Difference between revisions of "Available software"

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(→‎IBM-AI Deep Learning Anaconda Channel: change URL on advice from CWhidden)
 
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See [[Installing local software]] for instructions on installing and managing your own python environments in your home directory.
 
See [[Installing local software]] for instructions on installing and managing your own python environments in your home directory.
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==IBM-AI Deep Learning Anaconda Channel==
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To use deep learning packages like Tensorflow, pytorch, caffe on DeepSense you need to add the IBM-AI anaconda channel to your list of available software channels using below command.
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conda config --prepend channels https://ftp.osuosl.org/pub/open-ce//1.2.2/
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See also [https://docs.deepsense.ca/index.php?title=Installing_Software#3._Installation_of_Deep_Learning_packages| Installing Software].
  
 
== IBM WMLA Deep Learning Packages ==
 
== IBM WMLA Deep Learning Packages ==
  
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[https://developer.ibm.com/linuxonpower/deep-learning-powerai/ IBM PowerAI] includes multiple open source deep learning frameworks compiled for IBM Power8 systems.
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[https://developer.ibm.com/linuxonpower/deep-learning-powerai/ WMLA] includes multiple open source deep learning frameworks compiled for IBM Power8 systems.
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Anaconda under the WMLA install is a global install that can be accessed from any systems on DeepSense's platform. It is different from the anaconda install in users' home directories. Therefore, users cannot modify anything under the install of WMLA. However, users can use (i.e., read permission) the conda environments that have been created. If the environments created cannot satisfy your requirements, please feel free to ask the DeepSense support to create the environments for you. WMLA has following pre-developed environments which are ready to use by the users.
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dlinsights
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dlipy36-wmlce161
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dlipy36-wmlce162
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dlipy36-wmlce170
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dlipy37-wmlce170
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Users can check the version of the packages under these environments by activating the environment.
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Below is the method for using these environments.
  
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IBM WMLA Enterprise includes:
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[luy@ds-lg-01 ~]$ ls /software/WMLA/anaconda3/envs
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dlinsights dlipy36-wmlce161 dlipy36-wmlce162 dlipy36-wmlce170 dlipy37-wmlce170
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[luy@ds-lg-01 ~]$ source /software/WMLA/anaconda3/etc/profile.d/conda.sh
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[luy@ds-lg-01 ~]$ which conda
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/software/WMLA/anaconda3/bin/conda
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[luy@ds-lg-01 ~]$ conda activate dlipy36-wmlce170
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(dlipy36-wmlce170) [luy@ds-lg-01 ~]$ which python
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/software/WMLA/anaconda3/envs/dlipy36-wmlce170/bin/python
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(dlipy36-wmlce170) [luy@ds-lg-01 ~]$ conda list
  
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Users can find more frameworks at the following locations
 
{| class="wikitable"
 
{| class="wikitable"
 
!Framework
 
!Framework
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|Caffe
 
|Caffe
 
|/opt/DL/caffe
 
|/opt/DL/caffe
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|
 
|-
 
|-
 
|cuDNN
 
|cuDNN
 
|/opt/DL/cudnn
 
|/opt/DL/cudnn
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|
 
|-
 
|-
 
|IBM Distributed Deep Learning (DDL)
 
|IBM Distributed Deep Learning (DDL)
 
|/opt/DL/ddl
 
|/opt/DL/ddl
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|
 
|-
 
|-
 
| HDF5
 
| HDF5
 
|/opt/DL/hdf5
 
|/opt/DL/hdf5
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|
 
|-
 
|-
 
|NCCL
 
|NCCL
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|openblas
 
|openblas
 
|/opt/DL/openblas
 
|/opt/DL/openblas
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|
 
|-
 
|-
 
|protobuf
 
|protobuf
 
|/opt/DL/protobuf
 
|/opt/DL/protobuf
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|
 
|-
 
|-
 
|pytorch
 
|pytorch
 
|/opt/DL/pytorch
 
|/opt/DL/pytorch
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|
 
|-
 
|-
 
|snap-ml
 
|snap-ml
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|Tensorboard
 
|Tensorboard
 
|/opt/DL/tensorboard
 
|/opt/DL/tensorboard
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|
 
|}
 
|}
  

Latest revision as of 15:35, 8 March 2022

Basic Software

  • RedHat Enterprise Linux Server release 7.7 (RHEL)
  • gcc 4.8.5
  • glibc 2.17
  • R 3.6.0

Anaconda Python

DeepSense has two Anaconda python environments. Anaconda 2 is installed on each compute node. While Anaconda 3 is installed in a shared directory that can be accessed from any machines in the cluster.

Version Environment location
python 2.7.15 /opt/anaconda2
python 3.7.4 /software/WMLA/anaconda3/

These python environments have many packages installed, including prerequisite libraries for running the IBM PowerAI deep learning frameworks.

See Getting_started for instructions on using the shared anaconda python environments.

See Installing local software for instructions on installing and managing your own python environments in your home directory.

IBM-AI Deep Learning Anaconda Channel

To use deep learning packages like Tensorflow, pytorch, caffe on DeepSense you need to add the IBM-AI anaconda channel to your list of available software channels using below command. 

conda config --prepend channels https://ftp.osuosl.org/pub/open-ce//1.2.2/

See also Installing Software.

IBM WMLA Deep Learning Packages

WMLA includes multiple open source deep learning frameworks compiled for IBM Power8 systems. Anaconda under the WMLA install is a global install that can be accessed from any systems on DeepSense's platform. It is different from the anaconda install in users' home directories. Therefore, users cannot modify anything under the install of WMLA. However, users can use (i.e., read permission) the conda environments that have been created. If the environments created cannot satisfy your requirements, please feel free to ask the DeepSense support to create the environments for you. WMLA has following pre-developed environments which are ready to use by the users. 

dlinsights
dlipy36-wmlce161
dlipy36-wmlce162
dlipy36-wmlce170
dlipy37-wmlce170

Users can check the version of the packages under these environments by activating the environment. Below is the method for using these environments. 

[luy@ds-lg-01 ~]$ ls /software/WMLA/anaconda3/envs
dlinsights dlipy36-wmlce161 dlipy36-wmlce162 dlipy36-wmlce170 dlipy37-wmlce170
[luy@ds-lg-01 ~]$ source /software/WMLA/anaconda3/etc/profile.d/conda.sh 
[luy@ds-lg-01 ~]$ which conda
/software/WMLA/anaconda3/bin/conda
[luy@ds-lg-01 ~]$ conda activate dlipy36-wmlce170
(dlipy36-wmlce170) [luy@ds-lg-01 ~]$ which python
/software/WMLA/anaconda3/envs/dlipy36-wmlce170/bin/python
(dlipy36-wmlce170) [luy@ds-lg-01 ~]$ conda list

Users can find more frameworks at the following locations

Framework Location
Caffe /opt/DL/caffe
cuDNN /opt/DL/cudnn
IBM Distributed Deep Learning (DDL) /opt/DL/ddl
HDF5 /opt/DL/hdf5
NCCL /opt/DL/nccl /opt/DL/nccl2
openblas /opt/DL/openblas
protobuf /opt/DL/protobuf
pytorch /opt/DL/pytorch
snap-ml /opt/DL/snap-ml-local /opt/DL/snap-ml-mpi
Tensorflow 1.11 (including keras) /opt/DL/tensorflow /opt/DL/ddl-tensorflow
Tensorboard /opt/DL/tensorboard

To use most of these frameworks you need to activate a python2 or python3 environment and then activate the relevant framework.

For example, to use tensorflow you can activate a python2 environment: 

. /opt/anaconda2/etc/profile.d/conda.sh
conda activate

and then activate tensorflow: 

source /opt/DL/tensorflow/bin/tensorflow-activate

You can then import tensorflow as tf in your python code.

See Getting started with Deep Learning for a tutorial on using Caffe and Tensorflow on Deep Sense.

IBM Advance Toolchain

You may require newer versions of compilers such as GCC than are provided with RHEL.

The IBM Advance Toolchain for Linux on Power is a set of open source compilers, runtime libraries, and development tools.

The IBM Advance Toolchain] includes recent versions of:

  • GNU Compiler Collection (gcc, g++ and gfortran)
  • GNU C library (glibc)
  • GNU Binary Utilities (binutils)
  • Decimal Floating Point Library (libdfp)
  • IBM Power Architecture Facilities Library (PAFLib)
  • GNU Debugger (gdb)
  • Python
  • Golang
  • Performance analysis tools (oprofile, valgrind, itrace)
  • Multi-core exploitation libraries (TBB, Userspace RCU, SPHDE)
  • support libraries (libhugetlbfs, Boost, zlib, etc)

To use the the Advance Toolchain, first activate environment modules: 

source /usr/local/Modules/init/bash

Then load the advance toolchain: 

module load at12.0

To stop using the advance toolchain, unload the environment module: 

module unload at12.0

Note that software dynamically compiled with the advance toolchain will only run with the advance toolchain loaded.

Requested Software

Software packages that are requested for use by DeepSense projects will be available in several locations. Our preference is to use conda packages when available.

External conda channels

If a requested software is available for ppc64le systems from an externally maintained anaconda channel then we will simply list the channel. You can install such software into a local anaconda environment using: 

conda install -c <channel> <software>

Internal conda packages

When possible, software compiled by DeepSense staff will compiled using conda build and placed in a subdirectory of /software/conda-bld/ . You can install such software into a local anaconda environment using: 

conda install -c file://software/conda-bld/ <software>

Shared software

Some software will simply be installed in its own subdirectory of /software. You can run this software directly from its subdirectory.

Bioinformatics Software

Software Version Location
trimmomatic 0.39 /software/trimmomattic-0.39
cutadapt 2.3 /software/conda-bld/linux-ppc64le/
bowtie2 biobuilds channel
LAST 980 /software/last-980
Burrows wheeler aligner 0.7.15 /software/bwa
pb-falcon 2.2.0 /software/conda-bld/linux-ppc64le/
MASURCA 3.3.4 /software/conda-bld/linux-ppc64le/
Samtools 1.9 /software/conda-bld/linux-ppc64le/
htslib 1.9 /software/conda-bld/linux-ppc64le/
bcftools 1.9 /software/conda-bld/linux-ppc64le/
gatk 4.1.2.0 /software/conda-bld/noarch/
stacks 2.4 /software/conda-bld/linux-ppc64le/
angsd 0.923 /software/conda-bld/linux-ppc64le/
vcftools biobuilds channel
plink biobuilds channel
msprime 0.7.0 /software/conda-bld/linux-ppc64le/
slim 3.3 /software/slim-3.3
DeepGSR /software/DeepGSR

Requesting Additional Software

Contact DeepSense support to have additional software installed or for help installing or compiling software locally in your home directory.

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