Skip to main content
Home
Home
  • About MaX
    • Goals
    • Organisation
    • MaX in a nutshell
    • People at MaX
    • Codes at MaX
    • Project Repository
    • Publications
    • Job openings
    • Newsletter
    • Communication
    • News & Events
    • MaX 2018-2021
  • Software
    • Codes
    • Features and algorithms
    • Libraries
    • Workflows
  • Exascale
    • Deployments
    • Programming models
    • Co-design
    • Performances
    • Separation of concerns
  • Data
    • Fact & Figures
  • Services
    • MaX Container technology for HPC system
    • MaX Help Desk
    • MaX High level consultancy
    • Simulations on premises and in the cloud
    • Turn-key materials solutions
    • Services to the Industry
    • Facts & Figures
    • FAQ
  • Training
    • Training materials
      • Open Online courses and videolectures
      • Presentations
      • Training material related to the MaX flagship codes
    • List of workshops & schools
    • Training through research in the MaX labs
    • Fact & Figures
  • Contact us
Home
  • About MaX

    About MAX

    MAX (MAterials design at the eXascale) is a European Centre of Excellence which enables materials modelling, simulations, discovery and design at the frontiers of the current and future High Performance Computing (HPC), High Throughput Computing (HTC) and data analytics technologies.

    • Goals
    • Organisation
    • MaX in a nutshell
    • People at MaX
    • Codes at MaX
    • Project Repository
    • Publications
    • Job openings
    • Newsletter
    • Communication
    • News & Events
    • MaX 2018-2021
  • Software

    SOFTWARE

    The software developed by MAX is made available to the whole community in open-source form. In this section you can find our main software output and how to obtain it.
     

    Codes

    Software libraries

    Features and algorithms

    Workflows

    Impact of MAX flagship codes

    • Codes
    • Features and algorithms
    • Libraries
    • Workflows
  • Exascale

    EXASCALE

    MAX addresses the challenges of porting, scaling, and optimising material science application codes for the peta- and exascale platforms in order to deliver best code performance and improve users productivity on the upcoming architectures.

    Programming models

    Performances

    Data on demand

    Co-design

    Data on demand

    Separation of concerns

    • Programming models
    • Co-design
    • Deployments
    • Performances
    • Separation of concerns
  • Data

    DATA

    MAX is committed in supporting data stewardship by adhering to the FAIR-sharing principles. High-quality data is provided both in the format of curated scientific results and raw data, focusing on the tracking of provenance to ensure the full reproducibility of results.

    Data at MaX

    Data at MaX

    Complete archived data

    Curated data

    Data on demand

    Data on demand

    FAIR data

    FAIR data

    Facts and Figures

    Facts and Figures

    • Fact & Figures
  • Services

    SERVICES

    MAX develops and offers services and technical support dedicated to the general public and the expert users from both industry and academia.

    MaX Helpdesk

    Help Desk

    max-high-level-consultancy-materials-science

    High level consultancy

    Turn-key materials solutions

    Turn-key materials solutions

    MaX Container technology for HPC system

    Container technology for HPC system

    Simulations on premises and in the cloud

    Simulations on premises and in the cloud

    Services to the Industry

    Services to the Industry

    Facts and Figures

    Facts and Figures

    FAQ

    FAQs

    • MaX Container technology for HPC system
    • MaX Help Desk
    • MaX High level consultancy
    • Simulations on premises and in the cloud
    • Turn-key materials solutions
    • Services to the Industry
    • Facts & Figures
    • FAQ
  • Training

    TRAINING

    MAX offers integrated training and education in the field of HPC developments and in the computational materials science domain, including workshops and schools, contributions to University courses and training through research in the CoE labs.

    List of workshops & schools

    Data on demand

    Training through research in the MaX labs

    Training materials

    Facts and Figures

    Facts and Figures

    • Training materials
      • Open Online courses and videolectures
      • Training material related to the MaX flagship codes
      • Presentations
    • List of workshops & schools
      • Quantum Espresso Targeting Accelerators
    • Training through research in the MaX labs
    • Fact & Figures
  • Contact us
  • About MaX
    • Goals
    • Organisation
    • MaX in a nutshell
    • People at MaX
    • Codes at MaX
    • Project Repository
    • Publications
    • Job openings
    • Newsletter
    • Communication
    • News & Events
    • MaX 2018-2021
  • Software
    • Codes
    • Features and algorithms
    • Libraries
    • Workflows
  • Exascale
    • Deployments
    • Programming models
    • Co-design
    • Performances
    • Separation of concerns
  • Data
    • Fact & Figures
  • Services
    • MaX Container technology for HPC system
    • MaX Help Desk
    • MaX High level consultancy
    • Simulations on premises and in the cloud
    • Turn-key materials solutions
    • Services to the Industry
    • Facts & Figures
    • FAQ
  • Training
    • Training materials
      • Open Online courses and videolectures
      • Presentations
      • Training material related to the MaX flagship codes
    • List of workshops & schools
    • Training through research in the MaX labs
    • Fact & Figures
  • Contact us

April 2020 Newsletter

Home / Newsletter / April 2020 Newsletter
*|MC:SUBJECT|* *|MC_PREVIEW_TEXT|*

April 2020 Newsletter

Dear Readers,

Welcome to our MaX April 2020 Newsletter. Our warmest wishes for these challenging times! In the following we update you on some of our ongoing activities, and start by offering some stimulating #StayHome opportunities available through the MaX website.

Our novel, capacity building materials include video lectures from the recent Yambo and Fleur schools as well as lectures recorded in the occasion of the school on High-Performance & High-Throughput Materials Simulations using Quantum ESPRESSO and AiiDA and the training material of the 3 weeks electronic structure course held by S. de Gironcoli: from blackboard to source code. Hands-on Tutorials on the MaX flagship codes can be followed online and you may also wish to visit the online school on Wannier90 that features the MaX codes.

For an introduction to first-principles electronic structure calculations, please see the online course by S. Cottenier. An introduction to Density Functional Theory will also be offered by Nicola Marzari with some live online seminars, based on MaX open-source codes such as Quantum Espresso, and on our Materials Cloud platform and tools.

A series of webinars for more advanced users and developers of our codes will be organized in the coming weeks: see the first dates in the news below. In these webinars we will highlight how the codes are prepared to run on the new HPC architectures, which are often accelerated.


Unfortunately, we had to postpone some events and schools due to the COVID-19 outbreak, including the Advanced School on Quantum Transport, the Digital Learning for Electronic Structure events and the school on First Principle Simulation with SIESTA. We will inform you about new plans as soon as possible.

Last but not least: if you need any support on MaX flagship code usage, the fora and mailing lists of the MaX flagship codes and the MaX help-desk are always active.

Please enjoy our insights below, do stay tuned, and most importantly, stay safe!

Save the dates for the first three MaX upcoming webinars on its codes in the next months of 2020: Quantum ESPRESSO on May 13, AiiDA on May 27, and Yambo on June 17.

DFT and GW towards the exascale: porting of the MaX codes on GPUs

 
MaX developers are working to support the European HPC community in view of the forthcoming supercomputing architectures. As of today, a number of MaX codes, as well as core libraries have been released production-ready with GPU-support on heterogeneous architectures.  This result, obtained through a deep refactoring of the main codes, is key to better exploit the potential offered by the future pre-exascale and exascale EuroHPC machines. The porting on GPUs has been done by adopting different GPU-aware programming models and libraries: CUDA-Fortran for Quantum ESPRESSO, Yambo and FLEUR, CUDA and OpenCL for BigDFT, CUDA and ROCm for SIRIUS and the DBCSR, COSMA and SpFFT libs. Noticeably, we have addressed the possibility of delivering  GPU acceleration as a library feature, like for the case of PSolver and the forthcoming libconv (BigDFT) and DBCSR-SpFFT (CP2K, CSCS).
 

Co-design in Materials Science Towards Exascale

 
Within the MaX co-design activity, Quantum ESPRESSO, one of the MaX flagship codes, has been used as a demonstrator for cutting edge new HPC technology (ARM + NVIDIA GPUs). In fact, at SC19 in Denver, NVIDIA showcased Quantum ESPRESSO running "live" on an ARM TX2+V100 system, comparing "live" performance with the ARM TX2 host alone. The exhibition was supported by a stand alone pod (in the NVIDIA booth) with an expert available all the time to run the demo with the many visitors.

read more >>

Machine Learning: Improved predictions for time-to-solution of material science simulations

 
The accurate prediction of the time-to-solution required by massively parallel scientific codes is a key goal in HPC. It allows scientists to better program and allocate their computational tasks, and benefits environmental sustainability since energy waste due to sub-optimal execution parameters could be easily detected.
However, this predictions are especially challenging for hybrid and complex architectures. Using machine learning techniques for DFT-based material science codes marks an important step in reducing such complexities. The results by Pittino et al, presented at PASC 19, show how accurate predictions obtained with machine learning approaches can outperform parametrized analytical performance models made by domain experts.

read more >>

MaX Training

Computational School on Electronic Excitations in Novel Materials using Yambo Code
 

The school “Electronic Excitations in Novel Materials using the Yambo code” was held at the International Center of Theoretical Physics (ICTP) campus in Trieste from 27th to 31st January 2020. The school, organized by the MaX Centre in collaboration with the Psi-K network, was held at ICTP as part of its 2020 scientific calendar.

read more >>

Hackathon on Domain-Specific Libraries  for Materials Modelling

 
The MaX Hackathon on Domain Specific Libraries for Material Modelling was held at the ICTP campus in Trieste, Italy, from the 25th to the 29th of November 2019. The program was a unique opportunity to advance the development of the MaX libraries along with the interfacing of the MaX flagship codes to those libraries.

read more >>
Subscribe here for regular updates and insights
Twitter
LinkedIn
Website
Email
MAX - MAterials design at the eXascale has received funding from the European Union’s Horizon 2020 - Research and Innovation program - under grant agreement no. 824143
Copyright © MAX 2020, all rights reserved.
You can
update your preferences or subscribe/unsubscribe from this list.






This email was sent to *|EMAIL|*
why did I get this?    unsubscribe from this list    update subscription preferences
*|LIST:ADDRESSLINE|*

*|REWARDS|*
Home

  • MAX Centre of Excellence
  • c/o CNR NANO
  • via Campi 213A
  • I-41125 Modena
  • ph +39 059 2055629
  • email: info@max-centre.eu
  • communication@max-centre.eu
SITEMAP
  • About MAX
  • SOFTWARE
  • EXASCALE
  • DATA
  • SERVICES
  • TRAINING
  • CONTACT US
INFORMATION
  • Privacy Policy
  • Terms and Conditions
Connect with us

©2023-MAX.All rights reserved.Privacy PolicyTerms of Service


MaX - Materials design at the Exascale has received funding from the European High Performance Computing Joint Undertaking and Participating Countries in Project (Czechia, France, Germany, Italy, Slovenia and Spain) under grant agreement no. 101093374.

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European High Performance Computing Joint Undertaking. Neither the European Union nor the granting authority can be held responsible for them.

© Copyright 2023