Difference between revisions of "Available software"
(→IBM-AI Deep Learning Anaconda Channel: change URL on advice from CWhidden) |
|||
| (One intermediate revision by one other user not shown) | |||
| Line 30: | Line 30: | ||
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. | 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:// | + | conda config --prepend channels https://ftp.osuosl.org/pub/open-ce//1.2.2/ |
| − | + | 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 == | ||
| − | 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 | + | [https://developer.ibm.com/linuxonpower/deep-learning-powerai/ 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 | dlinsights | ||
| Line 55: | Line 56: | ||
/software/WMLA/anaconda3/envs/dlipy36-wmlce170/bin/python | /software/WMLA/anaconda3/envs/dlipy36-wmlce170/bin/python | ||
(dlipy36-wmlce170) [luy@ds-lg-01 ~]$ conda list | (dlipy36-wmlce170) [luy@ds-lg-01 ~]$ conda list | ||
| − | |||
| − | |||
| − | |||
| + | Users can find more frameworks at the following locations | ||
{| class="wikitable" | {| class="wikitable" | ||
!Framework | !Framework | ||
Latest revision as of 15:35, 8 March 2022
Contents
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>
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.
