, 1.48.0, 1.58.0, 1.60.0

1.60.0

 

Toolchains

Application

Versions

Default

gcc

4.8.5, 5.5.0, 6.5.0, 7.5.0, 8.5.0,

9.5.0, 10.3.0, 11.2.0, 12.1.0

12.1.0

intel

2017u8, 2018u4, 2019u5, 2020u4, 2021.4, 2022.2

2022.2

llvm

12.0.1, 13.0.1, 14.0.4

14.0.4

musl

1.2.0

1.2.0

intelmpi

2017u8, 2018u4, 2019u5, 2020u4, 2021.4, 2022.2

2022.2

openmpi

1.6.5-gcc, 1.6.5-intel, 2.1.6-gcc, 2.1.6-intel,

3.1.4-gcc, 3.1.4-intel, 4.1.1-gcc, 4.1.1-intel

4.1.1-intel

mpich

3.4.3-gcc, 3.4.3-intel, 4.0.2-gcc, 4.0.2-intel

4.0.2-intel

 

Libraries

Application

Versions

Default

boost

1.67.0_py39

1.67.0_py39

dftd4

2.5.0

2.5.0

eigen

3.4.0

3.4.0

elpa

2016.05.004, 2017.05.002, 2017.11.001,

2018.05.001, 2020.05.001, 2021.05.002,

2016.05.004_omp, 2017.05.002_omp,

2017.11.001_omp, 2018.05.001_omp, 

2020.05.001_omp, 2021.05.002_omp

2016.05.004

fftw

3.3.10, 3.3.10_mpi

3.3.10_mpi

flook

0.8.1

0.8.1

gsl

2.7.1

2.7.1

hdf5

1.10.8, 1.12.2

1.12.2

intelmkl

2017u8, 2018u4, 2019u5, 2020u4, 2021.4, 2022.2

2022.2

libbeef

0.1.3

0.1.3

libint

1.1.5, 2.6.0

2.6.0

libvdwxc

0.3.2, 0.4.0

0.4.0

libxc

4.3.4, 5.2.2

5.2.2

libxsmm

1.17

1.17

metis

5.1.0

5.1.0

netcdf-c

4.8.1

4.8.1

netcdf-cxx

4.3.1

4.3.1

netcdf-fortran

4.5.4

4.5.4

parmetis

4.0.3

4.0.3

pexsi

0.9.2, 0.10.2

0.10.2

plumed

2.8.0

2.8.0

pnetcdf

1.12.3

1.12.3

sirius

6.5.7, 7.3.1

6.5.7

spfft

0.9.13, 0.9.13_omp, 1.0.6, 1.0.6_omp

1.0.6

spglib

1.16.3

1.16.3

spla

1.5.4_omp

1.5.4_omp

superlu_dist

4.3, 5.2.2, 5.4.0

5.2.2