Release Notes

Version 0.60.0

  • Updating LAMMPS image to version 29Oct2020 and the corresponding LAMMPS-AWESEMMD

  • New prototypes for NWChem workflow menus in NWChem NEXT examples

  • Prototype of new launchpad PySide2 application for starting cloud resources in place.

  • New quantum chemistry code DALTON image available

  • Major revision to Chemistream starting application:
    • JupyterLab local manager session is deprecated

    • Startup GUI now manages license file installation and cloud startup functions

    • Multiple remote compute sessions can now be managed through startup GUI

    • Improved error handling throughout the startup process

  • Reworking of compute session workflows for ALFABET, NWChem and Dalton to use ipywidgets for all functions

  • Improving startup user instructions for all remote workflows

  • New streamlined workflows for Dalton and NWChem for
    • scaling studies

    • parsing HOMO/LUMO values

    • series of runs given input SMILES strings

    • calculating hyperpolarizabilities

  • Implemented multi-stage builds for Docker images resulting in a further 50% size reduction

  • Updating panel and panel-chemistry dependencies resulting in faster app/image installs

  • Updating to JupyterLab=3.3.0

  • Using jupyterlab_scenes module to enable auto-execution for turnkey workflows

Version 0.20.0

  • Reworked Chemistream application build system so pyinstaller no longer used, thereby resulting in smaller installers

  • Streamlined startup page on JupyterLab: Manager tab

  • Adding menu selection for new RLMolecule (from NREL) image

  • Adding menu selection for new SPPARKS image with proprietary ALD model pre-compiled

  • Adding menu selection for new NWChem image with the DDEC6 and Molden packages added

  • Maintaining separate local ports for remote cloud compute session and local compute session

  • Fixing temporary directory scratch space for NWChem sims

  • Improved docker desktop setup for ‘local’ compute session across platforms

  • Improved checks for installed docker and docker engine start for ‘local’ compute session

  • Updating LAMMPS and SPPARKS examples for better results parsing

  • Improved visualization for SPPARKS diffusion 3d example

  • Reworking of dependencies in Chemistream installer. The installer depends on Makalii and Jupyterlab only. All compute modules and codes are moved to Docker images available from Tech-X repo. All installers are nearly half as large.

  • Installer setup and configuration now ~2-3x faster due to simplified dependencies.

  • All Tech-X Docker images have been reworked for fewer dependencies and are smaller

  • JSME editor is now embedded in Jupyterlab notebooks, available through the Chemistream RDKitBase class

Version 0.12.1

  • Updating to conda Python 3.8

  • Updating to JupyterLab > 3

  • Updating ipywidgets to latest version that simplifies and speeds up installation

  • Updating pyinstaller and constructor packages to latest version (these can use conda python)

  • Adding menu selection for new GROMACS image

  • Using development version of NGLView that simplifies and speeds up installation

  • Removing STREAMM dependency from Chemistream module as this is only used in remote compute sessions. This has decreased the size of installers on all platforms

  • Adding ability to start a ‘local’ compute session so users can test workflows without need for configuring cloud accounts. This is valid on MacOS, Linux and Windows

  • Improving stability of setup of compute session

  • New example modules for BDE training model

  • Bug fixes for storage (Waihona) interface methods

Version 0.9.12

  • Removing py3Dmol dependencies and methods from ChemVis module

  • Adding NGLView dependencies and migrating from py3Dmol

  • New methods for NGLView added to ChemVis module

  • Adding example directories for rDock and QMCPack

Version 0.9.10

  • Upgrading to JupyterLab v 2.1.0

  • Examples for remote storage (eg AWS S3 and Azure Blob)

  • Adding RDKit dependency for a base class RDKitBase that is used by several examples’ derived classes.

  • Adding example for downloading OPV database info and analyzing with RDKit

  • Adding extra setup python files to tailor installs for app/cloud and (un)licensed versions

  • Freezing Miniconda version to version Miniconda3-py37_4.8.3-platform-x86_64.sh”

Version 0.9.8

  • Examples for machine learning, image recognition for ‘Digits’ and ‘Fashion’

  • Example for neural net prediction of bond dissociation energies using Alfabet

  • Example for complex P3HT workflow

Version 0.9.1

  • Cloud management for Amazon and AWS

  • Initial development of Jupyterlab framework using ipywidgets

  • Examples for scaling with NWChem, LAMMPS and SPPARKS

  • Cloud images all enabled with generation of multi-node HPC cluster

  • Cloud images all enabled with creation of NFS shared directory